Sarcopenia, with risk factors such as poor nutrition and physical inactivity, is becoming prevalent among the older population. The aims of this study were (i) to systematically review the existing data on sarcopenia prevalence in the older Chinese population, (ii) to generate pooled estimates of the sex-specific prevalence among different populations, and (iii) to identify the factors associated with the heterogeneity in the estimates across studies. A search was conducted in seven databases for studies that reported the prevalence of sarcopenia in Chinese older adults, aged 60 years and over, published through April 2020. We then performed a meta-analysis to estimate the pooled prevalence, and investigated the factors associated with the variation in the prevalence across the studies using meta-regression. A total of 58 studies were included in this review. Compared with community-dwelling Chinese older adults , the pooled prevalence of sarcopenia in older adults from hospitals  and nursing homes  was higher. The multivariable meta-regression quantified the difference of the prevalence estimates in different populations, muscle mass assessments, and areas. This study yielded pooled estimates of sarcopenia prevalence in Chinese older adults not only from communities, but also from clinical settings and nursing homes. This study added knowledge to the current epidemiology literature about sarcopenia in older Chinese populations, and could provide background information for future preventive strategies, such as nutrition and physical activity interventions, tailored to the growing older population. The speed of population ageing is accelerating globally. According to statistics from the World Health Organization (WHO), by 2050, the proportion of individuals over the age of 60 is expected almost to double (22%) compared with 12% in 2015 [Advancing age is marked by a series of physiological changes in body composition, including the decrease in skeletal muscle mass and increase in fat mass ,4. SarcoSarcopenia is diagnosed based on low muscle mass, low muscle strength, and diminished physical performance. However, no standard and unique diagnosis criteria for sarcopenia have yet been established. At present, several international groups, such as the European Working Group on Sarcopenia in Older People (EWGSOP), Asia Working Group for Sarcopenia (AWGS), International Working Group on Sarcopenia (IWGS), Foundation for the National Institutes of Health (FNIH) Sarcopenia Project, have provided their own diagnostic criteria for sarcopenia ,13,14. EAt present, two systematic reviews have pooled the estimate of sarcopenia prevalence in community-dwelling Chinese older adults  ,25. HoweInformation about the prevalence of sarcopenia is the first step to develop preventive routines or health services tailored to the growing older population. Meta-analysis and meta-regression of prevalence data are increasingly important for policy making and implementation of preventive measures in situations for which inconsistent prevalence estimates have been reported in the literature. This study could help policy makers and health practitioners make evidence-based decisions targeting the health issues of sarcopenia.This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) statement .Two researchers (Z.C. and W.Y.L.) independently searched the following online electronic databases: PubMed, Cochrane Library, Embase (Ovid), CINAHL, Web of Science Core Collection, CNKI, and Wanfang (accessed on 15 April 2020); the latter two being Chinese. The search period was restricted from the earliest records to 15 April, 2020. Key search terms were “sarcopenia”, “epidemiology”, “prevalence”, “aged”, “elderly”, “older”, “China”, and “Chinese”. Logical operators  were used to shape the search strategy. Detailed search strategies for PubMed and Wanfang are presented in the Inclusion criteria were as followed: (1) the prevalence of sarcopenia was reported or could be calculated; (2) participants were of Chinese ethnicity; (3) the age was 60 years and over; (4) participants were recruited from the community, clinical settings, or nursing homes; (5) EWGOSP, AWGS, IWGS or FINH definitions of sarcopenia were adopted; (6) muscle mass was measured with DXA or BIA; (7) primary research irrespective of design. Exclusion criteria were (1) studies published as reviews, letters to editors, conference abstracts, expert opinions, case reports; (2) studies published in languages other than English and Chinese.First, duplicate records were identified and removed. Then, titles and abstracts were screened to remove studies irrelevant to the research questions. Next, full-text articles were retrieved and reviewed for eligibility according to the selection criteria. When multiple papers came from the same dataset, we chose the one with the largest sample size which might be closer to the original cohort in order to avoid those using a particular subset of the whole dataset. The above process was performed independently by the two researchers (Z.C. and W.-Y.L.). Any discrepancies were adjudicated by a third researcher (P.-H.C.).The following details were extracted from each of the eligible studies: the year of publication, country or area in which the data were collected, research design, sample size, settings where participants were recruited, diagnostic criteria for sarcopenia, measurement of muscle mass, muscle strength, and physical performance and prevalence of sarcopenia. For cohort or intervention studies, only baseline data were extracted. For studies using more than one diagnostic criterion to define sarcopenia, all estimates of prevalence were extracted.Two researchers (Z.C. and W.Y.L.) independently assessed the quality of included studies using a validated tool developed by Hoy et al., which was tailored to assess the risk of bias for prevalence studies with different types of design . The tooThe prevalence of sarcopenia varied in different genders and populations recruited from different settings . Accordimetaprop command in Stata 15.0  was used to obtain pooled estimates of prevalence [Random-effect models take into account the possibility that the parameters for the population may vary among studies . Therefoevalence ,32.p-value < 0.10 indicating heterogeneity [2 statistics of 25%, 50%, and 75% set as the cut-offs for low, moderate, and high heterogeneity, respectively [metareg command) to model the adjusted association between multiple explanatory variables and prevalence estimates. Based on previous evidence, we considered the following study characteristics to be potential sources of heterogeneity: populations from different settings, diagnostic criteria for sarcopenia, assessment of muscle mass, muscle strength and physical performance, and the area of study. In order to have a sufficient power, meta-regression was only performed for covariates reported in at least ten studies [We assessed the heterogeneity in the estimates across studies using Cochran’s Q test, with a ogeneity . We quanectively . If heteectively . For thi studies .Publication bias refers to the phenomenon that studies with significant results are more likely to get published than those with negative results, which can result in systematic differences between published and unpublished studies . In the We identified 459 records from databases and 6 records from the reference lists. After removing 139 duplicated records, we screened the titles and abstracts of the remaining 326 records, and removed another 168 irrelevant records, leaving 158 studies. Further reviewing the full texts of these studies for eligibility, we excluded another 100 for the reasons specified in The characteristics of the included studies are summarized in 2 = 95.2%). For participants from different settings, the pooled prevalence rates were 12.9%  in community-dwelling older men (n = 27), 29.7%  for hospitalized older men (n = 9), and 26.3%  in nursing-home residents (n = 5). We did not pool the prevalence for outpatients due to an insufficient number of studies (n = 2). Substantial heterogeneity in prevalence estimates was found across the studies, with all of the I-square values being greater than 80%.In the 46 studies that reported the prevalence of sarcopenia in older men, the overall prevalence was 18% . For participants from different settings, the prevalence was 11.2%  in community-dwelling older women, (n = 27), 23.0%  for hospitalized older women (n = 9), and 33.7%  for those from nursing homes (n = 4). Because only one study reported the prevalence for female outpatients, we did not perform meta-analysis for outpatients. Similarly, considerable heterogeneity was found across studies.In the 44 studies that reported the prevalence of sarcopenia in older women, the overall prevalence was 16.4%  as well. We also systematically investigated factors that contributed to the significant heterogeneity in pooled prevalence estimates using multivariable meta-regression. Our findings contribute to the epidemiological literature on sarcopenia in Chinese older adults, and can provide a starting point for future research and efforts in sarcopenia prevention among Chinese populations.For community-dwelling Chinese older adults, we obtained similar estimates of prevalence (12.9% in men vs. 11.2% in women) compared with previous reports  ,25. WhenMultivariable meta-regression indicated that the populations being from different settings was a significant factor contributing to the variation in the pooled prevalence estimates for both genders. Compared with community-dwelling older residents, those who were hospitalized were at 1.69 to 2.10 times the risk of prevalent sarcopenia, and nursing-home residents had 2.50 to 2.73 times the risk. The much higher prevalence rate of sarcopenia in older adults from hospitals and nursing homes was also reported by Papadopoulou and colleagues . HoweverWe found the prevalence estimate in older men varied depending on the method used to assess muscle mass. Specifically, compared with the DXA method, the risk of prevalence was lower  when using the BIA method. However, no such difference was detected in older women. There is some evidence that the BIA method tends to yield higher estimates of muscle mass, and therefore lower estimates of the prevalence of sarcopenia than the DXA method . Wu and Our study also found the risk of prevalent sarcopenia in older Chinese men living outside the mainland, specifically, in Hong Kong and Taiwan, to be nearly half that of their counterparts living on the mainland . However, this difference was not significant in the case of older Chinese women. Regional variation in the prevalence of sarcopenia among community-dwelling Chinese older adults was also reported in a previous systematic review, with 17% in mainland and 6% in Hong Kong and Taiwan . However2 for both genders (Previous observational studies found that older age was significantly associated with sarcopenia and severe sarcopenia in Chinese older adults ,50. Howe genders . We did The present study was subject to several limitations. Firstly, a few of the included studies reported the prevalence by different age groups, so we could not pool the prevalence rate by age subgroup. However, age is a well-established factor of sarcopenia. The lower bound of age for participants in the studies included in this review ranged considerably, from 60 to 80 years. Therefore, age may be a significant source of the substantial heterogeneity that we found across studies. Future epidemiological research of sarcopenia is encouraged to report age-specific prevalence. Secondly, due to the small number of studies which reported the prevalence of sarcopenia for outpatients, we were unable to obtain a pooled prevalence rate for this group. Thirdly, we did not include all of the possible covariates in our meta-regression analysis to investigate the source of considerable variations in sarcopenia prevalence. For example, all of the included studies used dynamometers to assess muscle strength, but we had insufficient information to investigate the potential influence of the type of dynamometer used on the prevalence rate. We were likewise unable to analyze the influence of different measurement protocols used for the gait speed tests due to insufficient information. Finally, our results should be interpreted with caution because most of the included studies had a moderate risk of bias and significant heterogeneity.This meta-analysis and meta-regression provides a comprehensive synthesis of sarcopenia prevalence in current literature targeting Chinese older populations not only from communities, but also from clinical settings and nursing homes. This is, to our knowledge, the first study to report pooled prevalence in Chinese older populations from clinical settings and nursing homes, and to examine the impact of populations from different settings, diagnostic criteria, muscle mass assessments, areas and walk distance of gait speed test on the prevalence estimate of sarcopenia via meta-regression analysis. Despite the variations in prevalence estimate across studies, this study revealed a certain proportion of Chinese older adults suffering from sarcopenia, especially for those who were hospitalized and residing in nursing homes. Considering the accelerating pace of aging, efforts should be made to implement early screening and lifestyle interventions such as nutrition and physical activity promotion to prevent this increasingly widespread age-related geriatric syndrome, especially for vulnerable groups.


