Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and the disease outcome commonly depends upon the tumour stage at the time of diagnosis. However, this cancer can often be asymptomatic during the early stages and remain undetected until the later stages of tumour development, having a significant impact on patient prognosis. However, our comprehension of the mechanisms underlying the development of gastric malignancies is still lacking. For these reasons, the search for new diagnostic and prognostic markers for gastric cancer is an ongoing pursuit. Modern mass spectrometry imaging (MSI) techniques, in particular matrix-assisted laser desorption/ionisation (MALDI), have emerged as a plausible tool in clinical pathology as a whole. More specifically, MALDI-MSI is being increasingly employed in the study of gastric cancer and has already elucidated some important disease checkpoints that may help us to better understand the molecular mechanisms underpinning this aggressive cancer. Here we report the state of the art of MALDI-MSI approaches, ranging from sample preparation to statistical analysis, and provide a complete review of the key findings that have been reported in the literature thus far. Gastric cancer (GC) develops from the lining of the stomach and is the fifth most common malignancy worldwide . The proMass spectrometry (MS)-based techniques have become some of the most prevalently employed analytical strategies for the detection and identification of endogenous biomolecules in tissue. The application of these techniques is now commonplace in clinical research ,4,5 and Matrix-assisted laser desorption/ionisation (MALDI) remains the most widely applied MSI technique owing to its capability to analyse a wide range of analyte classes  . In partIn this review, we provide a concise overview of the methodological aspects of MALDI-MSI and summarise how the technique has been used to advance gastric cancer research for the purpose of biomarker detection and monitoring treatment response.MALDI-MSI applied to thin mammalian tissue sections was formally introduced in 1997 and its use has increased exponentially in recent years . The tecTypical MALDI-MSI analysis is most commonly performed on tissue sections that have been sectioned and mounted onto electrically conductive glass slides, such as those coated with indium tin oxide (ITO) . For proRegarding the imaging of drugs and products of drug metabolism, MALDI-MSI has been readily used within the pharmaceutical community for the purpose of drug discovery and development . The monN-glycans in tissue [N-glycans and proteins within the same tissue section [N-glycans, one of the most common post-translational modifications, may significantly advance MALDI-MSI investigations in gastric cancer given their fundamental role in many cellular processes and their establishment as clinical biomarkers [In the case of protein imaging, formalin-fixed paraffin-embedded (FFPE) tissue is now also readily employed . FFPE tin tissue ,23, demo4Ac) is recommended for the desalting of tissue prior to lipidomic analysis [Particular attention to detail must be paid during the collection of FF tissue, as negligence during the sample collection can lead to degradation and delocalisation of the analytes of interest. The method most commonly employed during collection is snap-freezing using liquid nitrogen; however, this procedure can damage tissue morphology if it cools at different rates. This can be overcome to some degree by lightly wrapping the tissue in aluminium in order for it to cool at a more uniform rate . Alternaanalysis .N-Octanoyl-N-methylglucamin (MEGA-8) and RapiGest SF  [N-glycosidase F (PNGase F) in order to visualise the distribution of N-glycans that are associated with different pathological states of tissue [Regarding FFPE tissue, metabolite MS-imaging requires tissue immersion in xylene, or a similar organic solvent, in order to remove any paraffin . Proteinter, UK) ,35, and f tissue .Matrix deposition plays a crucial role in MALDI-MSI experiments and can limit the true spatial resolution that can be achieved. The general aim of the co-crystallisation process is to maximise analyte extraction whilst at the same time limiting the degree of lateral diffusion, which is equally important to the choice of matrix . Wet matN,N-dimethylaniline (CHCA/DANI) have been employed to obtain a more ubiquitous matrix layer and enhance the detection of protein signals [Depending on the target analyte of choice, a number of different matrices can be used. For example, DHB , sinapinic acid  and α-CHCA (α-cyano-4-hydroxycinnamic acid) are the most common matrices of choice for the extraction of low molecular weight proteins, peptides, and lipids (1–20 kDa) . However signals . For met signals . In view signals .m/z-bins for ToF MS and even greater than 1,000,000 m/z-bins for Fourier-transform ion cyclotron resonance (FTICR) MS measurements [m/z values. In fact, modern MALDI-FTICR-MS instrumentation, as well as MALDI linear ion trap (Orbitrap), can enable the unequivocal identification of certain analytes  based on their accurate mass alone [MALDI mass spectrometry instrumentation has rapidly evolved in recent years, offering ever more mass resolution and increased sensitivity. In fact, state-of-the-art MALDI-MS instrumentation enables the generation of individual spectra with intensities measured at 25,000–50,000 urements . These ass alone ,50. Furtss alone . Notwithss alone , not onlss alone ,54,55.x and y axes) of the digitalised tissue section are combined with a third dimension consisting of the mass-to-charge ratio (m/z) of the molecules present within the tissue section. Depending on the spatial resolution and the number of data points (sampling rate) per spectrum, a MALDI-MSI dataset can be of several gigabytes, even terabytes. Therefore, efficient statistical methods for data mining must be employed in order to extract information from the spectral data [MALDI-MSI records the presence and relative abundance of a great variety of molecules on tissue, allowing the localisation and spatial distribution of such molecules to be visualised. For each pixel of the digitalised tissue image, a mass spectrum is acquired, generating a so-called “data cube” A, a tensral data .x-axis and all the peak intensities are estimated from the x-axis itself. Normalisation multiplies the intensity of the data points of the spectra by a scaling factor in order to bring the intensity scale  within the same range and therefore make analyses more reproducible [m/z and intensity pair values. After peak maxima have been aligned to each other in order to account for fluctuations in the peak values among the spectra of the dataset related with the peak picking process, the data can be submitted to statistical analysis. Mostly, machine learning algorithms are employed for statistical analysis of the data cube, and, depending on the data provided and on the aim of the data mining process, unsupervised or supervised approaches are carried out , principal component analysis (PCA) and t-distributed stochastic neighbour embedding (t-SNE). Hierarchical clustering analysis (HCA) estimates the pairwise distance among data observations and generates a dendrogram, in which the observations are grouped under the same nodes based on their similarity to each other . In massOn the other hand, supervised learning aims at employing algorithms, referred to as classifiers, which learn from labelled data, i.e., data in which the outcome is known, in order to exploit known features (which correspond to peaks in the mass spectrometry imaging dataset) to make predictions about new, unknown data, resembling the classification problem . The firGastric cancer is a complex, heterogeneous and aggressive disease that represents the third leading cause of cancer-related deaths worldwide . Unfortu+ (m/z 798.541) using FTICR-MS/MS [m/z 798.5 has been detected in another MALDI-imaging study by Uehara et al., revealing that it was overexpressed in cancer tissue compared to the adjacent non neoplastic mucosa [m/z 496.3, identified as the proton-adducted lysophosphatidylcholine (LPC) (16:0), was low in cancer lesions [Recent genomic studies have discovered mutations in the GTPase, Ras homolog family member A (RHOA), that are associated with a poor clinical prognosis in patients with diffuse-type gastric cancers ,71. The CR-MS/MS . Similarc mucosa . On the  lesions .A recent study based on the integrated strategy of MALDI-MSI and immunohistochemical assays investigated the association of cancer progression and the effects of de novo lipogenesis . In factN-acetylneuraminic acid were significantly decreased in the cancerous area [In addition, MALDI-MSI in negative ion mode has the ability to visualise small molecule metabolites , which are important cellular components closely linked with tumour development and progression . Guo et ous area .The poor prognosis of gastric cancer is due to a lack of reliable tumour markers that may improve early-stage diagnosis of cancer. Recently, proteomic approaches using MALDI-MSI techniques have been adopted in order to better understand the pathology and to search for novel diagnostic and therapeutic targets through the characterisation of the proteome profile of a malignant lesion with respect to the non-tumour area.Deininger et al. employed hierarchical cluster analysis along with principal component analysis in order to uncover proteomic differences in gastric cancer tissue and non-neoplastic stomach mucosa . They dem/z 3445 (HNP-1) was overexpressed in cancer tissue, confirming the observation of two other MALDI-MSI studies on gastric cancer [m/z 4156, has been observed in the cancer area of intestinal-type gastric cancer and oesophageal adenocarcinoma [m/z 11,185, identified as S100 calcium binding protein A10 (S100A10), was an independent prognostic factor [m/z 1325.6 was specifically increased in the poorly differentiated cancer tissue and was identified as histone H4 [A recent MALDI-MSI study detected seven tumour-specific proteins that predicted unfavourable disease outcome in a cohort of 63 patients with intestinal gastric cancer . Three pc cancer ,85, and c cancer . Besidesc cancer , known tarcinoma ,87, and arcinoma . Moreovec factor . Among tstone H4 . Recentlstone H4 . Followistone H4 .The MALDI imaging approach in combination with two classification models (support vector machine and random forest) has been promisingly used for gastric cancer tumour classification as well as for the classification of the human epidermal growth factor receptor 2 (HER2/neu) status prediction in gastric cancer ,92. Medim/z 3445 (HNP-1) and m/z 14021 (histone H2A), respectively, which were found to be involved in the prognostic signature of the subpopulations [Thus far, intratumor heterogeneity is an unresolved factor that influences the evolution of cancer and adversely affects patient outcome. Phenotypically distinct gastric cancer subpopulations have been investigated by MALDI imaging in combination with advanced clustering methods and t-SNE ,84. In pulations ,84.N-glycans) in 106 primary resected FFPE human gastric cancer tissues by MALDI-MSI in order to understand the underlying molecular mechanisms and discover the clinical implications of glycosylation in gastric cancer [Among the post-translational modifications, glycosylation is the most abundant and complex, and alterations in the glycosylation of gastric cancer cells have an impact on gastric carcinogenesis and cancer progression ,94. Kunzc cancer . The stuc cancer .In the context of gastric cancer, the application of MALDI-MSI is still in its relative infancy. However, there is already sufficient evidence in the literature to suggest that MALDI-MSI can play a crucial role in uncovering the molecular pathways implicated in the development of this particularly deadly cancer.This approach has already detected molecular alterations associated with gastric cancer at the proteomic, lipidomic, and metabolomic level, and can also monitor the distribution and xenoboiotic metabolism of prospective therapeutic agents such as fasudil. On the basis of these findings, the potential of MALDI-MSI is evident and, by combining these findings using integrative omics approaches, we can improve our understanding of gastric cancer at numerous molecular levels and assist in the clinical management of patients. Whilst this final goal is not imminent, and cannot be achieved using a single approach, MALDI-MSI can certainly make a significant contribution to this pursuit. Nevertheless, the potential of MALDI-MSI for obtaining findings able to contribute to the diagnosis, prognosis, and understanding of numerous diseases, most specifically cancer, is expected to grow in the future as this technology advances.


Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant–plant and plant–microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground ‘signalomics’, and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial – and priming events. The world is facing a concerning challenge to produce sufficient food in a sustainable manner, with an increasing global population and decreasing food resources. Food plant production is hampered by a plethora of biotic stresses such as pathogens and herbivores . To defeFigure 1). Failure hereof, either below- or above-ground .Plants use preformed defense mechanisms aimed at preventing both pathogen entrance and herbivore feeding  to improve plant health. These inoculants are natural or synthetic microbial communities . This isFigure 2). In response to altered gene expression, plants subsequently release an array of metabolites (primary and secondary). It is through such communication that mutual relationships are established that are vital for root–root interactions . The term ‘signalomics’ describes these metabolomics approaches employed to decipher the chemical communications occurring within the rhizosphere.These organisms interact with each other and with the plant in a sophisticated manner, achieved by chemical communication established in the rhizosphere . These are low-molecular weight lipophilic compounds synthesized from different metabolic pathways and serve as a chemical window in which information is released   in Petri dishes  resulted in enhanced growth of A. thaliana. Here, 3-hydroxy-2-butanone (acetoin) and 2,3 butanediol were the common VOCs between the two strains  . VOCs prigure 3) . Certain strains .N-acyl homoserine degradation products, thereby enabling the study of signaling dynamics in QS  are species- or genotype-specific and can be differentially modified depending on the secreting source. Given this strong complexity and specificity, root exudates have the potential to overlay a much more detailed layer of information about the communication events in the rhizosphere  that initiate nodule formation in the roots. Interestingly, LCO also plays a role in interactions between arbuscular mycorrhizal fungi and plants. Furthermore, these flavonoids are able to mimic bacterial QS molecules, thus influencing bacterial metabolism  which induce bacterial tabolism . QS playtabolism . Differetabolism . In additabolism .Figure 2), either through secretion/release of certain signaling molecules .Communication between plants occurs below- and above-ground . Such compounds from Bacillus and Pseudomonas genera are the best studied in disease management  that act as antibiotics. These are classified into three families: iritin, fengycin and surfactin depending on the branching fatty acid  in a similar manner based on MAMPs such as lipopolysaccharide (LPS) and flagellin, and secondary metabolites. MAMPs from beneficial microbes are known to activate MTI, but in this case, the activated defenses do not ward off the beneficial microbes (Pseudomonas spp. produce SA under low iron conditions which is channeled toward SA-containing siderophores (P. aeruginosa (siderophore producing mutant KMPCH) was shown to induce systemic resistance  are well documented volatile signaling molecules (E)-ocimene, 6-methyl-5-hepten-2-one and (E)--caryophyllene (Z)-3-hexen-1-ol was found to have a two-fold priming effect and modulation of herbivorous insect behavior  that can significantly influence plant growth and crop yield , the success depends on the appropriate activation of defenses that can be faster, earlier, more sensitive, or stronger. These timeous activation of suitable defense responses in primed plants can save plants from becoming diseased or consumed, thus adding a benefit of off-set the cost of establishing the primed condition .P. fluorescens WCS417r-ISR hosting plants showed systemic expression of defense genes when compared to the control, and P. syringae infection led to identification of genes (mostly JA- and ET-regulated genes) with more enhanced expression than non-ISR expressing plants -(-)-2,3-butanediol were found to prime Arabidopsis plants against pathogen infections and herbivore attack  or by MAMPs from P. syringae, the progeny showed high levels of defense gene expression via the SA-dependent pathway and was resistant to P. syringae and Hyaloperonospora arabidopsidis. These progenies also had a stronger priming phenotype than the parents. Trans-generational priming is achieved through defense response memorization and propagation (in both meiosis and mitosis) by the parents  or DNA recombination caused by environmental stresses . This foathogens . In addise genes . In a st parents . HoweverFigure 3, priming can be divided in to three major events: (1) perception of the priming stimulus, (2) secondary stimulus, and (3) trans-generational priming. The early stages of priming involve signaling by phytohormones and other signaling molecules. Phytohormones are well-documented plant metabolites involved in different stages  of plant defense responses or plant priming  regulated pathway    . Epigeneechanism . The fewd plants . HoweverFigure 4). As stated, the rhizosphere can contain a spectrum of different microbial communities, constituting very complex chemical environments. Metabolomics, as a data-driven, hypothesis-generating scientific approach with the aim to detect and quantify 100s of compounds per analysis .Recent advances on both analytical instrumentation and – analysis with high selectivity, accuracy, and robustness, and combined with data processing software developments and availability of public databases, have facilitated this endeavor. Thus, these progressions have enabled researchers not only to study one aspect of a biological system, but also the interaction with the surroundings . Below wThe sample preparation method(s), to a large extent, determines the type of compounds to be detected. Sample preparation for any metabolomics study comprises several steps mostly dictated by the chosen analytical platform. The main steps include material harvesting at a specific time and quenching to minimize metabolic turnover rates. Next, metabolite extraction with organic solvents or solid phase extraction is performed, taking the matrix in which the metabolites occur into account. This is followed by pre-analytical sample preparation  .Gas chromatography, liquid chromatography (LC), and capillary electrophoreses (CE) coupled to MS have developed into the preferred bio-analytical platforms used in metabolomics . GC-MS i2) is used to obtain more structural information and this is referred to as tandem MSn experiments  or in-space (qTOF and QqQ)]. In-time refers to the ability to perform multiple stages of MS achieved by allowing ions from the ion source into the ion trap followed by fragmentation to generate diagnostic information. On the other hand, in-space refers to instruments with two mass analyzers separated by a collision cell which allows two MS stages (LC-MS column chemistry selection and retention mechanisms makes it the technique most used to complement GC-MS. Most LC-MS applications use reverse phase (RP) and normal phase (NP) stationary phases with eluates eluted with a mobile phase mixture  . Other ceriments . Tandem S stages .CE separates compounds based on charge and size, and offers high resolving power. CE-MS is mainly used for intermediate primary metabolic pathways  cycle, and pentose phosphate pathway) and is usually coupled to a TOF mass analyzer , 2016.In recent years, MS imaging (MSI) has been advanced and applied in different metabolic studies. MSI is a new imaging technique that provides the distribution of compounds on the surface . Here, a two or three dimensional image is created by taking measurements across an individual pixel basis . Comparem/z ion is defined by the same variables that only correspond to it. Recently, Metabolomics generates large amounts of complex datasets that require both storage and data processing tools (reduction of data complexity) . This caplantmetabolomics.org) are also emerging  gene function prediction, and (2) systemic interaction characterization of biological systems . ‘-OmicsRecent studies have highlighted the complexity of the rhizosphere as an interlinked ecosystem consisting of different microorganisms that can enhance plant growth through different mechanisms. Chemical communication plays an important role in establishing a mutual relationship between plant roots and PGPR. In addition, both plants and PGPR determine the community of PGPR found in the rhizosphere. In attempts to unravel rhizosphere signalomics, several metabolites, both primary and secondary, have been identified to be the major messengers between plant roots and PGPR. Here, root exudates and PGPR metabolites (non-volatile and volatile) play major roles in establishing a mutual relationship. PGPR are also capable of interfering with phytohormone-linked signaling to inhibit or limit defense responses. PGPR do not only enhance plant growth, but also prime plants against infection by different phytopathogens. ISR/PGPR priming is a result of the complex rhizosphere interaction between plant roots and PGPR, leading to pre-conditioning of plants for an enhanced defense response against secondary stimuli. Most studies done on ISR/PGPR priming are gene- or transcription-based with very few on metabolomics. However, the limited studies available suggest that the early stages involve biosynthesis of signaling molecules followed by modulation of both primary - and secondary metabolism. When secondary stimuli are subsequently perceived, triggered events occur in an enhanced manner. These different physiological states  are reflected in changes to the metabolomes and can be investigated through targeted and untargeted metabolomics approaches. However, such studies generally focus on single organisms rather than studying the more complex system consisting of plant, rhizomicrobes and pathogen. Through increased technological advances, both biologically and chemically, we are now better able to study in detail the chemical changes which are associated with microbe-plant interactions and the biochemical mechanisms behind them. Metametabolomics, targeted at the phytobiome would therefore be a future approach aimed at unraveling the complexity of chemical communication in the rhizosphere.Conceived and designed the research: MM and ID. Contributed to the paper and revised it critically for important intellectual content: MM, LP, NM, NL, and ID. All authors gave approval to the final version.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.


