Coxiella burnetii polymerase chain reaction (PCR) detection at the ARC-OVR.Q fever and toxoplasmosis are economically important zoonoses as they cause considerable losses in livestock  and wildlife  through reproductive disorders such as abortions and stillbirths. Q fever and toxoplasmosis testing in South Africa is conducted by the Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR). However, both zoonoses are understudied and not monitored in South Africa as they are not considered controlled or notifiable diseases in the Animal Disease Act 35 of 1984. A retrospective study was conducted on Q fever (2007–2009) and toxoplasmosis (2007–2017) using diagnostic laboratory data at the ARC-OVR. Also, we report on sporadic abortion and stillbirth cases in livestock from diagnostic tissue samples submitted for C. burnetii antibodies and seropositivity was 0.9% (95%CI: 0.3–1.7) with sheep  having the highest seropositivity followed by cattle , while all goats  and wildlife  tested were negative. From 2007 to 2017, 567 sera were tested for T. gondii antibodies; overall seropositivity was 12.2% (95%CI: 9.6–15). Wildlife had highest seropositivity to T. gondii antibodies  followed by goats  and sheep  while seropositivity in cattle was 2.4% (95%CI: 0.06–12.9). Of 11 animals tested by C. burnetii PCR detection (2021–2022), 10 (91.0%) were positive. The amplicon sequences showed similarity to Coxiella burnetii strain 54T1 transposase gene partial coding sequence.During 2007 to 2009, 766 animal samples were tested for We have confirmed the occurrence of the causative agents of Q fever and toxoplasmosis in livestock and wildlife in South Africa, with data limitations. These zoonoses remain of importance with limited information about them in South Africa. This study provides baseline information for future studies on Q fever and toxoplasmosis in South African livestock and wildlife, as well other African countries. Due to limited data collection experienced in this study, it is recommended that improvements in data collection samples tested should include associated factors such as sex, age, and breed of the animals. Coxiella burnetii [C. burnetii are cattle, sheep, and goats, while the bacterium can also infect rodents, cats, dogs, and arthropods [Q fever is distributed worldwide except in New Zealand and is caused by burnetii . Q feverburnetii . For insburnetii . The mosthropods . The mosthropods , indirecthropods . Previouthropods .T. gondii infections caused US $ 5–15 million losses annually [Toxoplasma gondii, the causative agent of toxoplasmosis, infects a wide range of warm-blooded animals, including livestock and wildlife. Infections by the protozoan cause congenital abnormalities, late abortions and fetal death in livestock after several replication cycles of the tachyzoites [Like Q fever, prevalence of toxoplasmosis in livestock and wildlife is important because the disease is considered a public health risk in humans from consumption of raw milk and improperly cooked meat from infected animals, also causing significant economic losses , 8. In Bannually . Toxoplahyzoites .Previously, toxoplasmosis diagnosis was mainly based on bioassays and microscopy, but these methods lacked sensitivity and were considered laborious and time-consuming . The SabC. burnetii (2007–2009) and T. gondii antibodies (2007–2017) in various provinces of South Africa by analyzing and reporting on Q fever and toxoplasmosis serological data in the ARC-OVR database. The study also reported on factors associated with seropositivity, such as the origin of samples, species and year of testing. We also analyzed diagnostic tissue samples submitted for C. burnetii PCR detection for possible sporadic abortion and stillbirth cases in livestock caused by C. burnetii infections.In South Africa, various laboratories, including the Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR), are designated facilities for serological testing of both Q fever and toxoplasmosis and consequently keep records. However, currently, both Q fever and toxoplasmosis are not regularly monitored. This is because both Q fever and toxoplasmosis are not recognized as controlled or notifiable diseases in the Animal Diseases Act of 1984 (ACT 35 1984) and the Animal Diseases Regulations; R.2026 of 1986 Government in Gazette No. 10469 of 26 September 1986 This is dC. burnetii antibodies, between 2007 and 2009, 766 sera were tested using CFT  and 2007 (21.6%), as demonstrated in Table For seropositivity to CFT Fig. . Most ofnd 2007 2.6%, as dC. burnetii PCR was the Eastern Cape (4/11), followed by Gauteng and North West Provinces (2/11) as shown in Table C. burnetii positivity by PCR (8/11) while cattle accounted for the rest. Most of the animals tested were due to abortions (9/11) while 2/11 were because of stillbirths  for testing by 1 animalsC. burnetii antibodies among species (p = 0.22) and provinces (p = 0.39), while the differences were substantial between years of testing (p = 0.001), being highest in 2007 (Table T. gondii antibodies and years of testing (p = 0.13), while there were significant differences between provinces (p < 0.001), with the highest odds of seropositivity in Limpopo, Western Cape and Free State (Table T. gondii antibodies was significantly higher in goats (p = 0.01) and sheep (p = 0.04).There were no significant differences in seropositivity to es p = 0.2 and proes p = 0.9, while C. burnetii by IS1111 PCR showed that samples from 10/11 animals were positive   in goat abortion material, cattle and sheep (21.3%), in Iran, which is consistent with observations in the current study of the samples that tested positive by Coxiella IS1111 PCR. Most tissues tested in the study were from goats and sheep as compared to cattle and mainly due to abortion cases as compared to cattle which were stillbirth cases. This finding may suggest that C. burnetii infections may be responsible for abortion cases in small ruminants such as goats and sheep as compared to cattle as previously observed by [. burnetii infections. This is because state authorities usually focus on controlled diseases like brucellosis and chlamydiosis in cases of abortions, until recently where samples from some abortion cases are also submitted for C. burnetii PCR detection with positive results. This may reflect that although Q fever is not yet considered a notifiable or controlled disease in South Africa, there is progress in the knowledge of the disease. However, more studies need to be conducted. Although this was a national study from all nine provinces of South Africa, it is based on unrelated past and current data and the total number of animals is limited, which is one of the limitations of the study.In the study, we detected Cllbirths  and may study by  also repnstance,  reportedoreover,  also reperved by  in the FC. burnetii PCR detection because animals were showing clinical symptoms such as abortions or stillbirths. Thus, C. burnetii PCR detection frequencies in the current study do not reflect the true prevalence of the disease in the country; however, it confirms the existence of C. burnetii infections specifically in areas where this is the first report on the bacterium. This will pave the way for future in-depth epidemiological studies.The study demonstrated the presence of the causative agents of both Q fever and toxoplasmosis in South Africa, laying a foundation for more studies on these zoonoses. Q fever and toxoplasmosis are important and should be regularly monitored. Proper record-keeping in various laboratories should be practised, and the records should be readily accessible. Diagnostic tissue samples were submitted for C. burnetii and T. gondii antibodies and also to investigate sporadic abortion and stillbirth cases in livestock caused by C. burnetii using tissue samples submitted for C. burnetii PCR detection. Q fever and toxoplasmosis DLD were obtained from the ARC-OVR Bacterial Serology and Epidemiology, Parasites, and Vectors (EPV) laboratories, respectively. Animal samples tested included cattle, sheep, goats, and dogs. Antelope, giraffe, lion, and cheetah serum samples were grouped and referred to as wildlife. Due to low numbers, pigs (10), dogs (2), cats (1), and horses (1) were grouped together and collectively referred to as other species. Diagnostic tissue samples submitted for C. burnetii PCR detection were obtained from the Bacterial PCR laboratory at the ARC-OVR and analyzed for their places of origin, species, and tissues submitted as well as the reason(s) for testing  from the ARC-OVR database of samples tested for seropositivity to rs, pigs 0, dogs . These samples were composed of tissues from different species and provinces of South Africa and submitted for various reasons such as stillbirth and abortion cases, as described in Table For PCR detection of C. burnetii antibodies. This method also has relative Se of 26.56% and Sp of 99.97% relative to ELISA in cattle [T. gondii Antibodies [T. gondii antibodies while a brown homogenous suspension showed a negative result [Complement fixation test (CFT), which has relative sensitivity (Se) of 99.96% in cattle and specificity (Sp) of 99.94% relative to ELISA in ruminants, was used to test for n cattle . Card agtibodies . This tee result .The data were collected and filtered using Microsoft Excel version 2016 and analyzed using Stata 15 . We assessed univariate associations of species, province of origin and year of sampling with Q fever and toxoplasmosis seropositivity using a two-tailed Fisher’s exact test. The same three variables were then included in multiple logistic regression models to adjust for confounding; however, multivariable analysis was not possible for Q fever seropositivity due to extensive collinearity. Model fit was assessed using the Hosmer–Lemeshow goodness-of-fit test.PCR confirmation was conducted for all diagnostic tissue samples from 11 animals. The diagnostic tissue samples consisted of various tissue specimens from different species