Parkinson's disease (PD) is a disease that involves brain damage and is associated with neuroinflammation, mitochondrial damage, and cell aging. However, the pathogenic mechanism of PD is still unknown. Sequencing data and proteomic data can describe the fluctuation of molecular abundance in diseases at the mRNA level and protein level, respectively. In order to explore new targets in the pathogenesis of PD, the study analyzed molecular changes from the database by combining transcriptomic and proteomic analysis. Differentially expressed genes and differentially abundant proteins were summarized and analyzed. Enrichment and cluster analysis emphasized the importance of neurotransmitter release, mitochondrial damage, and vesicle transport. The molecular network revealed a subnetwork of 9 molecules related to SCNA and TH and revealed hub gene with differential expression at both mRNA and protein levels. It found that ACHE and CADPS could be used as new targets in PD, emphasizing that impaired nerve signal transmission and vesicle transport affect the pathogenesis of PD. Our research emphasized that the joint analysis and verification of transcriptomics and proteomics were devoted to understanding the comprehensive views and mechanism of pathogenesis in PD. Parkinson's disease (PD) is an age-dependent neurodegenerative disease with the pathological part in the brain. Neurons in the substantia nigra of PD patients are lost massively with lack of striatum dopamine . The damRNA sequencing has been reported in the pathogenesis, and quantitative proteomics plays a role in the pathogenesis of PD, providing molecular abundance change in PD patient tissues , 7. BlooOn the other hand, Proteomics, a high throughput technique based on mass spectrometry, has shown superiority in revealing the pathogenesis of Parkinson's disease, and the proteomics of the substantia nigra has provided new insights to explain the prominent dysfunction in PD patients , 12. It http://www.ncbi.nlm.nih.gov/gds/). Proteomic results in the substantia nigra of PD patients are sourced from the proteomeXchange database (http://www.proteomexchange.org/). Pearson analysis calculates the r value by fitting the correlation curve. The threshold of fold change was set to 2 (∣FC | ≥2). Significant differences were described by calculating p values (p < 0.05).The data of the substantia nigra region of Parkinson's patients were extracted from the literature, and only the transcriptome and proteome data of the substantia nigra region were considered. In addition, the sequencing data of substantia nigra in PD patients was extracted from GEO Datasets (https://https://david.ncifcrf.gov/tools.jsp).Gene ontology (GO) analysis was used for clustering and enrichment analysis. Pathway analysis was described by Kyoto Encyclopedia of Genes and Genomes (KEGG). The Database for Annotation, Visualization, and Integrated Discovery   was usedhttp://www.bioinformatics.com.cn). Pearson's analysis was used to reveal correlations between transcriptomic and proteomic data, and Pearson's coefficients r were used to indicate positive or negative correlations.Visualization of GO analysis was performed through GO chord diagrams to show the relationship between molecular expression and enrichment items. KEGG bubble maps were used to map the results of pathway analysis using bioinformatic tools (https://string-db.org/cgi/input.pl), and the social network was drawn and optimized by Cytoscape software (version 3.7.2) [Molecular networks are based on interactions including textmining, experiments, databases, coexpression, neighborhood, gene fusion, and co-occurrence. The molecular network was constructed by STRING (n 3.7.2) . MCODE, t-test was used to analyze the significance of the data, and values of p < 0.05 were set statistically significant and ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.Visualization and analysis of data were performed in Prism . Student's Analysis of transcriptomics is an effective method to describe changes in the gene expression during the occurrence and development of diseases . To undeTo understand the interactions of DEGs, we constructed a social network. The interaction network of 96 molecules was enriched in STRING and artisticized in Cytoscape  was used to summarize the known targets of disease, and 516 PD-related molecules were retrieved. The expression of genes related to PD with high scores was extracted and found that SNCA, LRRK2, PINK1, TH, BDNF, and SOD2 were downregulated, while COMT, SNCAIP, CASP3, GFAP, and BCL2 were upregulated  through mRNA splicing and protein translation. ACHE existed on the cell surface as an oligomer. ACHE had catalytic activity and could hydrolyze neurotransmitters, acetylcholine ,and brain choline to terminate signaling. ACHE in the cerebral cortex has been found to be upregulated in Parkinson's dementia, which can influence the cognitive function . CADPS eOur research emphasizes that the joint analysis and verification of transcriptomics and proteomics were devoted to understanding the comprehensive views and mechanism of pathogenesis in PD.