Patients with schizophrenia have an increased prevalence of metabolic disturbances compared with the general population. However, the mechanisms underlying the metabolic side effects of antipsychotics are unknown. The aim of the present study was to compare the levels of high-density lipoprotein (HDL)-cholesterol in Japanese schizophrenia patients medicated with olanzapine, risperidone, or aripiprazole monotherapy.This study was a post-hoc analysis of a nationwide survey, which included 433 Japanese outpatients with schizophrenia and 674 inpatients. A brief questionnaire was compiled that covered demographic data, systolic blood pressure, diastolic blood pressure, and HDL-cholesterol after reviewing the relevant literature and guidelines. To compare demographic and clinical characteristics, analysis of variance was performed for continuous variables and the chi-square test was performed for categorical variables. For comparisons of HDL-cholesterol levels among the three antipsychotic groups, analysis of covariance was carried out with age, diastolic blood pressure, chlorpromazine-equivalent dosage, and waist circumference as confounding variables after stratification by body mass index (BMI) for each outpatient group and inpatient group.2. HDL-cholesterol levels when stratified by BMI differed significantly (p = 0.019) between the three antipsychotic groups after age, diastolic blood pressure, chlorpromazine-equivalent dosage, and waist circumference in inpatients. A significant difference in HDL-cholesterol levels was only found in the overweight inpatient group, and no significant differences in HDL-cholesterol levels were found among the three antipsychotics for outpatients of all BMI stratifications or inpatients that were underweight or of normal weight. For post-hoc analysis of HDL-cholesterol levels in overweight inpatients, HDL-cholesterol was significantly lower in the olanzapine group than in the aripiprazole group (p = 0.023).The mean age was 57.9 ± 14.0 years and the mean BMI was 23.4 ± 4.5 kg/mThis study reveals a difference in HDL-cholesterol levels in overweight Japanese inpatients with schizophrenia resulting from the use of different antipsychotics. In the post-hoc analysis of HDL-cholesterol levels in overweight inpatients, HDL-cholesterol was significantly lower in the olanzapine group than in the aripiprazole group. Further studies incorporating more detailed evaluations, including diet and physical activity, are needed to clarify the differences in HDL-cholesterol according to antipsychotic use. Patients with schizophrenia suffer from increased morbidity and mortality compared with the general population and have a life expectancy that is approximately 20% shorter . PatientMetabolic disorders associated with atypical antipsychotic drugs include abnormalities of glucose metabolism such as insulin resistance, hyperglycemia, dyslipidemia and weight gain –11. In aMany confounding factors affect HDL-cholesterol levels. It is well known that HDL-cholesterol levels are decreased in overweight subjects , 15, andThe prevalence of metabolic syndrome in schizophrenia patients treated with antipsychotics is higher than in the general population. In a previous nationwide survey on the prevalence of metabolic syndrome in the Japanese population, the prevalence in outpatients was approximately 3-fold higher than that in inpatients . Japan hThe aim of the present study was to compare HDL-cholesterol levels between Japanese schizophrenia patients medicated with olanzapine, risperidone, or aripiprazole monotherapy as a post-hoc analysis of a previous nationwide survey.This study was a post-hoc analysis of a previous survey . Of the The number of Japanese patients with schizophrenia was 795,000, and the majority of these patients were treated in hospitals in the Japan Psychiatric Hospitals Association in an investigation conducted by the Ministry of Health, Labour and Welfare in 2008. For the aim of assisting patients with schizophrenia, a joint project with the cooperation of the Japanese Society of Clinical Neuropsychopharmacology and the Japan Psychiatric Hospitals Association was started in Japan in 2012.A questionnaire survey was conducted between January 2012 and July 2014. Responses were obtained from 7655 outpatients and 15,461 inpatients in 520 facilities for outpatients and 247 facilities for inpatients belonging to the Japan Psychiatric Hospitals Association. We excluded patients aged under 20 years; patients whose sex, BMI, and HDL-cholesterol data were not recorded; and patients medicated with polypharmacy of antipsychotics or monotherapy with drugs other than olanzapine, risperidone, or aripiprazole. The final study population comprised 1107 individuals.2). Blood pressure was measured twice with patients in a seated position after at least 5 min of rest, using a standard mercury sphygmomanometer. HDL-cholesterol was measured by standard analytical techniques.A brief questionnaire was compiled to cover demographic data (age and sex), systolic blood pressure, diastolic blood pressure, and HDL-cholesterol after reviewing the relevant literature and guidelines. Body weight, height, and waist circumference were measured, and BMI was calculated by weight (kg)/height squared  was used for statistical analyses. For comparisons of HDL-cholesterol levels among the three antipsychotic groups, analysis of covariance was carried out with age, diastolic blood pressure, chlorpromazine-equivalent dosage, and waist circumference as confounding variables after stratification by BMI  for each outpatient group and inpatient group. Post-hoc analyses were performed using the Bonferroni method.Demographic and clinical variables are presented as the mean ± standard deviation (SD) or proportion. To compare demographic and clinical characteristics between the three antipsychotic groups, analysis of variance was performed for continuous variables and the chi-square test was performed for categorical variables. The threshold for significance was set at 2. Table n = 1107). No significant intergroup differences were observed for sex, BMI, waist circumference, systolic blood pressure, or HDL-cholesterol. Significant differences were observed for age (p < 0.001), diastolic blood pressure (p = 0.025), and chlorpromazine-equivalent dosage of current atypical antipsychotics (p < 0.001). The HDL-cholesterol levels for overweight inpatients differed significantly among the three antipsychotic groups (p = 0.019) after adjustment for age, diastolic blood pressure, chlorpromazine-equivalent dosage, and waist circumference. For post-hoc analysis of HDL-cholesterol levels in overweight inpatients among the three antipsychotic groups, HDL-cholesterol was significantly lower in the olanzapine group than in the aripiprazole group (p = 0.023), and HDL-cholesterol levels were similar between the olanzapine and risperidone groups (p = 0.160). HDL-cholesterol levels in underweight and normal weight patients did not differ significantly -cholesterol as well as decreased HDL-cholesterol , 25. In 2 and olanzapine-treated patients had significantly lower HDL-cholesterol levels than risperidone-treated patients [In a randomized comparative study of aripiprazole and olanzapine, no group differences were observed in the proportions of patients with potentially clinically significant fasting HDL-cholesterol levels, because the weight gain at the study end-point was significantly greater with olanzapine than with aripiprazole . The dispatients . BecauseIn a study on the acute metabolic effects of olanzapine in healthy volunteers, there was a significant decrease in HDL-cholesterol, in the absence of changes in total cholesterol and LDL-cholesterol . The decIn the present study, differences in HDL-cholesterol among patients treated with antipsychotics were not detected in outpatients. Although no direct comparisons of inpatients with outpatients were made in this study, a previous study reported that hypocholesterolemia was higher in inpatients than in outpatients or the general population , 34. TheIn the study of BMI status of hospitalized Japanese schizophrenia patients, underweight as well as obesity was a characteristic in schizophrenia inpatients compared with the general population . RegardiFor overall patients, the olanzapine group had a statistically significant higher chlorpromazine-equivalent dosage compared with the two other groups in this study. The HDL-cholesterol levels for overweight inpatients differed significantly among the three antipsychotic groups after adjustment for chlorpromazine-equivalent dosage. Regarding the risk of metabolic syndrome in psychiatry inpatients, metabolic syndrome was associated with chlorpromazine-equivalent total daily doses, and specifically with clozapine, olanzapine, and quetiapine . There wThis study reveals a difference in HDL-cholesterol in overweight Japanese inpatients with schizophrenia resulting from the use of different antipsychotics. Further studies incorporating more detailed evaluations including diet and physical activity, are needed to clarify the differences in HDL-cholesterol according to antipsychotic use.The present study had several limitations. First, the cross-sectional and antipsychotic treatments were not performed randomly, and thus bias in the antipsychotic prescriptions was not controlled. Second, the present analysis was a post-hoc analysis of a study that was not designed or powered to demonstrate differences between treatments, and thus the possibility of type II errors may remain. Third, comparisons with unmedicated schizophrenia patients or healthy controls could not be performed in this study. Fourth, we did not assess psychiatric symptoms or severity using the Brief Psychiatric Rating Scale, Positive and Negative Symptom Scale or Clinical Global Impressions in this study. Psychiatric symptoms might be related to body weight, physical activity, or antipsychotic drugs, so further study including the assessment of symptoms and severity is required.This post-hoc study of a large questionnaire survey showed differences in HDL-cholesterol levels between different antipsychotic monotherapies in Japanese inpatients with schizophrenia. HDL-cholesterol was significantly lower in the olanzapine group than in the aripiprazole group in overweight inpatients. The difference was only revealed in overweight inpatients, and further study is needed to evaluate factors such as diet and physical activity to clarify the differences in HDL-cholesterol levels related to antipsychotic use.