originating from other provinces of South Africa, as shown in Table C. burnetii in tissues  was conducted in a 50 µL reaction targeting the multi-copy transposase gene in insertion element; IS1111 using primers 5’CGCAGCACGTCAAACCG3’ and 5’TATCTTTAACAGCGCTTGAACGTC3’ [Coxiella gene fragment (gblock) from Integrated DNA Technologies  was used as template positive control while distilled water used as template negative control in the reaction. The reaction mixture contained 400 nM of each primer (IS1111F and IS1111R), 25 µL of the Amplicon 2 × Taq DNA polymerase Master Mix Red , and 10 µL of the extracted DNA. PCR amplification was conducted using BIO-RAD T100™ thermal cycler . Cycling conditions consisted of initial denaturation at 95 °C for 15 min, 35 cycles of denaturation at 95 °C for 30 s, annealing at 60 °C for 30 s, and extension at 72 °C for 60 s for 35 cycles. The final extension was carried out at 72 °C for 10 min, and amplicons were visualized on a 1.5% w/v ethidium bromide-stained agarose gel with an expected size of 146 bp [PCR for detection of AACGTC3’ , 30. Thef 146 bp  estimate1111 PCR products of the 16 tissues were sent to Inqaba Biotechnical Industries (Pty) Ltd  for sequencing by Sanger. Both reverse and forward PCR primers were also used as sequencing primers Sequences were manually edited using the BioEdit Sequence alignment editor (version 7.2.5) and analyzed using the BLAST search online tool (http://www.ncbi.nlm.nih.gov/blast).PCR confirmation of 16 tissues from 10/11 animals; 2271(a), 2271(b), 5030, 5269, 12,072(a), 12,072(b), 4243, 4322(a), 4322(b), 4322(c), 4460(a), 4460(b), 6450, 6451(a), 6451(b) and 2208 was conducted using Sanger sequencing. The ISFactors such as the age of animals, sex, and breed could not be determined as this information was also missing from the databases and sample submission forms.C. burnetii and histopathological changes. This is because clients only submitted tissues for PCR detection of C. burnetii, and only pathogen DNA and not the disease was detected. However we confirmed the bacterium by sequencing. Some of the tissues are the ones that tested negative for other abortifacient pathogens such as brucellosis and Chlamydiosis.We did not investigate subclinical infections of C. burnetii detection and confirmation by sequencing.We did not rule out co-infections because we did not investigate or confirm the cause of abortions, only focusing on C. burnetii and T. gondii antibodies.Information about the reasons for submission of the animal samples for testing was not available in the database, and sample submission forms resulted in difficulties in establishing whether sampling was random or biased. This is because animal samples can be submitted for testing for various purposes such as symptoms, export, import, diagnostic, and screening, resulting in sample bias which would not be considered representative samples. Therefore, the results do not reflect true seropositivity to


Glioblastomas are resistant to treatments targeting angiogenic blood vessel development. It is possible that glioblastoma cells are forming vessel-like structures, called vasculogenic mimicry (VM), and contributing to treatment resistance through this process. We aimed to quantify VM in primary and recurrent glioblastoma and to determine whether VM vessels express the pathological vessel marker prostate-specific membrane antigen (PSMA). We found that only a small proportion of vessels in glioblastoma were VM, and that these vessels did not express PSMA. However, the expression of PSMA was decreased in recurrent compared to primary tumours, as was the total vessel density. The potential of VM as a treatment target and its contribution to treatment resistance in glioblastoma require further investigation.p < 0.001). PSMA was expressed by endothelial vessels, and its expression was also decreased in recurrent tumours (p = 0.027). VM was observed in 42.86% of primary tumours and 28.57% of recurrent tumours. VM accounted for only a small proportion of the tumour vasculature and VM density did not differ between primary and recurrent tumours (p = 0.266). The functional contribution of VM and its potential as a treatment target in glioblastoma require further investigation.Vasculogenic mimicry (VM), the ability of tumour cells to form functional microvasculature without an endothelial lining, may contribute to anti-angiogenic treatment resistance in glioblastoma. We aimed to assess the extent of VM formation in primary and recurrent glioblastomas and to determine whether VM vessels also express prostate-specific membrane antigen (PSMA), a pathological vessel marker. Formalin-fixed paraffin-embedded tissue from 35 matched pairs of primary and recurrent glioblastoma was immunohistochemically labelled for PSMA and CD34 and stained with periodic acid–Schiff (PAS). Vascular structures were categorised as endothelial vessels (CD34+/PAS+) or VM (CD34−/PAS+). Most blood vessels in both primary and recurrent tumours were endothelial vessels, and these significantly decreased in recurrent tumours ( Glioblastoma is the most commonly occurring adult primary malignant brain tumour .Despite an aggressive standard treatment approach of maximal safe surgical resection, radiation therapy, and temozolomide (TMZ) chemotherapy, the median survival time for glioblastoma is poor at 14.6 months . AdditioVasculogenic mimicry (VM) is the formation of a functional vascular network by tumour cells . VM was Prostate-specific membrane antigen (PSMA) is a transmembrane glycoprotein expressed in the normal prostatic epithelium, renal tubules, and small intestine ,16. It iSince the extent to which VM occurs in recurrent glioblastoma has not previously been studied, we aimed to determine whether VM vessels were present in recurrent tumours and whether VM density differed between primary and recurrent glioblastoma. We also aimed to assess whether PSMA expression occurred in both angiogenic and VM vessels. This study was approved by the Human Research Ethics Committee of the University of Newcastle (H-2018-0007). Formalin-fixed paraffin-embedded (FFPE) tumour tissue from 35 cases of glioblastoma with matched primary and recurrent tumour tissue was sourced from the Mark Hughes Foundation Brain Cancer Biobank facilitated by the NSW Regional Biospecimen Services (The University of Newcastle). Glioblastoma was diagnosed histologically at the time of primary tumour resection by a Hunter Area Health Service pathologist according to either the 2007 or 2016 World Health Organisation Classification of Tumours of the Central Nervous System criteria. Clinical information available for the cohort included median age at diagnosis (years), patient sex, treatment after primary resection, IDH1 mutation status, MGMT promoter methylation status, recurrent tissue collection timepoint, and median overall survival (days) .® image analysis platform  for analysis.FFPE tissue was sliced into 4 µm sections and processed by the NSW Regional Biospecimen Services for automated IHC using the Ventana Discovery Ultra Staining System . Sections were labelled using pre-diluted rabbit monoclonal PSMA  and mouse monoclonal CD34  as the primary antibodies. Slides were loaded into the instrument and tissue sections were baked to the slides and deparaffinised. Antigen retrieval was performed at pH9/95 °C with an incubation time of 32 min. Blocking was performed before addition of the primary antibody, followed by incubation for 24 min at 36 °C. The appropriate secondary antibody was added , followed by another 24 min incubation period. 3′,3′-diaminobenzadine (DAB) was used as the chromogen. Labelled slides were removed from the instrument. All slides were stained with PAS and counterstained with haematoxylin. Positive and negative control slides were included with each batch of slides labelled by the instrument. Slides were digitised at 400× absolute magnification using the Aperio Digital AT2 Pathology System  and imported into the HALO® to select the area to be analysed. Exclusion annotations were used to outline areas within the tumour that were to be excluded from vessel assessment, such as necrotic tissue. The tiled partitioner function was then used to place 10 boxes of 550 × 500 µm within the annotated region. Boxes were placed at least 550 µm apart and were not placed over any exclusion regions. Where more than 10 boxes were generated, the relevant number of boxes required to reduce to total number to 10 were removed at random by HALO®. The number of endothelial, VM, and “mosaic” vessels were counted within each of the 10 regions per section. Endothelial vessels were CD34+/PAS+, VM vessels were CD34−/PAS+, and vessels that were partially CD34+ and partially CD34− with a PAS+ basement membrane were considered mosaic vessels, as described in previous studies [2.CD34/PAS-labelled sections were used to assess glioblastoma vasculature. An annotation region was drawn around the perimeter of each tumour section in HALO studies ,20. Dens® image analysis platform was used to assess PSMA expression levels. The tumour perimeter was selected, and large areas of necrosis and adjacent normal tissue were manually excluded. Tissue classifier algorithms were trained to recognise PSMA+ labelling , tumour tissue, necrosis, and areas of the slide that did not contain tissue. The Area Quantification algorithm was trained and optimised to detect positive pixel intensities corresponding to PSMA labelling within the tumour. The algorithm was then used to quantify the total tissue area analysed for each tumour and the percentage of the tumour that was weakly, moderately, and strongly labelled for PSMA. PSMA expression values were calculated as an H-score for each tumour section using the equation: H-score = (1 × % of weakly labelled tissue) + (2 × % of moderately labelled tissue) + (3 × % of strongly labelled tissue). HALOp-value < 0.05 was considered statistically significant for all tests. Datasets were tested for normality using