Background: Stroke is the second leading cause of death and disability worldwide. Stroke centers have become a central component of modern stroke services in many high-income countries, but their feasibility and efficacy in low, middle, and emerging high-income countries are less clear. Also, despite the availability of international guidelines, many hospitals worldwide do not have organized clinical stroke care. We present a methodology to help hospitals develop stroke centers and review quality data after implementation.Objectives: To describe and compare demographics, performance, and clinical outcomes of the Pacífica Salud, Hospital Punta Pacífica (PSHPP) stroke center during its first 3 years 2017–2019.Methods: Pacífica Salud, Hospital Punta Pacífica was organized to implement protocols of care based on the best practices by international guidelines and a quality improvement process. The methodology for implementation adapts a model for translating evidence into practice for implementation of evidence-based practices in medicine. This is a retrospective study of prospectively collected quality data between March of 2017 to December of 2019 for patients admitted to PSHPP with primary diagnosis stroke. Data collected include demographics, clinical data organized per the Joint Commission's STK Performance Measures, door to needle, door to groin puncture, 90 day modified Rankin Score, and hemorrhagic complications from IV thrombolysis and mechanical thrombectomy (MT). Primary outcome: year over year proficiency in documenting performance measures. Secondary outcome: year over year improvement.Results: A total of 143 patients were admitted for acute ischemic stroke, TIA, or hemorrhagic stroke. Of these, 36 were admitted in 2017, 50 in 2018, and 57 in 2019. Performance measure proficiency increased in the year-over-year analysis as did the total number of patients and the number of patients treated with IV thrombolysis and MT.Conclusions: We present the methodology and results of a stroke program implementation in Panamá. This program is the first in the country and in Central America to achieve Joint Commission International (JCI) certification as a Primary Stroke Center (PSC). We postulate that the dissemination of management guidelines is not sufficient to encourage the development of stroke centers. The application of a methodology for translation of evidence into practice with mentorship facilitated the success of this program. Interventions of proven benefit for acute stroke treatment include: administration of intravenous thrombolysis (IVT) within 4.5 h of symptom onset –3, mechaObservational studies and randomized trials have shown that stroke units improve the use of diagnostic tests and acute treatments, increase access to rehabilitation services, and lengthen survival without dependence following acute ischemic stroke , 12, 16.While the guidelines are widely available, it is often difficult to implement stroke centers in regions such as emerging high-income countries and low- and middle-income countries (LMIC) where organized systems of care are uncommon, resources scarce, and experience limited. In this paper, we describe the development, implementation, and performance of a stroke program in a hospital in Panamá, which ultimately achieved Joint Commission International (JCI) certification as a Primary Stroke Center (PSC) in February of 2020.This observational, retrospective analysis of prospectively acquired de-identified data from patients qualified (primary diagnosis stroke) for the stroke program at Pacífica Salud, Hospital Punta Pacífica (PSHPP) during the years 2017 through 2019. The hospital is a JCI accredited, private medical facility in Panamá City with 76 beds and over 5,500 inpatient visits per year.In December of 2016, PSHPP and Johns Hopkins Medicine International started a collaboration to design and implement a stroke program. We followed a methodology that has been used by our group in other stroke program building projects, steps listed below. Our methodology is an adaptation of the process outlined by Pronovost et al. for translating evidence into practice , 23. ThiGuidelines and best practices to be implemented at the site were assessed.Site survey was conducted to determine current stroke care, resources, staff, and logistics.A multidisciplinary/interprofessional Stroke Task Force was formed to create policies, procedures, and workflows for the stroke program. The team consists of professionals from departments that provide care for stroke, including the Emergency Department, Radiology, Laboratory, Pharmacy, Intensive Care Unit, Inpatient Unit, Rehabilitation, Neurology, Neurosurgery, and Critical Care Medicine. Standardization of IV thrombolysis served as an anchor, setting the tone for interprofessional collaboration.Intensive education program including lectures, training sessions, and reading material was implemented for nurses, physicians, healthcare workers, and all personnel in the hospital.Apparatus for collecting data measuring the quality of the processes implemented was created.Policies, procedures, and workflows were implemented and the stroke program was formally launched.Collaborative efforts within the multidisciplinary/interprofessional task force continued. Progress and Quality Improvement (QI) process was monitored with the goal of achieving JCI certification. Mock surveys and data monitoring by the Stroke Task Force informed further QI.Data pertaining to the demographics, stroke performance measures, and stroke outcomes for adult patients (age ≥ 18) admitted to PSHPP with primary diagnosis stroke during the years 2017–2019 were collected prospectively, deidentified, and analyzed for quality improvement. Quality of stroke care was assessed using standard performance measures adapted from American Heart Association/American Stroke Association . We alsop-values are p < 0.05.Data are presented as proportions for dichotomous variables and mean [standard deviation] or median (interquartile range) for continuous variables. Significant p-value, an additional post-hoc analysis comparing each pair of years was conducted  across years. Fisher exact test for proportions was performed to compare distribution of categorical variables  across years. For variables showing statistically significant onducted .p-value, an additional post-hoc analysis comparing each pair of years was conducted  among the 3 years (p = 0.659), with TIA being the most common, hemorrhagic stroke the least common, and ischemic stroke consisting of about a third of all patients (p = 0.6725). Most common risk factors for stroke patients include hypertension, type II diabetes mellitus, heart disease, prior cerebrovascular disease, dyslipidemia, and arrhythmias  except stroke education (STK-8) showed an improvement between year 2017 and 2019. Similarly, the rate of swallowing screen steadily increased from 2017 to 2019, with the difference being significant for years 2017 vs. 2019 .p = 0.007) and a significant positive correlation between year and median lab turnaround time  scores were 2b or greater in all patients treated in 2018 and 2019. There was one case of fatal symptomatic intracerebral hemorrhage in 2019 .n = 23), 10/23 (43.5%) had a score of 0, 4/23 (17.4%) of 1, 1/23 (4.3%) of 2, 3/23 (13.0%) of 4, 1/23 (4.3%) of 5, and 4/23 (17.4%) of 6  of 6 .We present the process for implementation of a stroke center in a hospital in Panamá. Over the development of the program, we observed a statistically significant improvement in a variety of standardized stroke performance measures: steady increase in the total number of stroke patients treated, and total number of IVT and MT in the year over year comparison. While data from before 2017 is not available as the QI database was created as part of this organizing effort; significant improvements are noted in most areas recorded during the first 3 years of implementation of the stroke center.It is important to note, however, that not all trends reflect improvement in the data. Some unexpected findings may be the result of performance improvement projects which changed definitions of variables or measurement. For example, the stroke education procedure was redesigned in 2018, with a more rigorous definition of what qualified as “stroke education” and may explain the significant decrease in the rate of stroke education (STK-8) between the first 2 years and 2019. Also, the documentation of 90-day mRS was implemented in 2018; therefore, data for 2018 are sparse with significant improvements in documentation for 2019. The mRS in 2019 demonstrated a distribution consistent with published data , 29. TheThe door to needle time was significantly improved from 2017 to 2018 and maintained a median below 60 min. Door to groin puncture also improved from 2018 to 2019. The groin puncture to recanalization, median time, in 2019 was 51 min. All these critical times consistent with the literature and international benchmarks. There was only one symptomatic intracerebral hemorrhage among the thrombectomy patients, which was fatal. Due to the low number of cases, it is difficult to reach conclusions regarding the significance of this finding.The organization of highly proficient stroke programs has been slower to spread in emerging high-income countries and LMIC, and in Latin America  despite A review of the literature concerning implementation of stroke units in LMIC or implementation of organized stroke care elements, did not reveal reports of a comprehensive methodological approach as was used in our group, rather; when discussing the development of stroke units, the emphasis is placed in the evidence for the benefit of stroke units, and the exortation that physicians need to take the lead to organize care teams and implement guidelines based on local resources . Papers Our implementation benefited from the setting. Panamá is an emerging high-income country and the setting is a small private hospital that has significant resources. This is in contrast with low resource settings in which barriers to stroke care are more significant. However, we view the value of the methodology in that it may be applied to different resource levels according to World Stroke Organization's Global Stroke Guidelines, Action Plan: A Roadmap for Quality Stroke Care , after dThis study is limited due to the program being implemented in a small private hospital in one country. The findings in this study, therefore, should not be used to draw conclusions about the general patient population in Latin America. Other limitations include the small total volumes and the lack of pre implementation data which make it difficult to ascertain the effect of organization over the baseline stroke care proficiency at this hospital. Finally, challenges in data definition and collection are also noted.In conclusion, we present a methodology and results of the implementation of a stroke program in Panamá. This program is the first in the country and in Central America to achieve JCI certification as a PSC. We postulate that the dissemination of management guidelines is not sufficient for the development of stroke centers, but the application of a methodology for translation of evidence into practice with mentorship can facilitate success of the program.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Johns Hopkins University School of Medicine and Pacífica Salud Hospital Punta Pacífica. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.NN-E: led implementation, manuscript review, and analysis. YM: manuscript first draft, statistics, and analysis. AO: implementation, data collection, and manuscript review. TF, IC, EO, EE, LK, EZ, and BJ: implementation and manuscript review. VU: designed implementation methodology, led implementation, manuscript review, writing segments of manuscript, and analysis. All authors contributed to the article and approved the submitted version.VU—Site PI for TIMELESS (Genentech Inc), Grant for investigator sponsored trial OPTIMISTmain . The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Language and communication deficits characterize both autism spectrum disorder and developmental language disorder, and the possibility of there being a common profile of these is a matter of tireless debate in the research community. This experimental study addresses the relation of these two developmental conditions in the critical topic of language. A total of 103 children  participated in the present study. Specifically, the study’s sample consisted of 40 children with autism, 28 children with developmental language disorder, and 35 typically developing children between 6 and 12 years old. All children completed language and cognitive measures. The results showed that there is a subgroup inside the autism group of children who demonstrate language difficulties similar to children with developmental language disorder. Specifically, two different subgroups were derived from the autism group; those with language impairment and those without. Both autism and language-impaired groups scored lower than typically developing children on all language measures indicating a common pathology in language ability. The results of this study shed light on the relation between the two disorders, supporting the assumption of a subgroup with language impairment inside the autism spectrum disorder population. The common picture presented by the two developmental conditions highlights the need for further research in the field. A growing body of research focuses on the investigation of language and communication deficits observed in children with developmental disorders, such as Developmental Language Disorder (DLD) and Autism Spectrum Disorder (ASD) e.g., ,2). Indi. Indi2])Developmental Language Disorder (DLD) is not a term included in the Diagnostic and Statistical Manual of Mental Disorders DSM-5), however, it is widely accepted amongst both the scientific community and clinicians. Instead, the DSM-5 includes the term “Language Disorder”  to define persistent difficulties in the acquisition and use of language, because of impairments presented in comprehension or production , however, namely DLD is a heterogeneous disorder; symptoms can be either expressive , receptive , or a combination of the two . RecentlAutism is a disorder characterized primarily by social deficits, as two of the three main diagnostic features, namely impaired communication and reciprocal social interaction, exist within the social domain. According to the DSM-5, a diagnosis of ASD has to include deficits in (1) social communication, and social interaction which occur across multiple contexts and (2) restricted repetitive behaviors, interests, and activities )Research so far provided evidence of higher-verbal children with ASD, who score similar to TD children, based on a range of structural language measures . The abiThe great heterogeneity observed within the ASD population is also apparent in the extent of structural language difficulties that co-occur with ASD ,66,71. IAs it concerns the communication domain, diagnostic features refer to delays and impairments in language acquisition, and qualitative deficits in discourse and other pragmatic aspects of language as well. A great emphasis in the research community about language in autism has focused its interest on the pragmatic impairments, which are treated as universal among ASD individuals and are specific to this disorder ,77. The In the Greek language, only limited studies included children with ASD. In a study investigating the narrative skills of 30 Greek-speaking children with ASD (ALN and ASD-LI) and a TD group, their narrative ability was measured in terms of both microstructural and macrostructural properties. Microstructural properties are referring to lexical and syntactic measures of complexity and macrostructure to the diversity in the use of internal state terms (ISTs) and the complexity of the story’s structure. The results showed that increased language ability and syntactic complexity are positively connected to ASD children’s narrative performance. However, both ALN and ASD-LI groups of children with ASD scored lower than the TD controls in measures of the production of Theory of Mind-unrelated ISTs, modifier clauses, and story structure complexity .In an additional study in the Greek language with high-functioning ASD children, results were indicative of difficulties in the ASD group at the interface of syntax with pragmatics and prosody. Specifically, they produced significant deficits in their ability to distinguish a discourse prominent element and to consider intonation relevant for a particular interpretation that excludes clitics, in relation to their TD peers . The difficulties of ASD-LI children in the Greek language are also supported by a study with Greek-Cypriot children investigating comprehension and production of two-constituent compound words. The results of the study indicate that despite the ASD-LI children’s ability to recognize compound constituents they demonstrated impairments to understand the compound meaning. In addition, they produced semantically inappropriate responses when attempted to explain the meaning of the compounds, indicating limitations in their conceptual-intentional system . To sum up, ASD is a highly heterogeneous disorder, with impaired cognitive-language abilities throughout the spectrum. Understanding the nature of these language deficits is complicated by the great heterogeneity of language and cognitive abilities within this population . For insMany studies have examined any potential phenotypic overlap between autism and DLD, especially in the language domain. Numerous studies have found that there are many similarities in the language abilities of children with autism and children with DLD and argue that the reason for these similarities is a shared etiology ,15.Impaired language development is apparent in DLD and—at least—in subgroups of ASD individuals. The relationship though, of these two developmental conditions with language deficits, is still undetermined. In the last twenty years, several assumptions have been made suggesting that a clear diagnostic border separating the two disorders may not emerge as clear as expected ,16,81. TIn addition, Lloyd and colleagues  administThe assumption of a common phenotypical path linking the two developmental conditions is furthermore strongly supported by McGregor and colleague’s findings . In theiThe grammar ability of the two groups has also been studied by Tuller and colleagues , who staMore recent data also highlight the possible overlap between the two conditions. Specifically, the CELF-4 standardized test was administered to assess ASD, DLD, and TD children’s language skills. The results showed no significant differences in language between the DLD and ASD groups, suggesting an overlap in the linguistic profiles of children with DLD and children with ASD .Recent evidence supports the existence of common ground between the two conditions in relation to the field of semantics. Gladfelter and Barron  exploredIn addition, a study by Modyanova and colleagues  investigThere is also research evidence supporting the existence of a common ground related to the field of pragmatics. In a recent study, where ASD-high function (HFA), DLD and TD groups of children participated, the groups were experimentally tested on various components of grammar, pragmatics, and nonverbal cognition. The results showed similar performance of DLD and HFA in pragmatics, lower than their TD peers. However, the DLD group performed significantly lower than the TD children on grammar and several cognition tests, while the HFA group did not . Thus, aAdditionally, Norbury and colleagues  also invAs it concerns the longitudinal outcomes of the proposed overlap, data from adolescents come to add to the “commonality” hypothesis. Specifically, Conti-Ramsden and colleagues , in theiDespite the above-mentioned studies arguing in favor of possible comorbidity of the two conditions, another theoretical position states that the similarities in the language and memory performance of children with autism and children with DLD are simply superficial, and do not suggest a common etiology . The evidence for this position gains support from studies in which children with DLD and children with autism demonstrate different patterns of deficits between the two conditions e.g., ,13). For. For13])In another study with adolescents with DLD and ASD-LI, the findings showed the second groups’ participants to outperform DLDs’ in lexical tasks involving word associations and structures . In an an = 8). An additional study . ASD group differed from ASD-LI group, DLD group form the group ASD-LI and ASD-LI from TD children’s group. The means and standard deviation scores are presented in p = 0.962 and p = 0.298, respectively. Similarly, the socioeconomic status of the family, was also not significantly different among groups, p = 0.975. Descriptive statistics of participants’ characteristics are presented in Participants IQ total score and age (in months) were treated as covariates, as one-way ANOVA revealed significant group differences of the two variables. Specifically, there appears to be a statistically significant effect of group on the dependent variables of IQ total variable, F  = 6.3, Our concern was that any group of differences may not be due to the group factor, but instead may simply reflect differences in total IQ score and/or age. To address this concern, we performed two LMM analyses for each of the dependent variables (language measures and the composites scores of the CCC-2). In all models A we included measures of total IQ and age as covariates, so that any fixed effect of group then reflects differences due to group membership above and beyond any individual differences in IQ score or age. In all models B we included only the factor of the group. Additionally, in all analyses we considered subjects as random effects. All models A showed that total IQ score and age are not significant predictors of the slope. In other words, the effect of factor group on the dependent variable was constant across the values of total IQ and age. In this study, the measures used to answer the research questions were the EREL, the Non-Words Repetition task (NWR), and also the Children’s Communication Checklist- Second edition (CCC-2). The Non-Words Repetition task (NWR) data was treated as raw scores because we wanted to include in our methodological design the factor of age. However, we were not able to manipulate all data in this way, since there are measures that provide their diagnostic algorithms, and transformation to z scores is already constructed by the manual provided, as in the case of WASI, and CCC-2. For these