Background: People living with Human Immunodeficiency Virus (HIV) often suffer from alcohol-use disorders resulting in their poor health and treatment outcomes. Little is known about the association of harmful alcohol drinking with their adherence to anti-retroviral therapy (ART) and health-related quality of life (QOL) in low-resource settings.Objective: This study aimed to investigate associations between harmful alcohol drinking, adherence to ART and health-related QOL in HIV-positive people, stratified by gender, in Nepal.Methods: We conducted a cross-sectional study of 682 HIV-positive people on ART to measure their self-reported harmful alcohol drinking and non-adherence to ART in the previous month of data collection. We also measured health-related QOL using a WHOQOL-HIV BREF scale. The association between harmful alcohol drinking and non-adherence to ART was examined using multiple logistic regressions. Additionally, multiple linear regressions examined association between harmful alcohol drinking and QOL.Results: Harmful alcohol drinking was associated with non-adherence to ART among men  and women . Men were more likely to have lower score for the psychological  and level of independence  domains when they had harmful alcohol drinking. Moreover, women were more likely to have lower scores for the physical , social relations , environmental , and spiritual  domains of QOL when they had harmful alcohol drinking.Conclusions: Harmful alcohol drinking had a negative association with ART adherence and QOL in both HIV-positive men and women in Nepal. Screening for alcohol-use disorders and community-based counseling services should be provided while delivering ART services to improve treatment adherence and QOL. Access to anti-retroviral therapy (ART) improved the life expectancies of people living with Human Immunodeficiency Virus (HIV) globally ,2. HowevHarmful alcohol drinking among HIV-positive people has been associated with non-adherence to ART in both high-income countries (HICs) and in low- and middle-income countries (LMICs) –9. In a People living with HIV who use alcohol tend to have a poor health-related QOL. Research in the United States shows that alcohol-use disorders can impact negatively on physical functioning and on the emotional well-being of HIV-positive people, which can then decrease mental health-related QOL . In thatGender difference also has implications in relation to the association between alcohol use and health outcomes. In the United States, men having sex with men (MSM) had a higher prevalence of HIV because of unprotected sexual practices resulting from harmful alcohol drinking behavior . Women iHIV-positive people who use alcohol, poorly engage in HIV services and this affects their continuum of care. A systematic review found that alcohol users were more likely to have missed at least one or more cascades of continuum of care such as attending treatment services, ART compliance, routine investigation of viral loads, and CD4 count . AdditioHIV-positive people had non-adherence to ART when they consumed alcohol in Nepal ,23. AlcoThis study was conducted in Nepal, a low-income country situated in South Asia, which harbors a population of 28 million. About 40,000 HIV-positive people are living in the country. Among them, approximately 12,000 were on ART in 2015 .The design was cross-sectional. The study districts were selected by convenience sampling method and participants were conveniently recruited from the various non-governmental organizations (NGOs) involved in providing HIV services. The participants who took ART for at least one year at the time of data collection and those who were diagnosed as HIV-positive within five years were included in the study sample.We calculated the sample size using G*Power statistical software. First, we took the reference prevalence of non-adherence to ART as 21% among HIV-positive people who received community-based psychosocial support . Second,Participants were asked about their regular drinking behavior. The extent of harmful drinking was measured using the Alcohol Use Disorders Identification Test (AUDIT), which is a 10-item scale designed to measure alcohol use covering amount, frequency, and hazardous drinking . The avaThe questionnaires developed by the AIDS Clinical Trial Group (ACTG) were applied to assess the missed pills. The data collection considered participants who missed at least one dose in the past month as being non-adherent to ART ,31.Participants’ health-related QOL was measured using the WHO Quality of Life-HIV BREF (WHOQOL-HIV BREF) scale . The scaParticipants were interviewed and asked for self-reported information regarding age, gender, marital status education, employment status, and physical symptoms. Marital status was categorized as married and unmarried/widow/single. Education level was grouped in two categories: illiterate and primary level education; or more. For employment status, we categorized the participants as employed/self-employed and unemployed. Further participants who reported opportunistic infections were categorized as having physical symptoms and we considered those who did not report any symptoms related to opportunistic infection as having no physical symptoms.The records about clinical staging were retrieved from the ART centers of the selected districts. The first and second clinical stages were categorized as early stage, and the third and fourth stages were categorized as advanced .A set of questionnaires was first translated from English to Nepali and then back translated to English by two independent translators, to ensure consistency in meaning and interpretation. Finally, some modifications were made before finalizing the questionnaires for pre-testing. Pre-testing of questionnaires was done among 48 participants in Kathmandu. Necessary modifications were made in the questionnaire after the pre-testing. We approached 720 HIV-positive people on ART and 682 participants (94.7%) responded to the questions. The pre-tested participants were not included in the study. The baseline data collection was conducted in February and March 2015.Data were analyzed descriptively using chi-squared and Fisher’s exact test for categorical variables and a t-test for age. Multiple logistic regressions examined the association between harmful alcohol drinking and non-adherence to ART. Additionally, multiple linear regressions examined the association between harmful alcohol drinking and the quality of life (QOL) domains. In each model, important covariates such as age, education, marital status, occupation, physical symptoms, and HIV-clinical staging were adjusted, as studies have indicated that these factors can influence ART adherence ,31. All The study was approved by the Research Ethics Committee of the Graduate School of Medicine, the University of Tokyo and the Nepal Health Research Council. Prior to data collection, permission was obtained from the selected agencies providing community home-based care and support services for HIV-positive people in Nepal. Participants were ensured about the confidentially of information and their voluntary participation. Moreover, written informed consent was obtained from the participants on a designated form. The participants were also asked for their thumbprint if they were not able to write their name. During the interview, if participants were found to have a severe alcohol-use disorder, they were referred to non-governmental organizations and nearby hospitals.Of 682 participants, 354 were men and 328 were women. About 25.1% of the men and 29.3% of the women were non-adherent to ART. ART adherent and non-adherent participants were not significantly differences in relation to their age, education, marital status, employment, HIV-clinical staging, or physical symptoms. Among them, 35.0% of the men and 15.5% of the women had harmful alcohol drinking. Compared with adherent men, more non-adherent men had harmful alcohol drinking . A significantly higher proportion of non-adherent women had harmful alcohol drinking compared to those who were ART adherent  see .Table 1.Men were more likely to be non-adherent to ART when they had harmful alcohol drinking . Also, harmful alcohol drinking was positively associated with non-adherence to ART among women  see .Table 2.Compared to those who did not have harmful alcohol drinking, men had lower scores for psychological , level of independence , environmental , and spiritual  domains when they had harmful alcohol drinking.Similarly, women who had harmful alcohol drinking had lower scores of physical  and spiritual  domains compared to those who did not have harmful alcohol drinking see .Table 3.After controlling age, marital status, education level, employment status, physical symptoms, and HIV-clinical staging, harmful alcohol drinking was negatively associated with QOL domains. Among men, harmful alcohol drinking was associated with the psychological , level of independence , environmental , and spiritual  domains. Additionally, women were more likely to have lower scores for physical , social relations , environmental , and spiritual  domains when they had harmful alcohol drinking see  and 5.TaIn this study, HIV-positive men and women in Nepal were more likely to be non-adherent to ART when they had harmful alcohol drinking. Additionally, harmful alcohol drinking was negatively associated with the psychological, level of independence, environmental, and spiritual domains of QOL among men. Women were more likely to have poor QOL for physical, social relations, environmental, and spiritual domains when they had harmful alcohol drinking.HIV-positive men and women who had harmful alcohol drinking were more likely to be non-adherent to ART. With regard to gender differences, both men and women had non-adherence. The strength of the association in women was slightly higher compared to men. In the Nepali context, alcohol drinking behavior might have impaired women to access to HIV services compared to men. It is possible that both men and women might not have sought family support and might have experienced poor coping skills because they suffered from other mental health and substance-use disorders such as use of heroin and cocaine.Higher frequency of alcohol consumption induces a stronger maladaptive coping strategy among HIV-positive people because the alcohol may be associated with other behavioral disorders that lead to non-adherence to ART . AlcoholHarmful alcohol drinking had negative effects on the QOL domains of both HIV-positive men and women or simply HIV-positive people. They might have endured poor self-efficacy and not sought appropriate care for opportunistic infections and physical symptoms . AlcoholIn this study, we observed gender differences in the QOL among men and women. Women were more likely to have a poor QOL in respect to social relations and spiritual domains. The lower level of support in women might have had a negative role in those who sought support from their spouse and family . Men werThis study has some limitations. Social desirability bias may have affected our results as participants self-reported their status regarding missing pills and alcohol use. To minimize this as much as possible the interviews were conducted in private places. Furthermore, we counted consumed pills out of the total prescribed for the previous month. The study districts were selected conveniently to reach the participants from NGOs, and therefore selection bias may limit generalizability of the findings. However, the results can be applied in the settings where participants have similar characteristics. The results might have also been biased by other substance-use disorders and mental health disorders. These factors impact negatively on engagement in HIV services. To minimize this as much as possible we recruited participants from similar settings.Despite these limitations, this study is novel being the first to examine these issues separately in HIV-positive men and women in Nepal. This study also adds new evidence about the negative association between harmful alcohol drinking, ART adherence, and QOL in both men and women.Harmful alcohol drinking was negatively associated with ART adherence and QOL of HIV-positive people in Nepal. When designing services for ART counseling, alcohol-use disorders should be integrated along with psychosocial counseling. Health services providers should pay particular attention to address alcohol-use disorders while providing screening and treatment for HIV-related consequences. Frontline health workers should be provided with training material that are community-based and tailor made so that they can screen for and treat these disorders in their work settings. Additionally, support mechanisms should be established at family and community levels to address alcohol-use disorders, improve ART adherence and enhance the QOL for HIV-positive people. More studies are warranted to investigate causal relationships between harmful alcohol drinking and ART adherence taking into account factors such as depression, stress, and substance-use disorders.