the Shapiro–Wilk test. Two-tailed Wilcoxon matched-pairs signed rank tests were used to assess median differences in total vessel density and densities of endothelial, VM, and mosaic vessel subsets between primary and recurrent tumour groups. A one-tailed Wilcoxon matched-pairs signed rank test was used to determine whether PSMA expression significantly decreased in the recurrent tumour group. Kendall’s tau-b correlations were run to determine the relationship between vessel densities, PSMA expression, and clinical characteristics. Kaplan–Meier survival analyses with log rank tests were used to determine whether there were differences in the overall survival (OS), progression-free survival (PFS), or post-progression survival distributions when tumours were grouped as being VM+/VM− or having above or below median PSMA expression. OS was defined as the time in days between the date of primary surgery and date of death, or last known follow-up for censored cases. PFS was defined as the time in days between the date of primary surgery and date of recurrent surgery, and post-progression survival was defined as the time in days from the date of recurrent surgery until date of death. Descriptive statistics are reported as median values for tests of group differences and survival analyses. Statistical analyses were performed using SPSS Statistics  or GraphPad Prism . A A total of 35 cases with matched primary and recurrent glioblastoma samples were included in this study. Twenty patients (57.14%) were male and 15 (42.86%) were female. The median age at diagnosis was 59 years (range 23–81 years) and the median OS time was 493 days (range 57–2531 days). Additional demographic and clinical information is summarised in Immunohistochemical labelling for CD34 and staining with PAS were used to identify endothelial, VM, and mosaic vessels in glioblastoma tissue sections . Vessels2) to recurrent (41.67 vessels/mm2) tumours was statistically significant  compared to primary (86.98 vessels/mm2) glioblastomas  and recurrent (1.32 vessels/mm2) groups  demonstrated a decrease in total vessel density at recurrence, and the decrease in total vessel density from primary (88.30 vessels/mmn = 20) had a median OS time of 514 days, which was longer than the median OS time of 445 days for patients with VM+ tumours (n = 15). However, the survival distributions of the two groups were not significantly different (χ2 (1) = 0.381, p = 0.537) (n = 25) had a longer median OS time of 553 days compared to the median OS time of 434 days for the VM+ recurrent group (n = 10). Again, the difference in OS distributions was not significant (χ2 (1) = 3.552, p = 0.060) (2 (1) = 4.830, p = 0.028), where the median survival of the VM− group  was longer than that of the VM + group   A. When s= 0.060) B. Howeve; n = 8) C. PFS di; n = 8) . z = −1.925, one-tailed p = 0.027) (To determine which type(s) of vessels expressed PSMA in glioblastoma, serial sections of tissue were labelled by DAB IHC for PSMA or CD34 and stained using PAS. Vascular areas of tumour tissue that were PSMA+ were also CD34+ on the subsequent section, indicating that PSMA is expressed by endothelial vessels, not VM, in glioblastoma . We then= 0.027) . n = 18) had a median OS time of 501 days, which was not significantly different from the OS time of 493 days for the below-median PSMA group  = 0.188, p = 0.665)  was longer than for cases with below-median PSMA expression  = 3.860, p = 0.049) (2 (1) = 0.143, p = 0.705)  A. The me= 0.049) B. Howeve= 0.705) C. PFS an= 0.705) . b = 0.343, p = 0.009). No other significant correlations between vessel densities and clinical features were observed . All correlations between densities of different vessel types are shown in b = 0.175, p = 0.143) or recurrent  glioblastoma. The complete correlation matrix is presented in We next determined whether there were correlations between densities of any of the observed vessel types, in either primary or recurrent tumours, and clinical characteristics such as age at diagnosis and OS time. There was a statistically significant moderate positive correlation between VM vessel density in the primary tumour and age at diagnosis . In The reduction in overall vessel density at recurrence compared to primary glioblastoma was attributed to a significant decrease in the density of endothelial vessels, which accounted for most of the tumour vasculature. A decrease in CD34+ vessel density in recurrent glioblastoma has been previously reported ,26, withLabelling for the endothelial cell marker CD34 through immunohistochemistry (IHC) and staining with PAS is the most frequently used method of identifying VM vessels in glioblastoma tissue . Using tAlthough we report a smaller proportion of VM vessels, our results are in agreement with those of a previous study, which also demonstrated that VM vessels represent a minor component of the glioblastoma vasculature . Liu et Despite VM making a minor contribution to the overall vascular density in glioblastoma, a shorter overall survival time has been reported for glioblastoma patients with VM+ primary tumours ,14. We aIn addition to completely CD34− vessels, we observed vessels that were partially CD34+ in a subset of both primary and recurrent glioblastomas. We categorised these as “mosaic” vessels, consistent with prior reports of these vessels in glioblastoma ,20. One PSMA is expressed by the vasculature of numerous tumour types. In agreement with our results, the expression of PSMA in endothelial-cell-lined vessels in glioblastoma has been previously reported ,26. In tWhile we did not observe PSMA+ VM structures in our glioblastoma cases, the possibility of PSMA expression by glioblastoma-derived vasculature cannot be entirely excluded. PSMA is expressed not only by vessels within tumours, but also by a small proportion of glioblastoma cells, which, in addition to VM, may also undergo the process of endothelial transdifferentiation in order to contribute to vessel formation ,40. In nChanges that occur after treatment in recurrent glioblastoma extend to aspects of the tumour microenvironment, including the tumour vasculature. These changes include a decrease in endothelial vessel density and decreased expression of PSMA, suggesting a reduced dependence on tumour angiogenesis. Categorical assessment of VM presence at recurrence suggested an association between VM and shorter post-progression survival. However, VM accounted for a minor proportion of the tumour vasculature in both the primary and recurrent setting, and the extent to which VM makes a functional contribution to the overall vasculature requires further study in order to determine whether VM is a relevant treatment target.


The purpose of the current meta-analysis was to determine the incidence and risk factors to provide a scientific basis for prevention and treatment of postoperative cognitive dysfunction (POCD) after carotid endarterectomy (CEA).Relevant articles published before October 2022 were searched from Pubmed/MEDLINE, Cochrane and Embase databases. The outcomes were the incidence and risk factors for POCD. A random-effects model was applied to estimate the overall odds ratios (ORs) and mean differences (MDs) for all risk factors through STATA 14.0 and RevMan 5.4. The quality of eligible studies was evaluated by Newcastle–Ottawa Scale (NOS) as previously described.P < 0.001). Of the 16 identified risk factors, hyperperfusion  and degree of internal carotid artery (ICA) stenosis  were the potential risk factors of POCD, whereas patients taking statins preoperative had a lower risk of POCD . Subgroup analysis revealed that the risk of POCD at 1 month after CEA was higher in patients with diabetes .A total of 22 articles involving 3459 CEA patients were finally identified. The weighted mean incidence of POCD was 19%  0.16–0.24, The risk factors of POCD were hyperperfusion and degree of ICA stenosis, while diabetes could significantly increase the incidence of POCD at 1 month after surgery. Additionally, preoperative statin use could be a protective factor for POCD following CEA.The online version contains supplementary material available at 10.1186/s13019-023-02428-6. Stroke is the most common cause of disability and death in the world, killing about 12 million people each year . RecentlDifferent from other surgery, the mechanism of POCD after CEA might be closely associated to existed cerebrovascular lesions and the specificity of the surgical procedure. Recently, Arba et al.  found thIn the present meta-analysis, we will systematically review the incidence and perioperative risk factors for POCD following CEA by comparing with the prior articles, to provide more accurate guidance for routine screening risk factors, which may be beneficial to early interventions of at-risk individuals.The present meta-analysis was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement , which wAll original English prospective and retrospective studies including cohort, case–control, cross-sectional, etc. were considered qualified for inclusion criteria, which assessed cognitive functions in patients before and after CEA. We excluded review articles, meta-analyses, conference abstracts, comments and case reports/case series. Moreover, the reported outcomes should be odd ratios (ORs) of risk factors with 95% confidence intervals (95% CI).All records containing titles and abstracts were inputted into Endnote X9 and repeating items were expurgated. Then, we screened titles and abstracts of the remaining studies according to inclusion criteria. The full texts of potentially included articles were further obtained and assessed by two reviewers to identify studies meeting the selection criteria independently. Any different opinions were identified by discussion, with the participation of a third author if necessary. In addition, all relevant reviews screened by the original search and the reference lists were assessed for additional eligible studies.We extracted details of the eligible studies, such as the first name of author, study type, year and country of publication, patient characteristics , methodological standards (cognitive assessment criteria and time of preoperative and postoperative cognitive assessment), Outcome measures. Variables represented by median and quartile were converted to mean standard deviation . All datI2 test. A fixed effects model was applied to conduct the meta-analysis if there was no heterogeneity (P > 0.1 or I2 < 50%) in the eligible studies. If there was significant heterogeneity (P < 0.1 or I2 ≥ 50%), a random effects model was applied for the meta-analysis. Publication bias was assessed as quality through Egger’s tests. A value of P < 0.05 was identified statistically significant.POCD incidence was shown as proportion of the case in total sample and pooled as proportional-weighted estimates. Review Manager 5.4 and STATA 14.0 software were used to conduct the meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to express effect-size for dichotomous data, while mean difference (MD) and 95%CIs were used to show continuous data. If data on risk factors for studies was incomplete, the effect estimate was shown as log[OR] with standard error. First, we performed a heterogeneity test on identified studies through The original literature searched from three databases produced 2350 records. 