instruments, the manual’s diagnostic instructions were followed.The administration of EREL language assessment revealed a language-impaired subgroup of children within the ASD group. The ASD group was then sub-divided upon participants’ performance on the EREL instrument. A group of children with language impairment (ASD-LI), and a group of children with normal language (ALN) were identified; ASD participants whose scores were −1.25 SD or more below the normative mean on two out of four Core Language scores  formed tThese results transformed the experimental groups and an additional group emerged by the analysis. Especially, the final groups were formed as follows: 16 children consisted the ASD group  , 28 children the DLD group , 24 children consisted the ASD-LI group , and 35 children  the TD group. Four children from the general population were also found to meet the DLD diagnostic criteria. The group descriptions that emerged by the language ability analysis are presented in In addition, the multilevel model was preferred for the analysis, as we assumed the existence of heterogeneity between individuals. The results are presented in The model ICC was also significant for all the language measures see , as the p < 0.001. Specifically, the ALN group scored significantly higher (p < 0.01) from ASD-LI, p < 0.001, and DLD children, p < 0.001. Interestingly, there were not any important differences between ALN and TD groups of children (p = 0.33). No important differences were also observed between participants in the ASD-LI and DLD groups p = 0.90, while ASD-LI and also DLD groups, scored significantly lower than the TD groups, p < 0.001. The ICC model for CFD measure was large (57%), further supporting the existence of important inter-individual differences among the participants. For the Concept and Following Directions (CFD) subscale of EREL, results revealed important group differences, p < 0.001. Important differences were found between the ASD-LI group, which scored significantly lower (p < 0.01) than the TD group, and also the DLD group scored significantly lower than the TD group, p < 0.001. No important differences were found among ALN and TD groups (p = 0.07), DLD group (p = 0.89), nor ASD-LI group (p = 1.0). Similarly, no important differences were observed between ASD-LI and DLD participants (p = 0.78). In addition, the ICC model for the WS measure was high (24%), further supporting the existence of important inter-individual differences among the participants. Similarly, important group differences were found for the Word Structure (WS) subscale of EREL, p < 0.001. As in the case of the WS subscale, important differences were located in the groups of ASD-LI group which scored significantly lower (p < 0.001) than the TD group, and also DLD group scored significantly lower than the TD group, p = 0.02. No important differences were found among ALN and TD groups (p = 0.50), DLD group (p = 0.66), nor ASD-LI group (p = 0.07). Similarly, no important differences were observed between ASD-LI and DLD participants (p = 0.29). Even not all significantly important, differences revealed for all groups, boxplots presented, indicate for different performances between groups. As it concerns the Recalling Sentences (RS or SRT) subscale, important group differences were also found, p < 0.001. Specifically, important differences were found between the ASD-LI group which scored significantly lower (p < 0.01) than the TD group, and also the DLD group  scored significantly lower than the TD group, p < 0.001. Important differences were also found between the ALN and TD groups, p < 0.01., DLD group (p = 0.66), nor ASD-LI group (p = 0.07). However, no important differences were observed between ASD-LI and DLD participants (p = 0.99), ALN and DLD groups (p = 0.97), nor ASD-LI and ALN participants (p = 0.98). The ICC model for the subscale of FS was large enough (37%), further supporting the existence of important inter-individual differences among the participants.This finding is moreover sustained by the ICC model, which declares a high percentage for RS measure (34%) and outbids the existence of important inter-individual differences in groups. Formulating Sentences (FS) EREL measure has also provided important group differences on language domain, p < 0.01. Important differences came up between DLD children, which scored significantly lower (p < 0.01) than TD children. No important differences emerged between ALN and DLD, p = 0.34, or TD group, p = 0.19. Importantly, not an ASD-LI group was formed in this subscale of EREL. WC is a subscale administered only in children between the ages of 9 and 12 years old. None of our participants were found to belong in the ASD-LI group in this age range. Our sample consists of 36 children (from 103) belonging to that age range, of which 19 children are TD participants. The variability of participant’s responses in each group is demonstrated, and it is further supported by a high ICC model for this variable (23%) and indicates important inter-individual differences.The last subscale of EREL measure, Word Classes (WC) also showed important differences between groups, p < 0.001. Specifically, differences are observed in ASD-LI children , who scored significantly worse than TD children , p < 0.001. Likewise, DLD children , also performed worse than TD children on the same task, p < 0.001, and controversially, no significantly different from the ASD-LI group, p = 0.99. No differences were also found in the ALN group , related to the ASD-LI (p = 0.53), DLD (p = 0.30), and TD (p = 0.05) group, respectively. The ICC model for NWR is also high (36%), informing once again for inter-individual differences among participants.Important differences between groups on language domain are also found on the NWR task, p < 0.001. ALN group , the score was significantly lower than TD group , p < 0.001, indicating increased deficits in the communication domain. In addition, the ASD-LI group , also obtained significantly elevated communication deficits in comparison to the TD group of children, p < 0.001. Finally, important differences were found for DLD children , who demonstrate more impairments in communication in comparison to TD children, p < 0.001. No important differences are observed among participants on ASD-LI and DLD groups (p = 0.16), who scored similarly on this subscale. No important differences are also found between ALN and ASD-LI (p = 0.87), or ALN and DLD (p = 0.67) participants.As it concerns the two composite scores of CCC-2 important findings emerged. GCC subscale see  significp < 0.01. ALL children  differ significantly from DLD , p < 0.01, and also TD  children, p = 0.03. No important group differences were found between ASD-LI  and ALN, DLD, or TD groups. DLD group also is not importantly different from the TD group (p = 0.75).SIDC subscale of CCC-2 see , also prRelated to the two composites of CCC-2, the model ICC was significant for the variable GCC (27%), indicating that the General Communication Composite contributes to the group differences, while the SIDC’s contribution is also important, even if not that large (11%). In sum, the ICC model showed that there are important between-group differences, explain a significant proportion of the observed variance .The results from this study are important and thought-provoking. We had investigated a potential relationship between ASD and DLD, and our findings are indicative of its existence. Specifically, we had expected that an ASD-LI subgroup would have derived from the general ASD group, indicating for language impairments within the ASD population, resembling a language profile similar to DLD children. We had also hypothesized that ASD (ASD-LI and ALN) and DLD groups of children would have scored lower than the TD group on language measures, and also that ASD-LI and DLD groups would demonstrate poorer performance than ALN and TD groups on EREL measures. In addition, we have predicted that the ALN group would have scored poorer than the TD group. We also hypothesized that both the ASD-LI and DLD groups would have performed significantly worse on NWR and SRT tasks.Most of these hypotheses have been met. Specifically, as it concerns language tasks, a common profile of ASD and DLD is supported by our results, indicating the presence of a language phenotype in ASD similar to that of DLD. Additionally, ASD-LI and DLD groups scored worse than ALN and TD groups on language measures. However, despite our projections, ALN and TD groups revealed no important differences in language tasks. Controversially, ASD-LI and DLD groups produced significantly more deficits than TD groups. Concerning NWR and SRT tasks, our findings on both tasks showed that ASD-LI so as in the DLD group, produced more deficits than the TD group. Nonetheless, despite our expectations, there were not found any important differences between ALN and ASD-LI or DLD groups, or between ALN and TD groups.Our results are strongly supported by previous studies. Specifically, there is a common profile of ASD and DLD, which indicates a possible common feature between the two developmental disorders, namely, ASD-LI. These findings are in line with previous studies, reporting that a statistically important number of children with ASD, score similarly to DLD children on different language tasks , and alsMoreover, not that surprisingly, ALN and TD groups revealed no important differences on language tasks, providing further support at the assumption of the existence of a subtype inside the ASD population, referred to as the “ASD-LI individuals”. This finding is further supported by De Fossé and colleagues’  study, wIn the majority of language tasks administered, the ASD-LI group scored lower than the DLD group. This finding could be explained by the fact that ASD-LI children except for the language impairment presented, have additional deficits to manage . This complexity of symptoms with additional impairments in different fields constitutes an additional obstacle in their effort for success on different tasks. A special reference is worth making on the RS (SRT) subscale of the EREL instrument. The group differences showed that ASD-LI as well as the DLD group produced more deficits than the TD group. The finding that the clinical groups with LI perform worse than the typical groups is in line with other studies e.g., ,32). Sur. Sur32])Similarly, the NWR task produced important differences among participants in different groups. Both the language-impaired groups demonstrated worse performance than the TD group. The results of the present study are consistent with several previous studies, supporting that children with ASD-LI and those with DLD have similarly poor performance on the NWR task. Evidence supporting NWR deficits in ASD-LI is compelling and the results of this study confirmed previous findings in the area ,18,125.Furthermore, the ICC model for all language tasks showed that there are important between-group differences, explaining a significant proportion of the observed variance. This finding provides additional support to the assumption that DLD and ASD constitute points on a continuum of the same disorder instead of separate conditions . Indeed,Especially, our results support the existence of an intermediate case of shared symptoms, namely ASD-LI, which indicates an important connection between ASD and