Tuberculosis (TB) case notification rates are usually higher in men than in women, but notification data are insufficient to measure sex differences in disease burden. This review set out to systematically investigate whether sex ratios in case notifications reflect differences in disease prevalence and to identify gaps in access to and/or utilisation of diagnostic services.In accordance with the published protocol (CRD42015022163), TB prevalence surveys in nationally representative and sub-national adult populations (age ≥ 15 y) in low- and middle-income countries published between 1 January 1993 and 15 March 2016 were identified through searches of PubMed, Embase, Global Health, and the Cochrane Database of Systematic Reviews; review of abstracts; and correspondence with the World Health Organization. Random-effects meta-analyses examined male-to-female (M:F) ratios in TB prevalence and prevalence-to-notification (P:N) ratios for smear-positive TB. Meta-regression was done to identify factors associated with higher M:F ratios in prevalence and higher P:N ratios. Eighty-three publications describing 88 surveys with over 3.1 million participants in 28 countries were identified . Fifty-six surveys reported in 53 publications were included in quantitative analyses. Overall random-effects weighted M:F prevalence ratios were 2.21  for bacteriologically positive TB and 2.51  for smear-positive TB. M:F prevalence ratios were highest in South-East Asia and in surveys that did not require self-report of signs/symptoms in initial screening procedures. The summary random-effects weighted M:F ratio for P:N ratios was 1.55 . We intended to stratify the analyses by age, HIV status, and rural or urban setting; however, few studies reported such data.TB prevalence is significantly higher among men than women in low- and middle-income countries, with strong evidence that men are disadvantaged in seeking and/or accessing TB care in many settings. Global strategies and national TB programmes should recognise men as an underserved high-risk group and improve men’s access to diagnostic and screening services to reduce the overall burden of TB more effectively and ensure gender equity in TB care. In this systematic review and meta-analysis, Katherine Horton and colleagues examine the differences in tuberculosis burden and notifications between men and women living in low- and middle-income countries. Global health initiatives have tended to treat “gender” issues in health as being synonymous with women’s health. However, for infectious diseases, policy and practice need to be guided by epidemiological data and consideration of transmission dynamics.Many more men than women are diagnosed with, and die from, tuberculosis (TB) globally.Data from population-level surveys for undiagnosed TB, carried out in a number of countries during the last two decades, can be combined with data on diagnosed (notified) cases to provide more complete insight into the magnitude and nature of sex differences in TB.Surveys conducted to identify adult cases of TB in communities in low- and middle-income countries between 1993 and 2016 were analysed by sex.TB prevalence among men was over twice as high as among women and was substantially higher even in settings with high HIV prevalence.Case notification rates were also higher for men, and the ratio of prevalent-to-notified cases of TB—an indication of how long patients take to be diagnosed, on average—was 1.5 times higher among men than women, suggesting that men are less likely than women to achieve a timely diagnosis.Given that undiagnosed TB is the key driver for transmission in communities, our data show that greater effort and investment are needed to improve awareness of TB in men as an individual and public health issue.Policies on gender and TB should place greater emphasis on the high burden of disease in men and the need to invest in male-friendly diagnostic and screening services, with the aim of reducing undiagnosed TB. Over the past twenty years, tuberculosis (TB) case notifications among men have exceeded those among women in most settings . In 2014Prevalence surveys offer a robust measure of disease burden in the community, reducing or eliminating the care-seeking biases that affect case notifications: a higher proportion of men in case notifications could reflect either higher incidence of TB disease or more complete registration for treatment by men. Prevalence surveys predominantly identify infectious TB patients with previously undiagnosed TB disease who have, therefore, not contributed to routine notification data before participation in the survey. As such, comparison of the characteristics of diagnosed TB patients (notification data) with those of undiagnosed TB patients  provides a unique insight into diagnosis and treatment access barriers. For example, finding a similar male predominance in undiagnosed TB  patients as in notified TB cases would support the hypothesis that men genuinely have a higher burden of TB disease, while finding a greater male predominance in undiagnosed TB patients than in notified TB cases would suggest male-specific access barriers or male sex being a risk factor for TB disease.A previous analysis in 2000 found that male TB prevalence exceeded female TB prevalence in 27 (93%) of 29 prevalence surveys conducted in 14 countries between 1953 and 1997 [Despite these findings, men are often overlooked in discussions of gender and TB. While global TB reports and meetings on gender acknowledge the fact that the majority of TB cases and TB-associated deaths occur among men, greater focus is usually placed on women. More broadly in global health discussions, there is a tendency to use the word “gender” when really “women” is meant, as exemplified by the Millennium Development Goals  and SustThe World Health Organization’s End TB Strategy emphasises the importance of equity in access to diagnosis and treatment ; men shoThis review set out to systematically investigate sex differences in the prevalence of bacteriologically positive TB and smear-positive TB in adult participants in cross-sectional surveys conducted in low- and middle-income countries to determine whether sex ratios in adult case notifications reflect population sex differences in disease and to compare prevalence-to-notification (P:N) ratios for men and women. The current study adds to previous analysis  by incluGlobal Tuberculosis Report 2015 [In accordance with the published protocol , studiesTwo authors (K. C. H. and P. M.) independently reviewed titles and abstracts in parallel to identify relevant studies for full-text review. A third author (E. L. C.) resolved any discrepancies. The same authors reviewed full texts to determine whether studies met inclusion criteria and then extracted data on study methodology and TB prevalence in parallel using piloted electronic forms.Study authors were contacted for additional information if studies did not report the number of participants and the number of bacteriologically positive and/or smear-positive TB cases by sex for adult participants. Authors were also contacted if sex-specific prevalence data were not available by age group.Mycobacterium tuberculosis infection but not TB disease were excluded. Individuals under 15 y of age were excluded since diagnosis of childhood TB is more complicated than diagnosis of adult disease, especially within the context of community-based surveys [The review included cross-sectional prevalence surveys conducted in low- and middle-income countries . Studies surveys . StudiesThe risk of bias in included studies was assessed in parallel by K. C. H. and P. M. Each study was ranked on eight criteria from a tool developed to assess the risk of bias in prevalence surveys . These cStudy participants were defined as individuals who were interviewed and/or underwent initial screening procedures, according to study-specific procedures. Participation was defined as the number of participants divided by the number of individuals who were eligible or invited to participate. High relative male participation was defined as a M:F ratio in participation ≥ 0.90.Case definitions for TB were based on internationally recognised terminology, where available, and study-specific definitions otherwise. Bacteriologically positive TB was defined as positive smear microscopy, culture, or WHO-approved rapid diagnostic results (such as from Xpert MTB/RIF) .Sex-specific prevalence of bacteriologically and smear-positive TB was defined as the number of individuals with bacteriologically or smear-positive TB divided by the number of study participants, by sex. Reported prevalence was used to estimate the number of cases or the number of participants where one of these values was missing. No adjustments were made for nonparticipation or nonsampling.Sex-specific P:N ratios were calculated as the ratio of smear-positive TB prevalence per 100,000 individuals to smear-positive TB case notifications per 100,000 individuals among adults ,19. WHO National estimates of TB and HIV burden were matched to each prevalence survey by country and year. For surveys that took place over more than one calendar year, estimates were averaged over all survey years (excluding years with no reported data). High TB prevalence was defined using the median value for included studies, which was an estimated national TB prevalence ≥ 300 per 100,000 individuals . High HIPrevalence of bacteriologically positive TB and smear-positive TB was calculated for included studies by sex. Prevalence of bacteriologically positive TB by sex and age was also calculated, where possible. Sub-group prevalence was estimated for sub-groups based on survey characteristics including WHO geographical region, survey setting , national estimates of TB and HIV burden , study quality, initial screening procedures, case definitions, and relative male participation. Clopper-Pearson confidence intervals  and M:F I2 statistic [Heterogeneity was assessed using the tatistic . Due to Meta-regression was performed for M:F ratios in prevalence and M:F ratios in P:N ratios to examine associations with the survey characteristics mentioned above, plus the starting year of each survey. Univariate meta-regression of M:F ratios in prevalence was conducted separately for bacteriologically positive TB and smear-positive TB. If either univariate meta-regression suggested evidence of an association with a particular characteristic, that characteristic was included as a variable in the multivariate meta-regression models for both bacteriologically positive and smear-positive TB. Similarly, multivariate meta-regression of M:F ratios in P:N ratios was based on evidence of associations in univariate analysis.All analyses were performed using R version 3.2.2  S1 Data.Of 7,502 potentially relevant English-language studies screened by title and abstract, 148 were reviewed in full; of these, 65 were excluded after full-text review  and 83 wThe risk of bias assessment identified 33 (43%) surveys with low risk of bias, 32 (42%) with moderate risk of bias, and 12 (16%) with high risk of bias . Eleven Female participation equalled or exceeded male participation in all of the 28 surveys for which participation was reported by sex . Of 687,The prevalence of bacteriologically positive TB was reported by sex in 56 surveys with 2.2 million participants in 24 countries ,110–112.p < 0.001; for women, 735, 95% CI 448–1202, versus 157, 95% CI 110–223, p < 0.001). This same relationship  was also apparent when HIV data from diagnosed TB patients, rather than the general population, were used   and in settings with high HIV prevalence in diagnosed TB patients for women  but not for men   . Prevale= 0.060) .The overall random-effects weighted M:F