2022 studies remained when 328 duplicate records were removed. Then, 1986 studies excluded according to titles and abstracts, and the full texts of 36 relevant studies were accessed and reviewed. Finally, a total of 22 observational studies, published between 2001 and 2021, were identified for further qualitative and quantitative synthesis. The database screening process was shown in Fig. The characteristics of the eligible articles were shown in Table I2 = 93.1%, P < 0.001). The result of subgroup analysis showed that incidence of POCD at 3 days, 1 month, 1 year after surgery was 32% , 13% , 13% , respectively.Incidence of POCD was reported in 21 studies, in total of 3413 patients. The weighted mean incidence of POCD was 19% (95% CI 0.16–0.24), as indicated in Fig. The pooled odds ratios (ORs) and mean difference (MD) of 16 risk factors with their heterogeneity test and confidence intervals results were summarized in Table I2 = 62%, P = 0.02), subsequent sensitivity analysis revealed that the degree of ICA stenosis was still a risk factor for POCD , as shown in Fig. I2 = 0%, P < 0.001), as illustrated in Fig. I2 = 0%, P = 0.02), as shown in Figs. Patient-related risk factors were demonstrated in 18 observational articles  as shown in Table There were 6 articles reporting hyperperfusion, 2 articles evaluating selective shunting placement and 9 studies assessing cross-clamping duration. The result of our analysis indicated that the risk of POCD increased in patients with hyperperfusion after CEA  and each factor relevant studies did not indicate the presence of publication bias: age (P = 0.891), sex (P = 0.939), diabetes (P = 0.518), dyslipidemia (P = 0.699), hypertension (P = 0.913), preoperative symptoms (P = 0.092), and cross-clamping duration (P = 0.299) , which might be related to the adjustment for confounding factors in the most of included studies [In the present article, the pooled incidence of POCD after CEA was 19% 95% CI 0.16–0.24), which was consistent with the result in a previous study (6–36%) [ studies , 16. Fur–0.24, whThe result of this article revealed that hyperperfusion was a significant risk factor for POCD after CEA. Cerebral hyperperfusion, a dramatic increase in cerebral blood flow (CBF) exceeded the metabolic requirements of the brain tissue, could cause cerebral oedema or intracerebral haemorrhage. Hyperperfusion post-CEA was defined as a 100% increase or greater in CBF compared with preoperative values. CBF was measured by single-photon emission computerized tomography (SPECT) scanning before and after CEA in included articles. Some studies indicated that asymptomatic hyperperfusion could also lead to postoperative cortical neural damage and resulted in cognitive decline , 18. TheI2 = 62%, P = 0.02), subsequent sensitivity analysis revealed that the degree of ICA stenosis was still a significant risk factor for POCD. We found the study by Zhang et al. [Moreover, different from the meta-analysis of 2020 , we foung et al. . Previoug et al. , 23. Besg et al. .From this meta-analysis, We did not find significant relationships between patient-related factors and POCD, such as age, sex, hypertension and others. Age is a well known risk factor for POCD in patients undergoing cardiac and noncardiac surgery , 26. TheAlthough there were no significant differences in diabetes, the subgroup analysis indicated that diabetes could significantly increase the incidence of POCD 1 month after surgery. Similarly, in a retrospective review of more than 6000 CEA patients, Tu et al.  verifiedAnother interesting result demonstrated that statin use preoperative was a protective factor for POCD following CEA, which consistent with conclusions of previous meta-analysis . StatinsThere are some limitations in the current meta-analysis. Firstly, the absence of standardisation to define POCD may limit the precision of the analysis. Secondly, the time of evaluating cognitive function is only within 1 year after CEA in included studies, which may lead to errors in the incidence of POCD. Finally, some other risk factors such as frailty, anesthesia method and data on middle cerebral artery Doppler are not considered in this study.The potential risk factors of POCD were hyperperfusion and the degree of ICA stenosis, while diabetes could significantly increase the incidence of POCD 1 month after surgery. What’s more, preoperative statin use could be a protective factor for POCD following CEA. In order to develop accurate prevention strategies, surgeons and nursing staff should have a comprehensive understanding of POCD after CEA. This meta-analysis can help them systematically identify risk factors.Additional file 1: Search Strategy and Supplemental Tables and Figures.


The gut microbiome regulates host energy balance and adiposity-related metabolic consequences, but it remains unknown how the gut microbiome modulates body weight response to physical activity (PA).Nested in the Health Professionals Follow-up Study, a subcohort of 307 healthy men  provided stool and blood samples in 2012–2013. Data from cohort long-term follow-ups and from the accelerometer, doubly labeled water, and plasma biomarker measurements during the time of stool collection were used to assess long-term and short-term associations of PA with adiposity. The gut microbiome was profiled by shotgun metagenomics and metatranscriptomics. A subcohort of 209 healthy women from the Nurses’ Health Study II was used for validation.Alistipes putredinis was found to modify the association between PA and body weight. Specifically, in individuals with higher abundance of A. putredinis, each 15-MET-hour/week increment in long-term PA was associated with 2.26 kg  less weight gain from age 21 to the time of stool collection, whereas those with lower abundance of A. putredinis only had 1.01 kg  less weight gain (pinteraction = 0.019). Consistent modification associated with A. putredinis was observed for short-term PA in relation to BMI, fat mass%, plasma HbA1c, and 6-month weight change. This modification effect might be partly attributable to four metabolic pathways encoded by A. putredinis, including folate transformation, fatty acid β-oxidation, gluconeogenesis, and stearate biosynthesis.The microbial species A. putredinis may strengthen the beneficial association of PA with body weight change, suggesting the potential of gut microbial intervention to improve the efficacy of PA in body weight management.A greater abundance of Video AbstractThe online version contains supplementary material available at 10.1186/s40168-023-01542-w. Overweight and obesity are global health problems , 2 and hBlautia wexlerae  synthase I (pinteraction = 0.034) in stearate biosynthesis II  and EC 1.3.1.10: Enoyl-[acyl-carrier-protein] reductase (pinteraction = 0.027) , compared to those with a lower abundance of A. putredinis (− 1.37 kg/m2 per 15 MET-hours/week) (pinteraction = 0.109)  (pinteraction = 0.030) , but not in those with a lower A. putredinis abundance  (pinteraction = 0.079)  is a subcohort nested in the NHS II. Mean (SD) age of MBS participants at stool collection was 60 (3) years. Similar to MLVS, MBS had A. putredinis on body weight response to PA; that is, individuals with a high abundance of A. putredinis had a stronger association of PA with less weight gain and reduced levels of obesity-related plasma biomarkers, compared to those with a low abundance of A. putredinis. We also observed that the microbial metabolic pathways of gluconeogenesis, fatty acid β-oxidation, palmitoleate biosynthesis, and folate transformations might associate with the modification effect of A. putredinis when it is present. Our findings support the consideration of gut microbial features as an important component influencing individuals’ body weight and metabolic responses to PA.Developing effective strategies for body weight management remains a challenge worldwide , 2. AlthA. putredinis may improve the positive effect of PA on controlling body weight gain via changes in gut microbial metabolism. Alternatively, low PA in combination with some additional exogenous factors may increase both the chance of A. putredinis acquisition and of weight gain. Further interventional studies are needed to differentiate these alternatives. If confirmed, measures to enrich A. putredinis may be considered to enhance the benefit of PA in body weight control. If supported by the appropriate direction of causality, this could potentially be more effective than direct modifications of the microbiome to support weight loss, since we observed no significant association of PA with overall microbial configuration