DLD. Interestingly, a great number of our participants fell in this intermediate category, not only about the language domain. This finding significantly supports the assumption of existing comorbidity between ASD and DLD. Important relations have been also found to exist between the clinical groups, as revealed by the majority of the tasks and measures employed. These relations, further support an overlapping situation between ASD and DLD. For instance, ASD-LI and DLD groups were found to have similar performance in all tasks of the language domain. This finding points to a comorbid relation in linguistics. Our results allow us to argue in favor of ASD and DLD as disorders lying on a continuum of symptoms, supporting the second theory presented in As illustrated in The CCC-2 instrument identifies children with disproportionate pragmatic and social impairments. In this study this assumption is confirmed, as the ASD group of children were more deficit in this composite, proposing increased pragmatic impairments, unrelated to one’s structural language ability. It is of great importance the finding of different impairments characterized by the fundamental deficits presented by each group, based on CCC-2 composites. The DLD group presented deficits on the General Communication Composite (GCC), and fewer deficits on the SIDC subscale confirming DLD’s children diagnosis, and also the ASD group has demonstrated impairments in GCC and SIDC simultaneously, as it is expected for individuals in the autistic spectrum. The results on GCC show that no important differences are observed in the three clinical groups related to their GCC symptoms. This result was expected, as both developmental conditions are proposed to score similarly on GCC (scores below 55), significantly lower than TD groups ,118. TheNevertheless, our results are confirmed from previous studies supporting that the SIDC score is expected to be eight or less in children with ASD ,118. ImpNevertheless, these findings raise questions about the extent to which pragmatic impairments are a secondary consequence of speech and language disorder. For instance, a large proportion of cognitively able children with ASD experience additional language impairments ,126. On It is apparent that language impairment adversely affects social interaction. However, the present data show that some children have pragmatic impairments out of keeping with their structural language skills. This is in line with previous studies showing that children with good structural language can nevertheless have pragmatic difficulties . At a thIt is, finally, important to acknowledge some methodological limitations. Evidence supporting NWR deficits in ASD-LI are numerous and the results of this study are consistent with several previous studies in the area ,18,125. Nevertheless, a study comparing NWR performance in ASD and DLD  includedBias can be introduced at any phase of a research process. We tried to prevent systematic errors and bias during designing, conducting, and reporting the results of our study. However, we believe some selection bias was inserted in the study due to the fact that participants, especially children in pediatric groups, were recruited through a call from speech pathologists and special educators who knew children. This is the first study, to our knowledge, conducted in Cyprus investigating the ASD and DLD population directly. The prevalence of ASD and DLD individuals in Cyprus is still not determined even if Special Education Services needs are elevated. This study succeeded to locate and examine an important number of ASD and DLD individuals all over the country, given the small numbers of the population in Cyprus. This study could be considered as attaining numbers of participants similar to what we could find in an epidemiological study in Cyprus, by addressing these two developmental conditions in a wide range of childhood ages. In addition, our results are also significant, as they confirm the existence of this intermediate set of symptoms that consists of the ASD-LI group, in a different language such as the Greek language. Greek, is a language with significant peculiarities and complexity in expression. The view that this middle ground exists is further reinforced by our data. This category of mixed symptoms deserves to be investigated closely, to obtain optimal results, both in research and clinical practice. The assumption that this intermediate group does, indeed, exist will no longer cause stress to specialists working with clinical groups about what is the most appropriate intervention plan to follow. Instead, they will be provided with the necessary support and guidance to work in the light of this middle cluster of symptoms.To further investigate the existence and relation of the two disorders will provide important and valuable information scientifically and clinically. The need for the development of effective intervention programs for both developmental conditions is highlighted by the specialists of all fields working with these populations, as the number of the affected children increases daily.In conclusion, our results further support the assumption of common symptomatology of the two disorders and are in line with the suggestion of moving beyond the “labels” and start subgrouping individuals in response to their characteristics, instead of trying to detect the symptoms following an already given diagnosis. The apparent need to divide the ASD group into two different categories based on the divergence of symptoms presented, namely ASD children with additional language impairment and ASD children without, is an indicative starting point of the need to change our perspectives and methodologies. Beyond that, if we accept that this category exists, it is important to provide answers to consequent questions. For instance, at what point in the continuum can we place this “shared” category of social symptoms? Can anyone argue that it is placed exactly in the middle of the two predominant disorders? Is it possibly closer to autism disorder, or perhaps to language disorder? With all this in mind, unquestionably, the research community has still a lot to discover and many challenges to overcome concerning this particular category.


Objective: The gut microecosystem is the largest microecosystem in the human body and has been proven to be linked to neurological diseases. The main objective of this study was to characterize the fecal microbiome, investigate the differences between epilepsy patients and healthy controls, and evaluate the potential efficacy of the fecal microbiome as a diagnostic tool for epilepsy.Design: We collected 74 fecal samples from epilepsy patients  and healthy controls  in the First Affiliated Hospital of Zhengzhou University and subjected the samples to 16S rRNA MiSeq sequencing and analysis. We set up a train set and a test set, identified the optimal microbial markers for epilepsy after characterizing the gut microbiome in the former and built a diagnostic model, then validated it in the validation group.Results: There were significant differences in microbial communities between the two groups. The α-diversity of the HCs was higher than that of the epilepsy group, but the Venn diagram showed that there were more unique operational taxonomic unit (OTU) in the epilepsy group. At the phylum level, Proteobacteria and Actinobacteriota increased significantly in Eps, while the relative abundance of Bacteroidota increased in HCs. Compared with HCs, Eps were enriched in 23 genera, including Faecalibacterium, Escherichia-Shigella, Subdoligranulum and Enterobacteriaceae-unclassified. In contrast, 59 genera including Bacteroides, Megamonas, Prevotella, Lachnospiraceae-unclassified and Blautia increased in the HCs. In Spearman correlation analysis, age, WBC, RBC, PLT, ALB, CREA, TBIL, Hb and Urea were positively correlated with most of the different OTUs. Seizure-type, course and frequency are negatively correlated with most of the different OTUs. In addition, twenty-two optimal microbial markers were identified by a fivefold cross-validation of the random forest model. In the established train set and test set, the area under the curve was 0.9771 and 0.993, respectively.Conclusion: Our study was the first to characterize the gut microbiome of Eps and HCs in central China and demonstrate the potential efficacy of microbial markers as a noninvasive biological diagnostic tool for epilepsy. The fecal microflora, as a major component of the gut microecosystem, plays an important role in human health and diseases and is also a significant regulator of environmental factors affecting host disease risk. The gut microbiome is closely related to and interacts with various organs and systems of the human body, including the brain, lungs, liver, bones, and cardiovascular system . As sequEpilepsy is a chronic neurological disease characterized by recurrent seizures. Epidemiological statistics have indicated that more than 50 million people worldwide suffer from this disease , which iIn recent years, with the development of sequencing technology, the relationships between the composition, function and metabolic potential of the microbiome and diseases have been extensively studied. The diagnostic potential of the gut microbiome for a variety of neurodevelopmental, neuropsychiatric, and neurodegenerative diseases has been confirmed by compelling studies, but only a few studies have highlighted the distinctions between the fecal microbiota in Eps and HCs, finding that the intestinal microbiota may play an important role in epileptic seizures and thus may represent a new target for drug therapy or a biomarker , the diaThe study was designed and performed in accordance with the PRoBE  design, the Helsinki Declaration, and the Rules of Good Clinical Practice . Before A total of 24 patients with epilepsy from the outpatient department of the First Affiliated Hospital of Zhengzhou University were enrolled from June 2019 to October 2019, and fecal samples were collected prospectively. Patients were included if they met the following criteria: (1) met the 2005 ILAE criteria for epilepsy; (2) had at least one epileptic seizure without a fixed cause; (3) had a tendency toward recurrent attacks; and (4) were first diagnosed as having epilepsy. Participants with the following conditions were excluded: (1) other neurological conditions similar to epilepsy; (2) use of antibiotics or probiotics in the past 3 months; and (3) a known history of chronic illness; (4) pregnant and lactating women.Fifty HCs from the physical examination department of the First Affiliated Hospital of Zhengzhou University were also enrolled in this study. Inclusion criteria: (1) good physical condition, no special discomfort symptoms compared with usual; (2) mentally normal, with normal expression ability; (3) volunteer to participate in this study; Exclusion criteria: (1) complicated with malignant tumors, serious cardiovascular and cerebrovascular diseases, infectious diseases and other mental and nervous system diseases; (2) younger than 18 years of age or older than 80 years of age; (3) pregnant and lactating women; (4) lack of relevant clinical information; (5) use of antibiotics or probiotics in the past 3 months. Clinical information including gender, age, seizure frequency, seizure types and clinical features was registered prospectively. Fecal