prevalence ratio was 2.21 for bacteriologically positive TB  and 2.51 for smear-positive TB . Random-effects weighted M:F prevalence ratios for bacteriologically positive TB and smear-positive TB were significantly greater than one in all regions except the Region of the Americas, where analyses included only two small sub-national surveys .Among countries with multiple surveys, an excess of male TB cases was observed in all studies in eight (73%) of 11 countries. Exceptions with inconsistent results were Ethiopia, South Africa, and Viet Nam, although overall random-effects weighted M:F prevalence ratios exceeded one for each of these countries.In univariate meta-regression of M:F ratios in bacteriologically positive TB , there wM:F prevalence ratios were also higher in the South-East Asia Region than in the African Region in univariate meta-regression of smear-positive TB . In this analysis there was also evidence that M:F prevalence ratios were lower in surveys that required individuals to report signs or symptoms of TB during initial screening procedures  compared to surveys within which initial screening procedures included criteria such as chest X-ray, self-reported history of TB, or self-reported contact with a TB case, instead of or in addition to self-reported signs or symptoms.In univariate meta-regression models for M:F ratios in bacteriologically positive TB and M:F ratios in smear-positive TB, none of the following survey characteristics were associated with differences in M:F ratios in TB prevalence: survey setting , survey starting year, TB prevalence, risk of bias, case definitions, or relative sex ratios in participation.In multivariate meta-regression of M:F ratios in bacteriologically positive TB, there was evidence that M:F ratios remained higher in the South-East Asia Region than in the African Region after adjusting for HIV prevalence and initial screening procedures, although the relative M:F ratio between these two regions was slightly lower than in univariate analysis .There was evidence in the multivariate meta-regression of M:F ratios in smear-positive TB that M:F ratios were 2.21 times higher in the South-East Asia Region than in the African region . There was also evidence in the multivariate meta-regression that M:F ratios in surveys that required individuals to self-report signs or symptoms of TB in initial screening procedures were lower than those in surveys with broader initial screening procedures .Data on the prevalence of bacteriologically positive TB by sex and age were available for 19 surveys in 13 countries ,101,107.P:N ratios for smear-positive TB exceeded one for both men and women in 25 (74%) of 34 surveys in 20 countries with available data . The medThere was no evidence in univariate meta-regression that any of the study or setting characteristics examined were associated with M:F ratios in P:N ratios . Due to Meta-analysis of 56 TB prevalence surveys including 2.2 million participants in 28 countries provides strong evidence that TB prevalence is higher among men than women, with a higher M:F ratio than that reported for case notification data. The number of prevalent cases per notified case of smear-positive TB was also higher among men than women, adding evidence that men may be less likely than women to seek or access care in many settings. Further evidence of men’s barriers to seeking or accessing care is provided by results showing that men were less likely than women to participate in prevalence surveys and that relatively fewer prevalent cases were found among men in surveys that required participants to self-report signs or symptoms in initial screening procedures.The excess male prevalence observed in surveys conducted between 1953 and 1997 , this stComparisons of sex ratios in TB prevalence and notification highlight sex differences in time to diagnosis and imply that in many settings women are more likely than men to have a timely TB diagnosis. While these results could be attributed to men seeking care in private facilities and therefore being less likely to be included in case notification numbers, this explanation would require that the proportion of men who seek care in the public sector be only two-thirds the proportion of women who seek care in that sector. Instead, there is wider evidence that men are less well-served than women by health services ,119. WitLower prevalence survey participation among men and evidence of lower M:F prevalence ratios in studies that require individuals to self-report signs or symptoms of TB in initial screening procedures imply that symptom screening in community-based active case finding may be a less effective tool for identifying TB disease in men than women. It is not known whether this is due to men refusing to report symptoms or whether the sub-clinical phase of disease may be longer for men . FurtherFindings from this review suggest that case detection efforts, whilst not ignoring women, should be greatly strengthened for men. This will require a detailed understanding of the barriers that men face in accessing care. Previous studies have highlighted factors such as loss of income and financial barriers, as well as stigma, that affect men’s healthcare decisions ,126. CarThis review summarises evidence on sex ratios in TB prevalence from a large number of prevalence surveys across geographic regions, an approach which introduces a number of potential sources of bias. Surveys varied greatly in their methodology, particularly in screening criteria and case definitions, and levels of participation varied within and between studies. However, over 84% of the surveys in the analyses had low to moderate risk of bias.Prevalence as a measure of disease burden has limitations as it provides an estimate at a single point in time and cannot distinguish between disease as a result of recent infection and disease from reactivation, limiting understanding of current transmission. Comparing the rate of prevalent cases to notified cases is a crude measurement, especially comparing all surveys to national case notification rates, regardless of study setting. Stratifying by age and rural or urban setting would improve P:N ratios; however, data on these characteristics were not available at the time of analysis. Prevalence data by sex and HIV status were too infrequently available to be reported here. To our knowledge, no surveys that conducted drug susceptibility testing reported the results of those analyses by sex, so it is not possible to comment on whether the sex differences reported here are also relevant to drug-resistant TB. Given the significant sex differences reported in prevalence, future surveys should analyse and report all results by sex to facilitate greater understanding of the relationship between gender and TB.Men have a higher prevalence of TB and, in many settings, remain infectious in the community for a longer period of time than women. Men are therefore likely to generate a greater number of secondary infections than women, and social mixing patterns have suggested that, as a result, men are responsible for the majority of infections in men, women, and children . AddressS1 Checklist(PDF)Click here for additional data file.S2 Checklist(PDF)Click here for additional data file.S1 Analysis(HTML)Click here for additional data file.S1 Data(TXT)Click here for additional data file.S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.


Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at:  The fundamental unit of chromatins is a nucleosome, which affects transcription; the packing of DNA into nucleosomes inhibits DNA availability to transcriptional regulators [Eukaryotic transcription is not only regulated by interactions between transcriptional regulators and gulators . Nucleosgulators –5. Sincegulators . Therefoet al. proposed a method based on support vector machine (SVM), using nucleotide composition as a feature vector [et al. and Kabir et al. also proposed SVM-based predictors, using pseudo-dinucleotide and pseudo-trinucleotide compositions, respectively [et al. proposed a predictor called iDHS-EL (identifying DHSs by fusing three different modes of pseudo-nucleotide composition into an ensemble learning framework), which combined three independent random forest (RF)-based predictors, where each one uses different modes of pseudo-nucleotide composition as input features [DHSs can be identified through southern blotting technique and chromatin immunoprecipitation, followed by microarray hybridization (ChIP-chip) , 8. Howee vector . Feng etectively , 11. Allfeatures . iDHS-ELi) The feature space used by the existing methods to construct models is incomplete and not comprehensive. Hence, other potentially useful features remain to be characterized. (ii) Biologically significant features are intrinsically heterogeneous and multi-dimensional; however, the existing methods do not employ feature selection techniques to quantify the importance and contribution of features used for the model, leading to only a partial understanding of the sequence-DHS relationships. Due to these deficiencies, other methods are needed to accurately predict DHSs in uncharacterized DNA sequences.Although these bioinformatics tools showed encouraging results and stimulated research in this area, further studies are needed for the following reasons. , dinucleotide physicochemical properties (DPCP), and trinucleotide physicochemical properties (TPCP). In addition to DHSpred, we also developed prediction models using three other machine learning (ML)-based methods . Our results showed that the performance of DHSpred was superior to that of three ML-based models developed in this study and four state-of-the-art predictors.In this study, we developed an SVM-based prediction method for DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), in which the optimal features are selected using RF  using the benchmarking dataset. MNC analysis revealed that, on average, guanine (G) and cytosine (C) were dominant in DHSs, while adenine (A) and thymine (T) were dominant in non-DHSs  . Among them, the top five motifs from TNC , TeNC , and PNC  were from DHSs  Figure . This tr) Figure , when sos Figure , and 2D An SVM-based model was constructed using the optimal feature set, through two steps. In the first step, we employed the RF algorithm and evaluated the importance of 2228 features  for distinguishing DHSs from non-DHSs. Based on a threshold feature importance score (FIS) ≥ 0.0003, 1139 features were selected as optimal feature candidates Figure . The perGenerally, it might be possible for hybrid models  or individual composition-based models to perform better than models developed by rigorous feature selection protocols, such as the one described above. To investigate this possibility, we developed prediction models using individual composition or hybrid models, whose performances in terms of MCC, accuracy, sensitivity, and specificity are shown in Figure k-NN. A detailed description of the development of prediction models using these methods was provided in our recent studies [k-NN), irrespective of the features used. This result indicated that the SVM method was more suitable for predicting DHSs than other MLs  by ~2% and 1–2%, respectively.In the second step of the previous section, we used three different ML-based methods instead of SVM, including, RF, ET, and  studies . For eacs Figure . We thenk-NN) in terms of AUC.To provide an intuitive comparison among the four methods, we plotted the receiver operating characteristics (ROC) curve of these four methods Figure . Here, tIn order to test the quality of the performance of our SVM-based model (DHSpred), it was necessary to compare it to other state-of-the-art methods. Here, we compared it with four such