and only weak associations with specific microbial taxa and functions. These latter findings are consistent with prior studies [Modification effect by the microbiome indicates phenotypes for which pre-existing microbial differences correspond with changed outcomes (such as weight gain), even if the microbiome itself is not substantially changed by an exposure (such as PA). In the current study, the observed modification effect of gut microbial features on the associations between PA and adiposity measures is striking. Although we cannot address causality because of the observational nature of this study, these findings suggest two main possible hypotheses. First, the carriage of  studies , 24–31 aA. putredinis driving the modification effect and validating the modification effect in an independent cohort, our study provides evidence supporting the gut microbiome, particularly A. putredinis, as an important modifier on individual’s response in body weight to PA.Several potential modifiers on body weight response to PA have been proposed, e.g., modified appetite, PA performed beyond the prescribed level, and perceived reinforcement value of food , 32, 33.A. putredinis, for example, expression of enzymes for folate/methionine transformations showed positive modifications on the association between PA and body weight change. This is only one of several A. putredinis activities implicated in the interaction, but it already suggests the variety of pathways by which it could act: changes in extracellular folate pools in the colon signal the host via both energy and immune regulation [A. putredinis pathways positively modifying body weight response to PA is fatty acid β-oxidation. Although gut anaerobes generally do not produce energy by fatty acid β-oxidation [A. putredinis showing effect modifications, it is not clear which of these may be causal drivers of the weight change phenotype versus passenger effects of modified A. putredinis physiology, and more studies are thus needed.Our finding represents a specific example of the gut microbiome’s broader ability to influence host metabolism through a variety of regulatory and energy balance mechanisms . In the gulation , 40, andgulation , 42. Anoxidation , the proxidation . HoweverA. putredinis to enhance PA-related metabolic benefit. Although we did not observe a direct association of PA with A. putredinis, A. putredinis was observed to be increased by PA intervention in prediabetic population [A. putredinis abundance in humans [A. putredinis to inform future prebiotic development.Once confirmed, our findings can have important implications. First, it supports the potential of gut microbial modulation in bolstering the efficacy of PA in body weight control. Personalized strategies tailored to individuals’ gut microbial features may represent a promising and sustainable approach to mitigate adiposity-related health problems. Second, our findings open a new venue of research in improving the abundance of pulation . Intakesn humans . FurtherOur study has several strengths, including the assessments of both long-term and short-term PA, the use of accelerometers for a more accurate PA quantification, analysis of deeply phenotyped cohorts with detailed information on multiple body weight and related metabolic measures, and validation of the findings in an independent cohort. Limitations are also noteworthy. First, it was not an interventional study, so we were unable to establish causality between the PA exposures and body weight measures. As an observational study, confounding from other factors influencing the gut microbiome and observed associations cannot be ruled out. However, we adjusted for several such factors, including dietary pattern, which did not essentially change our results. Second, systemic mechanistic explanations for the findings are lacking, particularly as they might be transmitted via host regulatory activities. Although we examined the effect modification by both microbial taxonomy and functions, more studies are needed to link the mechanisms to host outcomes before conclusions can be reached. Third, participants in the discovery cohort were uniformly older, predominantly Caucasian men. However, the consistent results in an independent cohort of younger women indicate the generalizability of our findings.A. putredinis may strengthen the beneficial association of PA with body weight change; the modifying role of A. putredinis may be partly attributable to its functional activities in the gut including folate transformation and fatty acid β-oxidation. Our findings provide evidence for a gut microbiome-based personalized approach for body weight management.In conclusion, a higher abundance of The Health Professionals Follow-up Study (HPFS) is an ongoing prospective cohort study of 51,529 US male health professionals aged 40 to 75 years at enrollment in 1986 . ParticiNurses’ Health Study (NHS) II is a large, prospective cohort study that enrolled 116,429 registered female nurses aged 25–42 years in 1989. Similar follow-up procedures have been used as in the HPFS cohort. Participants completed a detailed biennial questionnaire regarding their lifestyle and medical history with over 90% of follow-up . Mind–BoIn 1986 in the MLVS and 1991 in the MBS and every 2 years thereafter, using a modified Paffenbarger physical activity questionnaire (PAQ), participants reported mean time spent per week engaged in specific activities during the past year, using 13 categories ranging from “None” to “40 + h”. Activities included walking to work or for exercise (including golf), jogging (> 10 min/mile), running (≤ 10 min/mile), bicycling (including stationary machine), lap swimming, tennis, squash or racquetball, calisthenics or rowing, other aerobic exercise (e.g. exercise classes), lower-intensity exercise , moderate outdoor work , heavy outdoor work , weightlifting (including machines), and standing or walking around work and around home. Participants indicated activity intensity  for swimming, biking, and tennis. Participants also reported usual walking pace outdoors as easy, average, brisk, or very brisk and stair flights climbed daily. The questionnaire was validated against 4 7-day activity diaries administered across 4 different seasons  and against resting heart rate  . In the −1 h−1 [We used metabolic equivalent task (MET)-hours to represent PA levels. MET is the ratio of work metabolic rate to a standard resting metabolic rate of 1.0 (4.184 kJ) kg−1 h−1 . A MET v−1 h−1 . We deri−1 h−1 .Participants of MLVS were provided an accelerometer , detailed instructions, and a wear time diary. Accelerometers measure body movement during wear and objectively measure PA behavior. At two time points of approximate 1 month before the 1st and after the 2nd stool collection, they were asked to wear the monitor on the hip for 7 consecutive days during waking hours, except bathing or swimming, and maintain a wear time diary. Accelerometer methods have been described elsewhere . We usedDue to a lack of accelerometer administration in the MBS, we used the PA data collected by PAQ at the time of stool collection to represent recent PA and mean PA across all PAQs in NHS II and MBS to represent long-term PA.2) reported in HPFS. We used the difference between the 2 body weight measurements at the two stool collections (2nd minus 1st) to represent short-term body weight change in 6 months, and the difference between the reported body weights at stool collections and age 21 to represent long-term body weight change since age 21. A positive value of the weight change represents weight gain and negative value represents weight loss.At the enrollment of HPFS in 1986, participants were requested to report their body weight and height and recall their body weight at age 21. Body weight at age 18 was inquired at enrollment in the NHS II in 1989. Since then, participants reported their body weight biennially through questionnaires. The Pearson correlation coefficient between self-reported body weight and the mean of 2 standardized technician-measured weight was 0.97 . In MLVSO from the DLW protocol, total body water was calculated using the equation of total body water = NO/1.01 because the NO is assumed to overestimate total body water by 1% [In the MLVS, approximately coincided with the 2 accelerometer administrations, a Doubly Labeled Water (DLW) test was conducted to estimate fat-free mass. Isotope dilution has been long considered as one of the reference methods for the measurements of body composition. It has been well documented that fat-free mass in healthy adults has a hydration of 73% . Knowinger by 1% . TherefoIn the HPFS and NHS II, dietary information was collected at the baseline  and updated every 4 years thereafter with validated food frequency questionnaires . In the p = 0.004; with fat mass percentage 0.52, p = 0.002) and HbA1c levels   to collect a blood sample after fasting for 12 h. For each blood sample, information on fasting status, blood collection time and date, smoking status, and body weight was recorded. After collection, blood samples were placed on ice packs, stored in Styrofoam containers, returned to the laboratory via overnight courier, and centrifuged and aliquoted for storage in liquid-nitrogen freezers (− 130 °C or colder). High-sensitivity C-reactive protein (CRP) concentration was determined in plasma by an immunoturbidimetric high-sensitivity assay using reagents and calibrators from Denka Seiken with assay day-to-day variability between 1 and 2%. Hemoglobin A1c (HbA1c) was measured by turbidimetric immunoinhibition using packed red cells (Roche Diagnostics), which is a standard approved by the US National Glycohemoglobin Standardization Program and Food and Drug Administration for clinical use. Our study included 304 participants in the analyses on blood biomarkers. Among 304 participants, 164 and 140 participants provided two and one blood sample, respectively, yielding a total of 468 blood