samples were prospectively collected from the enrolled participants and subjected to 16S rRNA MiSeq sequencing.Fresh stool samples were collected from all participants. Each stool sample was subjected to routine testing to assess stool consistency . The samPRJNA 701117.Extracted DNA was amplified with PCR in a 20-μL reaction system. The V3-V4 hypervariable region of 16S rRNA was targeted by the forward primer 5′-CCTACGGGNGGCWGCAG-3′ and reverse primer 5′-GACTACHVGGGTATCTAATCC-3′. PCR was conducted in an ABI Gene AmpR 9700 system . Specifically, PCR included 2 min at 95°C followed by 30 cycles of denaturation (95°C for 30 s), annealing (55°C for 30 s), and extension (72°C for 30 s) and a final extension at 72°C for 5 min . Samples1) to match the operational classification units (OTUs).The filtered reads were distributed to different samples based on specific barcodes, and then the barcodes and primers were removed. The paired-end sequenced reads of each library were overlapped with the default parameters using FLASH v. 1.2.10 . The comEqual numbers of reads were randomly selected from all the samples; among them, a large number of sequences and singletons were sifted out. The unique sequences were clustered into OTUs by using the “usearch-CLUster-otus” command, the selected sequence was compared with the OTU sequences by using the “usearch-usearch-global-ID 0.97” command, and the identity threshold was set to 0.97. Then, the OTU composition table was created . After t2, is functionally similar to NMDS analysis. Unifrac uses phylogenetic information to assess community differences between samples. Weighted unifrac takes the abundance of sequences into account, whereas unweighted unifrac does not. The Wilcoxon rank-sum test R function was used for statistical comparisons of the two groups. Dominant species heat map was plotted with Heat map Builder. Microbial community bar plots were generated by species composition analysis. We compared the sequences with MUSCLE and used Fast Tree MP to generate an unrooted phylogenetic tree with a generalized time-reversible (gtr) model. The phylogenetic tree was rerooted by using a custom Perl script furnished by Microbes Online (reroot.pl)3.A rarefaction curve was plotted to compare microbial community richness among the samples and validate the sequencing data. Similarly, a Shannon–Wiener curve and rank-abundance curve were used to verify the data quality of the samples. The Venn program was used to identify the overlap and uniqueness of OTUs in the two groups. The within-sample diversity  was calculated by the Chao1 index, ACE index, Shannon index and Simpson index using the R program package ‘vegan.’ Distance matrices  were obtained by both the weighted and unweighted unifrac distance metrics and visualized by PCoA. PCoA, which was conducted in RBacterial classification, analysis and comparison were conducted between the EP group and the HC group at the phylum, class, order, family and genus levels. The bacterial compositions in individual samples and the two groups were both plotted. The Wilcoxon rank-sum test was also used to compare the epilepsy group and the HC group. LDA was conducted using the LEfSe method to characterize the fecal microbiomes. The LEfSe method combined both statistical significance  and LDA to measure the magnitude of differentiation between groups. The threshold LDA score for discriminative features was 3.0 [(log10) = 3]. The LEfSe method and LDA were used to characterize the fecal microbiota, and LDA was used to screen key microbial markers.Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was used to predict the metabolic functions of the bacterial flora and 16S rRNA gene sequences in the KEGG, COG, and Rfam databases. Data were then entered into the HUMAnN to find significant differences in KEGG ortholog (KO) abundances. This approach predicts the metabolic functions of bacteria and ancient bacteria by comparing the 16S rRNA gene sequencing data against a reference database of microbial genomes with known metabolic functions.The annotation information corresponding to each functional spectrum database per sample and the abundance matrix for the predicted functional groups may be obtained from the prediction results of PICRUSt. Relative differences in 16S rRNA gene copy number among species were considered during the prediction process. The original species abundance data were corrected to enhance prediction accuracy and reliability . The bioA random forest model was used to select significantly different OTUs in each sample group. The generalization error was estimated by a fivefold cross-validation. An OTU frequency profile was generated by mapping reads from the Eps and HC groups onto these represented sequences . A crossP < 0.05)  . The POD < 0.05) .SPSS v. 20.0  was used to process the data. The statistical significance of the differences between groups was calculated. Wilcoxon rank-sum tests were conducted to compare the continuous variables between groups. Fisher’s exact test was used to compare categorical variables between groups. Spearman’s rank test was used for the correlation analysis.After rigorous screening and exclusion, a total of 74 participants were enrolled, including 24 Eps and 50 HCs. The process and flow chart are shown in P < 0.01; The rank-abundance curve and Shannon–Wiener curve showed species diversity in epilepsy group and HC group. The curve was smooth and the species uniformity was good. However, the rarefaction curve and the species accumulation (Specaccum) curve showed that the sample size of the epilepsy group was small, and it was better to increase the sample size for more complete studies . We measR = 0.526 and P = 1e-04, so the difference between the two groups was statistically significant. The microbial community heat map  were separated along the NMDS2 axis , indicatheat map  showed tq values were calculated for P . However, the relative abundance of Bacteroidota in the HCs was higher than that in the Eps, while those of the Proteobacteria and Actinobacteriota in the Eps was higher than those in the HCs . Biomarker names, LDA scores, log values and P-values are shown in Linear discriminant analysis effect size analysis  and the c-Actinobacteria, c-Gammaproteobacteria, o-Bifidobacteriales, o-Clostridia-unclassified and f-Bifidobacteriaceae had obvious advantages, while in the healthy group, microbes such as c-Coriobacteriia, o-Bacteroidales and f-Rikenellaceae had obvious advantages. The LDA score in Escherichia-Shigella, Enterobacteriaceae-unclassified, Halomonas, and Bifidobacterium, predominated in Eps, whereas 36 genera, including Lachnospiraceae-unclassified, Bacteroides, Blautia and Lachnospira, predominated in HCs .In the cladogram  drawn byn = 24) and HCs (n = 50) . Twenty-six pathways, including oxidative-phosphorylation, drug-metabolism-other-enzymes, systemic-lupus-erythematosus, and beta-alanine-metabolism, were enriched in Eps .To elucidate the functional and metabolic alterations of the intestinal microbiomes between the Eps and HC groups, metagenomes were next inferred from the 16S rRNA data, and the functional potential of the gut microbiota was analyzed. LEfSe analysis was used to identify the differential abundant KEGG pathways between the Eps ((n = 50) . At leveP < 0.05 as the criteria for correlation. Seven of the clinical indicators had higher correlations with OTUs: Seizure-type, course and frequency are strongly correlated with all 38 OTUs, and negatively correlated with the same 31 OTUs, but positively correlated with the remaining seven OTUs. In addition, age, ALB, TBIL, Hb, and Urea were only positively correlated with part of OTUs. WBC, RBC, PLT, and CREA were positively correlated with some OTUs and negatively correlated with some OTUs. Interestingly, their related OTUs overlapped. And their negative correlation OTUs is the positive correlation OTUs of seizure-type, course and frequency. OTU69 (Blautia), OTU72 (Lachnospiraceae-unclassified), OTU98 (Lachnospiraceae-unclassified), and OTU322 (Blautia) are strongly correlated with more than half of the clinical indicators and may be the focus of research , OTU117 (Parabacteroides), OTU3 , OTU45 (Lachnospiraceae-unclassified), OTU322 (Blautia) and OTU35 (Collinsella), etc. (P < 0.0001) (P < 0.001) , etc. . The meaa), etc. . The PODa), etc. . The ROC 0.0001) . For the< 0.001) . These dEpilepsy is a complex condition with multiple risk factors and strong genetic predisposition, and more than 75% of people with active epilepsy go untreated in low- and middle-income countries, constituting a major treatment gap . EpilepsFirmicutes and Proteobacteria increased, while those of Bacteroidetes and Actinobacteria decreased. Most of the results of our study confirm those in previous reports, but there are some new findings that show some differences and advantages compared with the results of other similar studies. At the phylum level, compared to those in HCs, Proteobacteria and Actinobacteriota in the Eps were significantly increased, while Bacteroidota abundance was significantly increased in HCs. Twenty-three genera were enriched in the Eps while fifty-nine genera were increased in the HCs. We identified 22 microbial markers for the diagnosis of epilepsy. Moreover, the POD values indicated that the incidence in the epilepsy group significantly increased. The AUC for the training set reached 0.9771, and the AUC for the test set reached 0.993.To date, there have been only a few reports on epilepsy and intestinal microecology. Among these studies, The differences in our study compared with others can be attributed to regional differences. Regional differences are the main factors affecting intestinal microecology, and the results may vary with different patients from different areas. In addition, the small sample size may also have a certain impact, and more trials are necessary. Exogenous factors can affect intestinal microbiome to increase seizures, such as diet, infection  and antiBy participating in the physiology and pathology of cellular organisms, microbiome exerts certain influence on disease and health. In terms of the nervous system, several studies have demonstrated the importance of the gut microbiome. In particular, the microbiota–gut–brain axis is proposed to link the microbiome with the intestine and brain as a whole, and explore the possible mechanisms and pathways. This two-way communication signal transmission mechanism is complex, including neural, endocrine, immune and metabolic pathways . Ma et aProteobacteria and Actinobacteriota were significantly increased in the Eps, while Bacteroidota abundance was significantly increased in HCs. These results are convenient for diagnosis of epilepsy and targeted treatment of patients with epilepsy. However, our experiment also had some shortcomings. The sample size was insufficient. The only thing we can do is expand the sample size and try to improve the standardization of the sampling procedure to minimize the influence of other interference factors. Therefore, a more systematic study should be conducted on a large random sample of individuals from different regions and with different eating habits, genders and ages. Moreover, individual microbiology is associated with many confounding factors, such as time, diet, and the environment. This has been shown in multiple studies .The raw Illumina read data for all samples were deposited in the European Bioinformatics Institute European Nucleotide Archive database . Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.YJ and YL designed the study. GC, ZL, YC, TW, JL, HW, YZ, and YS collected clinical samples. SL and BR extracted the bacterial DNA. ZR and SL completed data analysis. SL and GC wrote the manuscript. All authors reviewed and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Whether smoking is related to a decreased risk of meningioma in women is still controversial. We conducted a systematic review and meta-analysis examining the association between smoking and risk of meningiomas in women.Two authors independently performed a systematic literature review in the PubMed, Cochrane Library, and EMBASE databases. We identified case-control and cohort studies quantifying associations between smoking and risk of meningioma in women. A meta-analysis by pooling studies was performed according to the multivariate-adjusted risk estimates and 95% confidence intervals (CIs) preferentially. We further conducted additional subgroup and sensitivity analyses to explore possible explanations of the results.A total of seven observational studies were included, with a total of 2132 female patients diagnosed with meningiomas. Ever smoking was associated with a significantly reduced risk of meningioma in women, with pooled odds ratio (OR) of 0.83 (95% CI 0.70–0.98). Similar findings were noted for current  and past  smokers. However, considering the areas, the OR of ever smoking was 0.77 (95% CI 0.68–0.87) in three American studies, but 0.99 (95% CI 0.73–1.35) in four studies conducted in other countries.Based on limited epidemiological evidence, a decreased risk of meningioma in women smokers was only observed in American studies rather than studies conducted in other countries. Meningiomas are suggested to be among the most common primitive tumors of the central nervous system and account for about a third of all intracranial tumors –3. AlthoIt is now well established from a variety of studies, that smoking is associated with a wide range of tumors, including lung cancer, liver cancer, ovarian cancer, prostate cancer, and others –12. To dIt is interesting to note that women smokers in American studies tended to had a significantly decreased risk of meningioma [13 17], whereas women smokers in studies conducted in other countries showed no significantly decreased risk of meningioma [14 15 21]. Therefore, whether the association between smoking and risk of meningioma in women differs across countries is still poorly understood. To the best of our knowledge, no formal systematic review and meta-analysis based on the existing epidemiological data is available regarding the association between smoking and meningioma in women in different countries. To address this research gap, based on the updated epidemiological data, we performed a formal systematic review and meta-analysis of smoking in relation to risk of meningioma in women, with a special focus on the difference of relationship in different countries.The meta-analysis was carried out following the guidelines from the Meta-analysis of Observational Studies in Epidemiology Group . In DeceTwo literature reviewers (PZ and TC) evaluated studies independently for possible inclusion and resolved any discrepancies by discussion. The following inclusion criteria were applied: (1) used a cohort or case-control study design; (2) availability of a quantitative estimate of the associations between smoking and risk of meningiomas; (3) provided the relative risk (RR) or odds ratio (OR) with confidence intervals (CIs); (4) availability of at least one of the following smoking exposure variables: never versus ever, past, current, or passive smoking; (5) could get raw data of female population; (6) when multiple reports were based on the same target population, the most informative one was included in this meta-analysis.Titles and/or abstracts of reviews were screened independently by two reviewers to identify publications that potentially meet the inclusion criteria outlined above. No study will be excluded a priori for the weakness of design or data quality. The full texts of all the retained original articles were retrieved. A standardized form was used to extract data from each identified publication. Relevant information included: study name; authors; country; period of publication; gender; sample sizes ; study design; variables of adjustment; availability of data on smoking; risk estimates (RRs or ORs) and their corresponding 95% CIs.X2-based Q statistical test and the I2 test. Heterogeneity was considered significant when I2 > 50% and P < 0.1. When no heterogeneity was presented, the results from single comparisons were combined using a fixed-effect model with the Mantel-Haenszel method. Otherwise, the random-effect model with the DerSimonian-Laird method was applied for pooling.All statistical analyses were used by STATA 12 . The multivariate-adjusted risk estimates and 95% CIs were used to estimate the pooled risk of smoking in meningioma development. For case-control studies, the OR was used as estimates of the RR because meningioma is sufficiently rare. When cohort studies reported only crude data and no information on person-years, we treated it as a control study using noncases as controls. The potential heterogeneity between publications was assessed by P < 0.05 was considered indicative of significant publication bias. All P values were two-sided.For the reason that the characteristics of target populations, study location, study designs, assessments of smoking, and adjustments for confounding factors were not consistent among studies, we further conducted additional subgroup and sensitivity analyses to explore possible explanations of heterogeneity and to assess the potential impact modification of these variables on outcomes. We also analyzed the effect of a single study on the overall risk estimate by omitting one study in each turn. Due to rather small numbers of studies for other outcomes, the sensitivity analysis was performed only for “ever versus never smoking”. The presence of publication bias will be assessed by applying the tests proposed by Begg’s and Egger’s tests. n=768), EMBASE (n=1710), and Cochrane Library databases (n=0). Most of these articles were not focused on the topic, and were no longer considered, whereas 34 unique publications were selected for full-text review. A total of 21 articles were excluded because of not present raw data for OR/RR (n=4), article type with review or case report (n=2), not availability of smoking exposure (n=2), and no quantitative estimating of association between smoking and risk of meningioma (n=13). Then, 13 publications were retained for the review. One article [Figure  article  was exclEMBASE n=10, and C article , 24–26.  article –17, 21.Table P for heterogeneity, 0.362). Among four studies conducted in other countries, the pooled OR was 0.99 . Overall, the OR was 0.83 .Figure P for heterogeneity, 0.229) for total studies  for total studies .Table Sensitivity analyses showed that the exclusion of five single studies could materially alter the overall combined risk estimate, with a narrow range from 0.83 (95% CI: 0.66–1.04) to 0.86 (95% CI: 0.73–1.02). However, exclusion of a single study  conducteP=0.565) and Begg’s (P= 0.368) tests confirmed no evidence of publication bias.Figure In the present meta-analysis, we reviewed and summarized the extensive but controversial evidence on the association between smoking and meningioma in women. We found that ever smoking was associated with a significantly reduced risk of meningioma in women. Similar findings were noted for current and past smokers. Importantly, a decreased risk of meningioma in women smokers was only observed in American studies rather than studies conducted in other countries according to the results of subgroup analyses. However, these findings were based on limited epidemiological evidence, including seven studies with 2132 female meningioma cases that provided risk estimates for smoking.The possible role of smoking in the development of meningioma in women is still unclear. It is widely recognized that meningioma is a hormone-sensitive tumor at a population level, with approximately 30% of meningioma expressing estrogen receptors and approximately 70% expressing progesterone receptors . An assoOur results are in accord with a previous meta-analysis which indicated that a statistically significant negative association between ever smoking and meningioma in women is found . HoweverDespite the intriguing findings of our study, several important limitations should be considered. Firstly, the major limitation of this study is the small number of studies: only seven studies were included in our meta-analysis of meningioma risk associated with ever versus never smoking. Meanwhile, only three studies were included to analyze the association between past or current smoking and risk of meningioma in women. Secondly, meningiomas are rare and most patients are asymptomatic, making it difficult to get high-quality information in epidemiological research. In our study, only one prospective cohort study was included, and most of the information on this topic came from case-control studies, which may be affected by various sources of bias. Furthermore, as the current studies use different assessment instruments (interview or mailed questionnaires) to assess the participants’ smoking status, the possibility of mis-reporting of cigarette smoking by study participants may exist. With different methods, the study participants may have different attitudes, which could affect the accuracy of the data collection. However, subgroup analyses based on the different study design and the different assessment instruments got consistent results. Thirdly, considering the multivariate adjusted OR values reported in the literature are the most precise risk estimates, these values were used in our meta-analysis preferably. However, not all included studies in this meta-analysis reported the multivariate adjusted OR. In fact, the variables of adjustment in current studies are inconsistent. Unfortunately, when the data were restricted to studies that reported adjusted OR, it resulted in a null association between the two. Therefore, evidence for an apparent protective effect of ever smoking on risk for meningioma in women is still weak.In conclusion, based on limited epidemiological evidence, ever smoking (including past or current smoking) is related to a decreased risk of meningioma in women. Importantly, a decreased risk of meningioma in women smokers was only observed in American studies rather than studies conducted in other countries according to the results of subgroup analyses. Thus, we infer that smoking behaviors differ across socioeconomic development levels and race may be the explanations of the inconsistent results in different studies. However, the evidence for this protective effect of smoking on risk for meningioma in women is still weak, particularly when the data are restricted to studies reported adjusted OR, which resulted in a null association between the two. Therefore, there remains a need for further prospective cohort studies including adequate numbers of cases that can more clearly evaluate the temporal relationship between smoking and risk of meningioma in women.