methods , which were developed from the same benchmark dataset –12. The k-mer, DPCP, and TPCP, while most other methods use all available information. For instance, iDHS-EL considers all the features from DPCP, instead of merely the important motifs. Although the existing methods could achieve relatively high-level performance, further improvement in performance is limited when handling complicated data samples. Hence, incorporating important features from multiple complementary sources of information (as the DHSpred method does) could allow us to sufficiently capture the differences between true DHSs and non-DHSs, thus improving the predictive performance.The superior efficiency of DHSpred could be attributed to the fact that it selectively incorporates multiple aspects of important information (achieved through systematic feature selection) from www.thegleelab.org/DHSpred.html Users can paste or upload query DNA sequences in the FASTA format. After submitting the input DNA sequences, they can retrieve results in a separate interface. To maximize the convenience for users, step-by-step guidelines are provided in the Supplementary information. To ensure reproducibility of our findings, datasets used in this study can be downloaded from the DHSpred web server.As mentioned in previous publications , 24–26, DHSs are nucleosome-free regions associated with different genomic regulatory elements, including promoters, enhancers, silencers, insulators, and transcription factor binding sites –4, 34. Tk-mer, DPCP, and TPCP. Although k-mer and DPCP features have been used in earlier studies [In this study, we developed a novel ML approach, called DHSpred, for predicting DHSs in the human genome. DHSpred combines various informative features from multiple sources, including  studies , 10, 12, studies , 36–38.  studies . We applk-NN) by cross-validations on the same benchmark dataset. The superior performance of our method might be attributed to two important factors: (i) integration of previously reported features and inclusion of novel features that collectively make significant contributions to the performance; (ii) a two-step feature selection protocol to eliminate overlapping and redundant features. Furthermore, our approach is a general one, which is applicable to many other classification problems in structural bioinformatics. It can be readily extended for predicting DHSs in the plant genome.In this study, it was demonstrated that DHSpred outperformed state-of-the-art methods  –12 and tk-mers showed the best performance in distinguishing DHSs from non-DHSs, indicating a strong relationship between the optimal features and DHSs. Interestingly, all these features represent the local and global DNA sequence pattern, hence these properties might play a vital role in maintaining the DHS function. Although the current predictor is purely based on the primary sequences information, incorporating epigenetic information, including DNA methylation, and histone modifications will improve the performance of the predictor. Thus, we will also try to implement epigenetic information in our future work.The final identified optimal feature set through a rigorous feature selection protocol revealed that a major contribution from TPCP (~52%) and the remaining contribution (48%) from DPCP, and important motifs in A user-friendly web interface is also available for researchers to use our prediction method. Indeed, our method is only the second method that is publicly available with high accuracy. Compared to experimental approaches, bioinformatics tools such as DHSpred represent a powerful and cost-effective approach for genome-wide prediction of DHSs. Therefore, DHSpred might be useful for large-scale DHS prediction and facilitate hypothesis-driven experimental design.i) construct a valid benchmarking dataset to train and test the prediction model; (ii) formulate the biological sequence samples with an effective mathematical expression that can truly reflect their intrinsic correlation with the target to be predicted; (iii) introduce or develop a powerful algorithm (or engine) to operate the prediction; (iv) properly perform cross-validation tests to objectively evaluate the anticipated accuracy of the predictor; (v) establish a user-friendly web-server for the predictor that is accessible to the public. Below, we describe these steps one-by-one.According to the Chou's  five-steet al. (2005), which was specifically used for studying DHSs [i) This dataset is more reliable, as it was constructed rigorously based on experimental data. (ii) It is a non-redundant dataset and none of the sequences has high pairwise sequence identity (> 80%) with any other sequence. Hence, this dataset could stringently exclude homology sequences. (iii) Most importantly, it will facilitate fair comparison between our method and the existing methods that were developed using the same benchmarking dataset.In this study, we utilized the dataset constructed by Noble ing DHSs . We deciet al. [Usually, the benchmark dataset comprises a training dataset and a testing dataset. The former is for training a model, while the latter is used for testing one. As pointed out in a comprehensive review , there iet al.  (2005) cS+ contained 280 DHS sequences, the negative subset S– contained 737 non-DHS samples, and the symbol denotes union in the set theory. Thus, S contained 1017 samples, which can be downloaded from our webserver.where the positive subset k-NN) model to accurately map input features extracted from a nucleotide sequence to predict its class , which is considered a classification problem. We used nucleotide composition and di- and trinucleotide-physiochemical properties as input features. These features reflect the characteristics of a DNA sequence, from different perspectives, as defined below.The aim of this experiment was to train each ML-based  can be characterized by six quantities, which include three local translation parameters  and three local angular parameters  , 47, whij is one of 16 possible dinucleotides, Nres is the sequence length, and i is one of the six physicochemical properties.where Recently, the twelve physiochemical properties  parameters had compiled for DNA trinucleotides . The parj is one of 64 possible dinucleotides, Nres is the sequence length, and i is one of the 12 physicochemical properties.where k-mer, DPCP, and TPCP were considered for DHS prediction. Notably, TPCP has never been considered before, although k-mer, DNC, and DPCP are utilized in existing ML-based methods for DHS prediction [To the best of our knowledge, this is the first study in which ediction , 10, 12.The feature selection protocol is the same as the one used in our recent study . We usedC and g) were optimized using a grid-search approach to train the model, while the remaining subsets were merged as the test set to validate the built model. This procedure was repeated ten times, and each subset was used in the training and validated in the testing. This 10-fold cross-validation procedure was repeated five times, resulting in five similar/different ML parameters and performances . We considered the average performances and median ML parameters as the final stable values, and carried out performance evaluation.In the second step, we selected different sets of optimal feature candidates based on an FIS cut-off . The sets of features with FIS greater than the cut-off value were selected as the input features for the SVM classifier. For each feature set, we randomly divided our benchmark dataset into ten subsets (~10% of DHSs and non-DHSs in each subset) for each validation step. At each cross-validation step, nine subsets were then merged as the training dataset, in which ML parameters . Hence, a grid search within the following ranges: C from 2–15 to 210 and γ from 2–10 to 210 in log2 scale, was conducted to tune the SVM parameters (C and γ). The optimal values for C and γ parameters for the final selected model were found to be 80.256 and 2.692, respectively. Besides SVM, we also utilized RF and other ML methods (ET and k-NN). These methods were implemented according to the scikit-learn package [SVM is a well-known supervised-ML technique used for developing both classification and regression models based on statistical theory . A detai package .In statistical prediction, the following three cross-validation methods are often used to examine a predictor for its effectiveness in practical application: independent dataset test, subsampling test, and jackknife test. However, among these three methods, jackknife test is deemed as least arbitrary one which can always yield a unique result for a given benchmark dataset as elaborated in  and demoet al. [et al. [et al. derived a new set of equations for these metrics [To compare the prediction methods, we evaluated sensitivity (Sn), specificity (Sp), accuracy (ACC), the Matthews correlation coefficient (MCC), product of Sn and Sp (Pt), and property excess (Py) , 58. Amo [et al.  (2005).  metrics , 25, bas metrics . The new+N is the total number of the DHSs investigated, -+N is the number of DHSs incorrectly predicted as non-DHSs, -N is the total number of non-DHSs investigated, +-N and is the number of non-DHSs incorrectly predicted as DHSs. The above set of metrics is valid only for the single-label systems. For the multi-label systems, whose existence has become more frequent in system biology [where  biology  and syst biology –64, a co biology .An online prediction server was developed using hypertext markup language and Java script, with a Python script executing in the backend upon submission of DNA sequences in the FASTA format. Users can submit single or multiple sequences containing standard DNA bp in FASTA format. The DHSpred web server then outputs the results of SVM-based predictions, along with probability values.t-test. By providing the mean and standard deviation (SD) found, the data are presented as mean ± standard error (SE). Also report the p-value and then draw a conclusion with α = 0.01, indicates that the difference is statistically meaningful. All statistical analysis was performed using our own script.The differences in MNC, DNC, TNC, TeNC, and PNC between ORIs and non-ORIs were analyzed using Welch's