samples. Among the randomly selected 10% quality control (QC) samples, the coefficients of variation were < 7% for CRP and HbA1c. We observed significantly positive correlations of BMI and fat mass percentage with plasma CRP  to remove low-quality read bases and reads of human origin. Taxonomic profiling was performed using MetaPhlAn 2.6.0 (http://huttenhower.sph.harvard.edu/metaphlan2) [Taxonomic and functional profiles were generated using the bioBakery meta’omics workflow . Sequencaphlan2) , which chttp://huttenhower.sph.harvard.edu/humann) [Shotgun metagenomes and metatranscriptomes were functionally profiled using HUMAnN 2.8.0 (/humann) . Briefly/humann) . Unmappe/humann)  using DI/humann) . Hits ar/humann)  and comb/humann) . More de/humann) , 48.Metatranscriptomic functional activity was assessed in 341 MLVS samples with both RNA and DNA data using RNA/DNA ratio. Owing to the compositionality of RNA and DNA measurements, the resulting ratio is relative to the mean transcript abundance of the entire microbial community. Thus, a ratio of 1 implies that the pathway is transcribed at the mean transcription abundance of all pathways in the microbial community. Only samples with at least 1 read per kilobase (RPK) were included in the analysis. Infinite values of RNA/DNA ratios were imputed using 99% percentile of a given feature and values of 0 were imputed using half of the 1% percentile before log transformation.We linked each of the microbiome measurements with the PA, body weight, biomarkers, and other variables collected at the time closest to the time of stool collection. Specifically, the 1st and 2nd metagenomes and metatranscriptomes  were linked to recent PA assessed at the first accelerometer, long-term PA assessed at the 1st stool collection, anthropometry assessed at the first questionnaire and DLW test, and biomarkers measured at the first blood sample collection. Similarly, the 3rd and 4th metagenomes and metatranscriptomes were linked to the corresponding second recent and long-term PA, anthropometry, and biomarker measures. We used recent PA level to link with BMI and fat mass percentage at stool collection, short-term weight change in the past 6 months, and plasma CRP and HbA1c at stool collection; and used long-term PA level to link with weight change since age 21.To investigate variation in species composition, we used principal coordinate analysis (PCoA) for each sample using the Bray–Curtis measure to calculate the dissimilarity matrix. We performed omnibus testing with permutational multivariate analysis of variance (PERMANOVA) to quantify the percentage of variance in the microbial communities explained by PA measures including recent and long-term total PA and PA by intensity, body weight measures including BMI and fat mass percentage at stool collection, short-term weight change in 6 months (restricted in data of the 1st pair stool samples), and long-term weight change since age 21, plasma CRP and HbA1c, and covariates based on the Bray–Curtis dissimilarity metric using the adonis function in the R package vegan 2.5–6. All the PERMANOVA tests were two-sided with the degree of freedom of 1.https://huttenhower.sph.harvard.edu/maaslin2) [q values. The circular phylogenetic tree was produced by GraPhlAn as a part of the bioBakery workflow (https://huttenhower.sph.harvard.edu/graphlan).For per-feature tests, we first performed quality control filtering for taxonomic and functional features by removing those with a relative abundance of < 0.01% in less than 10% of samples. Similarly, we filtered out all enzymes with a relative abundance of < 0.001% or detected in less than 10% of all samples. After filtering, 139 microbial species were included in the analysis. Using the raw functional profiling abundances calculated for metagenomes and metatranscriptomes, we quantified functional activity of the gut microbial transcripts by calculating the RNA/DNA ratio of microbial enzymes, which provides an index of over/under-transcription (relative to DNA copy number) within each individual microbiome sample . Pathwayaaslin2) . We log-p value for interaction. A significant p value of the product term indicates an interaction between the PA measures and the overall microbial composition or an individual microbial species, referred to as a modification effect. We used the same methods in examining the modification effect of the gut microbiome on the association between PA and body weight in the validation cohort.We used generalized linear mixed-effects regressions  for all the association analyses. All models included identifiers of participants as random effects to account for within-subject correlation due to repeated sampling, and included the PA measures and covariables of age, smoking, Alternative Healthy Eating Index (AHEI), total energy intake, probiotic use, antibiotic use, and Bristol stool scale as fixed effects. We firstly carried out hypothesis-generation by testing the potential interactions of PA measures with the 1st and 2nd principal coordinate loading scores (PCo1 and PCo2) of the overall gut community structure in relation to the body weight measures and biomarkers. We included in the models the main effects of the PA measures and PCo1 or PCo2, as well as their product term, in addition to the covariables as fixed effects and participant identifier as random effect. Of the 139 microbial species passing the quality control criteria, the 10 most abundant species together accounted for 46% of the overall community abundance. Thus, on top of a significant interaction between PA and PCo1 or PCo2, we further tested the interactions between PA and relative abundances of the top 10 loading individual microbial species using the same methods. We used the median abundance level as cutoff for each species to dichotomize the samples and examined their interactions with the PA level in relation to body weight measures. We tested the significance level of the beta coefficient of the product term using a two-sided likelihood ratio test by comparing models with and without the interaction term to calculate the A. putredinis, we further examined the metabolic pathways contributed by A. putredinis and the involved enzymes to understand the mechanism through which A. putredinis modulates body weight response to PA. Among all the pathways contributed by A. putredinis, we firstly performed a quality control by excluding those correlated with others with a correlation of > 0.9 and taking the most abundant feature in each of such clusters as its representative. For the pathways that showed significant modification effect, we examined all the involved enzymes. For each enzyme, we ranked the contributions from various species in metagenomes and, if the contribution from A. putredinis ranked the highest, we then examined the interaction of RNA/DNA ratio with long-term PA in relation to weight change from age 21 to stool collection. Metatranscriptomes were functionally profiled using the same methods as metagenomes in 341 MLVS samples with both RNA and DNA data. Median RNA/DNA ratio was used as the cutoff to define low and high transcriptional activity of A. putredinis. All analyses were two-sided and performed using R version 3.6.1.After observing the modification effect of Additional file 1: Supplementary Table 1. Characteristics of participants in the Men’s Lifestyle Validation Study according to quartiles of recent physical activity level. Supplementary Table 2. Spearman correlations between the variables of physical activity, body weight, body weight change, and plasma biomarkers. Supplementary Fig. 1. Spearman correlation between long-term total physical activity level and calorie-adjusted dietary intakes of major nutrients at p < 0.05. Supplementary Fig. 2. Principal coordinate analysis of all samples using species-level Bray–Curtis dissimilarity according to recent physical activity level measured by accelerometer. Supplementary Fig. 3. Gut microbial diversity using species taxonomic data according to recent total physical activity measured by accelerometer. Supplementary Fig. 4. Significant associations of physical activity, body weight measures, and plasma biomarkers of hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP) with microbial species (q ≤ 0.25). Supplementary Fig. 5. Significant associations of physical activity, body weight measures, and plasma biomarkers of hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP) with metagenomic pathways (MetaCyc) (q ≤ 0.25). Supplementary Fig. 6. Significant associations of physical activity, body weight measures, and plasma biomarkers of hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP) with metagenomic enzymes  (q ≤ 0.25). Supplementary Fig. 7. Interaction between physical activity measures and the first two principal coordinates axis (PCo1 or PCo2) in relation to body mass index at stool collection, fat mass percentage at stool collection, short-term (6 months) weight change, long-term weight change from age 21 to stool collection, plasma hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP). Supplementary Fig. 8. Interaction between physical activity and abundances of the top 10 most abundant species in relation to body mass index at stool collection, fat mass percentage at stool collection, short-term (6 months) weight change, long-term weight change from age 21 to stool collection, plasma hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP). Supplementary Fig. 9. Associations between intensity-specific physical activity and body weight measures according to Alistipes putredinis abundance. Supplementary Fig. 10. Relative abundance, prevalence, and interactions of all the species in the genus of Alistipes with physical activity in relation to body mass index at stool collection, fat mass percentage at stool collection, short-term (6 months) weight change, long-term weight change from age 21 to stool collection, plasma hemoglobin A1c (HbA1c) and high-sensitivity C-reactive protein (CRP).


CTCF) is a protein-coding gene involved in transcriptional regulation, insulator activity, and regulation of chromatin structure, and is closely associated with intellectual developmental disorders. In this study, we report two unrelated Chinese patients with intellectual disability (ID). According to variant interpretation results from exome sequencing data and RNA-seq data, we present two novel heterozygous CTCF variants, NM_006565.3:c.1519_2184del (p. Glu507_Arg727delins47) and NM_006565.3:c.1838_1852del (p.Glu613_Pro617del), found in two distinct unrelated patients, respectively. Moreover, RNA-seq data of patient 1 indicated the absence of the mutant transcript, while in patient 2, the RNA-seq data revealed a CTCF mRNA transcript with a deletion of 15 nucleotides. Notably, the RNA sequencing data revealed 507 differentially expressed genes shared between these two patients. Specifically, among them, 194 were down-regulated, and 313 were up-regulated, primarily involved in gene regulation and cellular response. Our study expands the genetic and clinical spectrum of CTCF and advances our understanding of the pathogenesis of CTCF in vivo.CCCTC-Binding Factor ( Intellectual disability (ID) is a neurodevelopmental disorder characterized by deficits in intelligence and adaptive functioning of varying severity before the age of 18. The global prevalence of ID is around 1%–3% in the general population and approximately 1% in China. ID can manifest as either an independent feature known as non-syndromic ID (NSID), or it can be accompanied by facial dysmorphic features and other morphological anomalies. Indeed, the majority of ID cases are attributed to genetic abnormalities. With the development of next-generation sequencing, researchers have identified more than 1,000 genes causally linked to ID (CTCF (CCCTC-Binding Factor) is a protein-coding gene (OMIM: 604167) involved in a variety of chromatin regulatory processes, including gene expression, chromatin higher-order organization, and maintenance of chromatin 3D structure (CTCF gene consists of 12 exons that encode eleven zinc finger (ZF) domains. Numerous studies have identified to date 59 pathogenic variants in the CTCF gene associated with autosomal dominant ID, including 5 large deletion variants  and c.1186dupA (p.Arg396Lysfs13), as well as one de novo missense pathogenic variant, c.1699C>T (p.Arg567Trp), in CTCF in four syndromic ID patients  have been identified in Chinese patients associated with the neurodevelopmental disorder, there is an urgent need to report additional genetic and clinical features from Chinese ID patients to expand the spectrum of CTCF variation in the Chinese population ( OMIM: 60167 involtructure . The CTCvariants . It is wCTCF variants (NM_006565.3:c.1519_2184del (p. Glu507_Arg727delins47) and NM_006565.3:c.1838_1852del(p.Glu613_Pro617del). Additionally, we assess the disease-causing mechanism in our patients through RNA sequencing. This study expands current knowledge of the genetic and clinical spectrum of CTCF variants and reveals consistent phenotypes and disease mechanisms across populations.Here, we present the genetic and clinical characterization of two unrelated Chinese ID patients with novel Patients were recruited from the Second Affiliated Hospital of Chongqing Medical University in Chongqing, China. The patients were clinically assessed, and medical experts and geneticists confirmed no other linked anomalies. This study was approved by the ethical committee of the Second Affiliated Hospital of Chongqing Medical University. Written informed consent was obtained from the patients' parents .Genomic DNA from the patients was extracted from peripheral blood collected in EDTA tubes. Exome sequencing was performed on the patients using the Agilent  version 6 enrichment kit and the Illumina HiSeq 4000 sequencing system .Trimmomatic was used to remove adapter contamination and trim low-quality reads to obtain clean reads . Then, tCopy number variations (CNV) were called using ExomeDepth  with defTo validate the presence of CNVs, we performed CNV-seq analysis following the protocol proposed by Dong Zirui et al. . BrieflyTotal RNA was extracted from the peripheral blood of these two patients and enriched by oligo-dT bead capture, separately. cDNA was synthesized according to the manufacturer's protocol, and cDNA libraries were constructed using the Illumina TruSeq stranded mRNA sample prep kit protocol (Illumina). Pooled samples were sequenced using a NovaSeq 6000 sequencing system.n = 735) from GTEx v8 data were used as controls  using STAR (2.7.8a) with the Gencode v29 annotation . Blood scontrols  first, fcontrols  package  using ST KOBAS-i . The adjCTCF Exon 10 (5′-CTGCGGCTTTTGTCTGTTCT-3′) and a reverse primer specific to Exon 13 (5′-CCTCCTCTTCCTCTCCCTCT-3′). The PCR reaction was performed under the following conditions: an initial denaturation at 95°C for 3 min, followed by 40 cycles of denaturation at 95°C for 30 s, annealing at 58°C for 15 s, and extension at 72°C for 45 s. The resulting PCR products were then subjected to Sanger sequencing for further analysis.The RNA specimens collected from both the patients and the negative control underwent reverse transcription and subsequent amplification of cDNA using a forward primer specific to GAPDH mRNA was utilized as an internal control, and the experiments were conducted in triplicate. Quantitative PCR (qPCR) analysis was performed using the QuantstudioTM 7 Flex system (Applied Biosystems) with the following amplification program: 95°C for 10 min, 40 cycles at 95°C for 15 s, and 60°C for 1 min.Reverse transcription-quantitative PCR (RT-qPCR) was used to measure the relative expression of candidate differentially expressed genes in both patient and control blood cells. The CTCF gene. As exome sequencing (ES) targets only the coding regions, to assess whether the intronic region of the CTCF gene was affected or not, we employed CNV-seq. The CNV-seq data indicated a 16,519 bp deletion in the region of chr16:67,658,826–67,675,344 (hg19), encompassing exon 8 to exon 12 of the CTCF gene , we compared total CTCF RNA expression levels to controls. As shown in CTCF expression levels in patient 1 were 50% compared to controls, indicating that the mutant mRNA is undergoing NMD.Patient 1 is a 22-year-old female with a height of 146 cm (<3rd percentile) and a weight of 62 kg (89th percentile). She presented with moderate intellectual disability, strabismus, and scoliosis . Exome sTCF gene . ConfirmCTCF gene is categorized as a haploinsufficient (HI) gene with a pLI score of 1. The deletion of exon 9 to exon 12 in the CTCF gene removes 30% (220/727) of the CTCF protein and could affect the zinc finger domain of the CTCF protein. Based on the ACMG/ClinGen guidelines for CNVs, the NM_006565.3:c.1519_2184del (p.Glu507_Arg727delins47) variant was classified as a likely pathogenic variant [criteria 2D-4 (0.9) = 0.9]. This classification was based on the variant's overlap with established HI genes and its result in exon deletions that include other exons in addition to the last exon, scoring 0.9 according to the guidelines. The inheritance status of this variant remains unknown as parental testing was not possible due to the family relocating, and her parents chose not to participate in the verification process.The CTCF gene (NM_006565.3:c.1838-1_1841del) in patient 2. Sanger sequencing confirmed that the c.1838-1_1841del variant occurred de novo , standing at a height of 135 cm (3rd percentile), with a head circumference of 52 cm . She exhibited mild intellectual disability, epilepsy, and distinctive facial dysmorphic features, including prominent incisors and ptosis. Notably, Patient 2 did not display any characteristic signs of skeletal dysplasia . Exome s de novo , as it wCTCF mRNA, leading to the deletion of 5 amino acids from the CTCF protein in patient 2  using RT-qPCR confirmed the accuracy of differential analysis with RNA-seq data  and NM_006565.3:c.1838_1852del(p.Glu613_Pro617del) identified in two unrelated Chinese ID patients and validated the effect of these two variants on gene expression and splicing of the CTCF gene. However, it is important to note that the de novo status of the c.1519_2184del variant cannot be confirmed at this time due to the unavailability of parental testing for the patient. Our findings have not only identified the likely genetic causes of disease in these two patients but have also expanded the spectrum of disease-causing variants that can cause ID.Identifying genetic causes of ID is crucial for understanding the molecular mechanisms underlying clinical features and for improving the management of the patients. In this study, we present two novel heterozygous CTCF gene is definitively associated with autosomal dominant syndromic ID, which was approved by the ClinGen Intellectual Disability and Autism Gene Curation Expert Panel on 7/21/2021  and NM_006565.3:c.1838_1852del(p.Glu613_Pro617del), identified in unrelated Chinese patients with ID. The c.1519_2184del variant in patient 1 cause a partial deletion of the zinc-finger domain. We speculate that the breakpoint for the c.1519_2184del variant may reside within the intronic or intergenic regions of the CTCF variants and discovered broad deregulation of genes involved in the cellular response to extracellular stimuli  in the patients. Among these, 66 DEGs were consistent when compared with the findings from the previous two studies. Moreover, nine genes  exhibited consistent differential expression across all three studies , which manifests as mild to moderate intellectual disability and respiratory chain complex IV deficiency. The deficiency of the COX15 gene leads to mitochondrial complex IV deficiency (OMIM #220110), presenting with encephalomyopathic features in the neonatal period for some patients, while others experience developmental regression within the first year of life. Additionally, GAS7 is associated with schizophrenia and plays a role in regulating neuronal migration and morphogenesis. Pathway enrichment analysis showed that the biological functions of these 507 DEGs were related to gene regulation and cellular response. Our study suggests that the main pathogenic mechanism of variants located in the CTCF domain is the imbalance of gene expression and regulation, which is consistent with previous research  and inframe deletion variants (c.1838_1852del) in the