Ammonia is constantly produced as a metabolic waste from amino acid catabolism in mammals. Ammonia, the toxic waste metabolite, is resolved in the liver where the urea cycle converts free ammonia to urea. Liver malfunctions cause hyperammonemia that leads to central nervous system (CNS) dysfunctions, such as brain edema, convulsions, and coma. The current treatments for hyperammonemia, such as antibiotics or lactulose, are designed to decrease the intestinal production of ammonia and/or its absorption into the body and are not effective, besides being often accompanied by side effects. In recent years, increasing evidence has shown that modifications of the gut microbiota could be used to treat hyperammonemia. Considering the role of the gut microbiota and the physiological characteristics of the intestine, the removal of ammonia from the intestine by modulating the gut microbiota would be an ideal approach to treat hyperammonemia. In this review, we discuss the significance of hyperammonemia and its related diseases and the efficacy of the current management methods for hyperammonemia to understand the mechanism of ammonia transport in the human body. The possibility to use the gut microbiota as pharmabiotics to treat hyperammonemia and its related diseases is also explored. Ammonia in the human body is produced mostly as a byproduct of protein digestion and bacterial metabolism in the gut . The kidThe direct consequence of hyperammonemia is represented by neurological disorders which include alterations of mood and personality, cognitive impairment, ataxia, convulsions, and coma . The sev3 and by mediated transport of NH4+ by channels and transporters through plasma membrane crossing, which will have a direct effect on the pH. Furthermore, NH4+ competes with K+ on K+ transporters, affecting the membrane potentials. A cascade of secondary effects and encephalopathy will result from these direct effects of elevated ammonia concentrations on the brain . Fi. FiN-carynthesis .Non-absorbable disaccharides are the first-line therapy for patients with hyperammonemia . The besRifaximin has become the most effective antibiotic of choice in the treatment of hyperammonemia because of its safety, efficacy, and tolerability . RifaximSodium benzoate decreases the blood ammonium level by reducing glycine metabolism in the liver, kidney, and brain. Benzoate integrates with coenzyme A (CoA) to form benzoyl-CoA in hepatocyte mitochondria. Then, benzoyl-CoA transfers the benzoyl moiety of the CoA ester to glycine and produces hippurate. This process hampers the degradation of glycine by the ammonia-forming metabolic pathway in the liver, kidney, and brain ,25,66.Sodium phenylacetate/phenylbutyrate is rapidly oxidized to phenylacetate, which conjugates with glutamine in the liver and then is excreted as a phenylacetylglutamine by the kidneys. While phenylacetate significantly increases the urinary production of phenylacetylglutamine, it prevents glutamine-stimulated ammoniagenesis ,26. A reA combination therapy of sodium benzoate and sodium phenylacetate decreases plasma ammonia levels and contributes to the high survival rate in urea-cycle-disorder (UCD) patients with acute hyperammonemia, with an acceptable adverse effect profile consisting of headache, nausea, and impaired mental status .l-Arginine and l-citrulline are a main and an intermediate product in the urea cycle (UC), respectively. l-arginine increases ammonia elimination by increasing l-citrulline and argininosuccinate production [l-citrulline administration restores l-arginine levels in N-acetylglutamate synthetase and carbamoyl phosphate synthetase-1 deficiencies and supports the urea cycle [l-arginine or l-citrulline administration is essential in UCDs to reactivate UC and reduce blood ammonium levels; however, the main drawback is the acute GI bleeding in cirrhotic patients [oduction ,30. l-cipatients .N-acetylglutamate (NAG) that activates carbamoyl phosphate synthetase 1 (CPS-1) in the urea cycle that is responsible for the removal of ammonia. Its administration is essential in patients with an inherent deficiency of NAG synthase [N-carbamylglutamate (NCG) can be used for partial CPS-1 deficiency patients to stimulate the remaining CPS-1 [Carglumic acid is a synthetic structural analog of synthase ,32,33. Ang CPS-1 . NCG admng CPS-1 ,32. Propng CPS-1 . Howeverng CPS-1 .Albumin-based dialysis (ABD) is considered as a regular part of treatment in intensive care medicine, especially for acute liver failure . AlbuminPeritoneal dialysis is an intracorporeal dialysis technique that uses the peritoneal membrane as a filter. The semipermeable peritoneal membrane allows solutes and water to be transported from the vascular system to the peritoneal cavity . AlthougMany drugs have been used for the treatment of hyperammonemia, but data to support their use are limited. However, most of these drugs can safely be used despite their limited proven efficacy.Neomycin and metronidazole have been historically used in the setting of hyperammonemia caused by liver disease . Antibiol-glutamine-N-acetyltransferase to form phenylacetylglutamine (PAGN) and is released by the kidney [Glycerol phenylbutyrate is a prodrug that is gradually hydrolyzed by pancreatic lipases, resulting in the delayed release of phenylbutyrate (PBA) in the GI tract. PBA undergoes β-oxidation to phenylacetate (PAA), which is conjugated with glutamine in the liver and the kidney through the enzyme phenylacetyl-CoA: e kidney . Glyceroe kidney ,41.l-ornithine phenylacetate contains both l-ornithine and phenylacetate in a salt form that activates the urea cycle (UC) in the liver [l-ornithine acts as a substrate for glutamine synthetase, thereby detoxifying ammonia into glutamine. Then, phenylacetate binds to excessive glutamine to make phenylacetate glutamine, which can be secreted by the kidneys. However, l-ornithine or phenylacetic acid alone cannot effectively treat HE, whereas phenylacetate-l-ornithine can effectively reduce intestinal glutaminase activity and its expression by improving the intestinal synthesis of glutamine, thereby reducing the brain arterial ammonia levels and extracellular ammonia in animal models [l-ornithine phenylacetate in cirrhotic patients induced a reduction of plasma ammonia and glutamine levels with a gradual increment in urinary phenylacetylglutamine [he liver ,43. In tl models ,83. The lutamine .l-Ornithine-l-aspartate fuels the ammonia-detoxifying metabolic pathway in the residual hepatocytes. The residual hepatocytes are the precursor liver cells that can generate a new generation of hepatocytes on physiological demand to increase the functional capacity of the liver. l-Ornithine is transformed to glutamate semialdehyde by ornithine aminotransferase, which is subsequently converted to glutamate. Finally, glutamate converts to glutamine, which detoxifies one ammonia molecule by glutamine synthetase [l-ornithine-l-aspartate successfully improved venous ammonia levels and cognitive abilities in HE patients [nthetase ,44. The patients ,46. Howepatients .l-Carnitine, a metabolic product of amino acids, activates UC enzymes and increases the elimination of free radicals by participating in the transportation of short-chain fatty acids through the peroxisomal and mitochondrial membranes [l-carnitine significantly reduced blood ammonia and improved patient mental status [embranes . A treatl status ,87.BCAAs (branched-chain amino acids) such as valine, leucine, and isoleucine interact with α-ketoglutarate through branched-chain aminotransferases and form glutamate and branched-chain α-keto acid. Glutamate converts to glutamine by incorporating an ammonia molecule through glutamine-synthetase . HoweverBioartificial liver support systems are model systems that recapitulate the liver metabolic activity. They are similar to the conventional hemodialysis with the addition of filtration through multiple hollow-fiber cartridges which contain cells with hepatocytic functions, such as the VTL C3A cell line . In a coCell therapy might be an appropriate strategy to transfer the missing enzymes via liver cell transplantation in UCD . Liver hGene therapy which introduces a functional enzyme-coding gene promises to restore UC activity in patients with primary UCD. The delivery of the ornithine transcarbamoylase and arginase 1 gene via an adeno-associated virus vector resulted in successful phenotype correction in mouse models, while the safety of the gene delivery system and its long-term effectiveness for human trails has been challenging ,60,88.9 colony forming units (CFU)/mL and 1012 CFU/mL of bacteria may be found in the terminal ileum and colon [Lactobacillus species could reduce blood ammonia levels and improve health. Current pharmabiotic approaches are shown in .It is well known that chronic hyperammonemia (HA) can induce cognitive decline and anxiety-like behavior in a rat model, demonstrating that HA-mediated HE can cause neurological dysfunctions. Furthermore, the treatment with the probiotic strain  HA rats . From pral flora . Also, Eopathies . Probiotopathies , probablopathies . Anotherreported . It was n levels . A numbeLactobacillus, Bifidobacterium and Streptococcus thermophilus), selected specifically for their ability to reduce inflammation and reduce intestinal permeability. Each hydroxypropyl methylcellulose capsule of VSL #3 contains a high number of live freeze-dried probiotic bacteria (110 billion) that are constituents of the normal GI flora of healthy humans [Since several probiotic strains have the ability to treat diseases associated with hyperammonemia, it was also reported that highly concentrated combinations of probiotic strains have a more significant effect on the treatment of HE patients . The VSLy humans . A consiy humans . Two phay humans . In addiPediococcus pentosaceus, Leuconostoc mesenteroides, Lactobacillus plantarum 2592, and Lactobacillus paracasei subsp. paracasei 19, each at a dose of 1010 CFU per sachet, along with 10 grams of biologically active fermentable fibers consisting of inulin, pectin, beta-glucan, and resistant starch, can be used to treat cirrhosis patients with minimal HE, leading to a significant reduction in the number of urease-producing bacteria such as E. coli, Staphylococcus, and Fusobacterium sp. In contrast, no–urease-producing Lactobacillus sp. increased significantly, becoming the predominant creature in the stool [Synbiotic supplementation, which contains the lyophilized non-urease-producing bacteria he stool . The synhe stool . The reghe stool . Moreovehe stool .Current therapies for hyperammonemia treatments, involving rifaximin, lactulose, and probiotics, focus on the intestinal ecosystem and indeed have variable effects on the composition and function of the intestinal microbiota . TherefoEnterobacteriaceae but maybe anaerobes or gram-positive bacteria. In healthy conditions, the activity of urease from urease-producing bacteria is normally beneficial for the hosts. In the presence of liver diseases, however, it is very pathogenic to the hosts. Urea produced by the liver as a waste product is both excreted by the kidneys in urine and transported into the colon [Ammonia can be produced by the urease that hydrolyzes urea into carbon dioxide and ammonia . As it ihe colon . In unhehe colon . The cirhe colon .Fusarium and Enterobacteriaceae, as well as in the abundant primary taxa of the Ruminococcaceae, Lachnospiraceae, and Clostridia strains, compared with that of healthy individuals. Recent studies have shown that the cirrhosis dysbiosis ratio (CDR) is positively correlated with cirrhosis, as calculated by quantifying fecal bacterial strain counts in a control group, in patients with compensated cirrhosis, and in patients with decompensated cirrhosis. The lower CDR indicates a less diverse gut microbial composition and is associated with increased scores in the model for end-stage liver disease (MELD) and with increased intestinal permeability [It was observed that the microbiome was altered in liver diseases , and thieability . Decompeeability .Parabacteroides (strain ASF519), Lachnospiraceae (strain ASF502), Ruminococcaceae (strain ASF500), Eubacterium (strain ASF492), Mucispirillum (strain ASF457), L. salivarius (strain ASF361), L. acidophilus (strain ASF360), and Clostridium (strain ASF356). The bacteria were selected because of their dominance and persistence in the normal microflora of mice and also because this consortium of eight bacteria has the minimal urease gene content [Evidence suggests that fecal transplantation may have a therapeutic effect on the disease by altering the microorganisms bringing them close to their normal composition. In Ting-Chin David Shen’s study with mice inoculated with a slurry of bacteria with low urease gene activity via fecal transplantation, ammonia concentration in the feces was significantly reduced . The alt content . The ani content . These r content .Hyperammonemia is a disease of metabolic disturbances resulting from an excess amount of ammonia in the blood. Although the immediate consequence of hyperammonemia is to cause encephalopathy and death, a prolonged, low-degree hyperammonemia might be related to neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s diseases, etc. . Therefo