P < 0.05) in SeNSM group compared to control. Principle Coordinate Analysis separated the microbial communities into three clusters based on feeding treatment. The bacterial community was dominated by phylum Bacteroidetes and Firmicutes that were affected (P < 0.05) by Se sources. Specifically Bacteriodetes was higher (P < 0.05) in SS and SeNSM groups; and Firmicutes was higher (P < 0.05) in the control group. Moreover, the predominant bacterial genera were Prevotella, Rikenellaceae RC9 gut group, Unclassified_Bacteroidales, which were higher (P < 0.05) in SeNSM group. The methanogenic community belonged to phylum Euryarchaeota and was significantly decreased (P < 0.05) by Se supplementation. Principal component analysis based on rumen fermentation parameters, and relative abundances of bacteria and methanogens revealed three distinct clusters. These findings suggest that Se supplementation affected the relative abundances of dominant bacterial groups, declined rumen methanogens and SeNSM supplementation showed some positive impacts on some fibrolytic bacteria.Dietary selenium (Se) sources affects the structure of the rumen microbial community and rumen fermentation. This study evaluated the effects of sodium selenite (SS) and bio-nanostructured selenium (SeNSM) on rumen fermentation and structure of rumen microbial community of lactating Barki ewes. Twenty one lactating Barki ewes were assigned into three groups based on their body weight and milk yield. The experiment lasted for 50 days, whenever, the control group was fed basal diet; group SS received basal diets plus sodium selenite as inorganic source of Se; and group SeNSM received basal diet plus organic selenium bio-nanostructured. Ruminal pH and volatile Fatty Acids (VFA) was lower ( Balanced diets are essential for the health and performance of animals. The diet of lactating animals should contain proper amounts of macro and micro minerals that are required for maintaining health and optimum milk production. The diets of ruminant animals are originated mainly from forage plants, which vary in their contents of minerals. Moreover, the mineral content in the plant depends on several factors such as soil, plant type, climate conditions, and agricultural practices . SubsequSelenium plays a vital role in animal productivity as it is involved in several metabolic functions and represents the metal part of several enzymes . SeleniuStreptococcus thermophilu and Lactobacillus delbrueckii subsp. Bulgaricus, and enhanced the immunity and performance of pregnant ewes and growing lambs [Furthermore, nanotechnology was used to produce bio-Se nanoparticles (SeNPs) to improve the bioavailability of Se . Organicng lambs –13. Hendng lambs  highligh, which is affected mainly by the animal diet [. Consequently, it is necessary to study the effect of feeding interventions on rumen microbial fermentation. Minerals affect the rumen ecosystem by changing the rumen dilution rate and osmotic pressure [. Previous studies [Bacteria make the greatest contribution to rumen fermentation , which imal diet . Consequpressure –19. Prev studies , 21 repo. However, limited research has examined the effect of Se sources on the modulation and structure of rumen microbial groups. Tian et al. [Using organic Se in the form of Se-Yeast increased short-chain fatty acids in the rumen compared to inorganic Se . In addin et al.  and Cui n et al.  observedn et al.  investign et al. , and in n et al. . Recent n et al. , 21, 25.This experiment was conducted at the farm of the Faculty of Desert and Environmental Agriculture, Matrouh University, Matrouh, Egypt.Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus were mixed in yogurt culture at 1:1 (w/w) and cultivated in whey yeast extract media [Bio-nanostructured selenium (SeNSM) were prepared according to the method of Prokisch and Zommara  and as dct media . Afterwact media . The sedOvis aries; average body weight, 32.72 ± 0.84 kg; 14 ± 7 days in lambing date) were used in this study for 50 days as an experimental period. Animals were divided into three groups according to their BW and milk yield from a previous lactation period to receive one of three experimental diets: basal diet (Control); basal diet supplemented with 1.2 mg/kg dry matter (DM) of Se from sodium selenite  as the inorganic source of Se (SS); basal diet supplemented with 1.2 mg/ kg DM of Se from SeNSM as the organic source of Se (SeNSM). The Se supplementation was mixed daily into the concentrate before feeding and then mixed with roughage. According to our previous study [This study is a apart of our previous study  and animus study  to each Diet was analyzed for for DM method 930.15) and nitrogen (method 954.01) according to the procedure of to the Association of Official Analytical Chemists .15 and n. AnalyseBy the end of the experimental period, ruminal liquor samples were withdrawn from all ewes before the morning feeding using a stomach tube with GM-0.336A vacuum good pump . Ewes were restrained without anesthesia or sedation and released. The first 50 mL of rumen fluid was discarded to minimize saliva contamination according to El-Essawy et al. .DNA was extracted from one milliliter of rumen sample. The sample was centrifuged at 13,000 rpm, and the remained pellets were used in DNA extraction by i-genomic Stool DNA Extraction Mini Kit  according to the manufacturer’s instructions. The quality and quantity of extracted DNA were verified by Nanodrop spectrophotometer and gel electrophoresis. The composition and diversity of microbial community were studied using amplification of variable V4 region on 16S rDNA gene by 515F and 926R primer sets using the following PCR conditions: 94 °C for 3 min; 35 cycles of 94 °C for 45 s, 50 °C for 60 s, and 72 °C for 90 s; and 72 °C for 10 min. The purified PCR-amplicons were sequenced using Illumina MiSeq system at Integrated Microbiome Resource .assign Taxonomy” and “addSpecies” functions and microbial taxa were identified using SILVA reference database (version 138). Alpha diversity indices, Chao1, Shannon, and InvSimpson, were calculated. Moreover, Beta diversity of microbial communities was dtermined as principal coordinate analysis (PCoA) using bray–curtis dissimilarity. The differences in rumen fermentation parameters, microbial diversity indices, and the relative abundances of bacterial phyla and genera were determined by One-way Anova using Duncan test a P < 0.05 as a threshold of statistical significance. Morover, Principal component analysis (PCA) was determined using the relative abundance of dominant bacterial phyla and genera and rumen fermentation to compare the clustering of individuals of every sheep group.The generated paired-end (PE) Illumina raw sequences were analyzed in R (version 4.2.2) using the DADA2 pipeline . The FasP < 0.05) in SeNSM group compared to control.Ruminal pH, ammonia-N, and total VFA, are shown in Table The Illumine sequencing of the V4 region on the 16S rDNA gene in all rumen samples generated 393,443 high-quality sequence reads with a mean of 32,786.9 ± 2257.93 (Mean ± standard error (SE)). The total sequence reads in control group was 129,653 with an average of 32,413.25 ± 4735.69, the total sequence reads in SS group was 124,464 with an average of 31,116 ± 4527.28, and the total sequence number in SeNSM group was 139,326 with an average of 34,831.5 ± 3284.4. Different alpha diversity indices were measured; the number of ASVs and Chao1 index were higher in SeNSM group compared to other groups; also Shannon and InvSimpson indices were higher in SS group compared to other groups (Table P < 0.05), wherever phylum Bacteroidetes was increased significantly and SS group showed the highest relative abundance of this phylum followed by SeNSM and control group, respectively . Inspection of the bacterial community revealed 12 bacterial phyla and one archaeal phylum  in the rumen of supplemented groups  compared with the control group   in SS group compared to Control and SeNSM. Phylum Synergistota was found only in sheep SS group. Furthermore, the methanogenic community was assigned to phylum Euryarchaeota, which was represented 1.3% of total sequence reads and was decreased significantly (P < 0.05) by Se supplementation. Euryarchaeota was assigned to genus Methanobrevibacter and genus Methanosphaera (Table Methanobrevibacter was decreased significantly (P < 0.05) due to Se supplementation. Methanosphaera was not detected in the SeNSM group. Principal component analysis (PCA)  Fig.  was condStreptococcus thermophilu and Lactobacillus delbrueckii subsp. bulgaricus in a whey yeast extract media [In our previous study, SeNSM was produced by yogurt culture containing ct media . Furthemct media . Organicct media , 26–36. ct media –17. Prevct media , 38 a loct media , 37, 38.ct media . Also, pct media . Moreovect media  explaine. Previous studies on sheep and goat [Diet composition is the main determiner of the diversity and composition of the rumen microbial community. The results of PCoA Fig.  showed tand goat , 18 showand goat  reportedPrevotella, Rikenellaceae RC9 gut group, and Unclassified_Bacteroidales in SeNSM group, which is in the line with a previous study on goats [Prevotella dominated the microbial communities of several ruminant species and it plays an active role in the utilization of amino acids and hemicelluloses, and pectin and produces propionate and xylanase [Rikenellaceae RC9 gut group, which showed higher relative abundance in SeNSM group, plays a critical role in the digestion of crude fiber [Previous studies , 40, 41 on goats . Genus Pxylanase , 43. Morde fiber , 45. Furde fiber .Prevotella in the rumen of buffalo. Genus Prevotella utilizes hydrogen, the primary substrate for methanogenesis, to produce propionic acid, which affects methane production adversely [These findings are supported by the results of Tian et al.  who showdversely , 40–48.Prevotella was increased, which agrees with the study of Aguilar-Marin et al. [Methanosphaera in the rumen of supplemented sheep in our study.In this context, the relative abundance of rumen methanogens, phylum Euryarchaeota, was declined in supplemented sheep groups SS and SeNSM, whenever, the relative abundance of n et al. . In addin et al.  reportedMethanosphaera is one of the major methane-producing genera in the gut of ruminant animals and it was declined in the rumen of Barki sheep when propionic acid was increased [Prevotella and Rikenellaceae RC9 gut group in the rumen of supplemented groups, it could be speculated that Se supplementation could improve lignocellulose digestion and modulate the rumen methanogenic community.Genus ncreased , which sOscillospiraceae NK4A214 group and Christensenellaceae R-7 group. Oscillospiraceae NK4A214 group is uncultured bacteria that was detected in the rumen of reindeer and the role of this bacteria in the rumen is still unknown [Christensenellaceae R-7 has a potential role in fiber digestion and was linked positively with animal performance [The decline in the relative abundance of phylum Firmicutes might indicate that Se supplementation is not suitable for this phylum . This ph unknown . Christeformance –49, howeformance .It could be observed that SeNSM affected the relative abundance of some bacterial and archaeal groups compared with SS. For instance, the genus Oscillospiraceae NK4A214 group (phylum Firmicutes) and Rikenellaceae RC9 gut group (Phylum Bacteroidia) were higher in SeNSM compared to SS. Furthermore, the archaeal genus Methanosphaera was not detected in SeNSM group. These findings indicated that selenium sources affect the relative abundance of some rumen bacteria and archaea. Mainville et al.  explaineThis study provides deep insight into the effect of Se source on the rumen microbial community of lactating Barki sheep. Selenium supplementation declined rumen methanogens and improved the abundance of some microbial groups that have a role in fiber digestion, which indicates that Se supplementation could improve dietary fiber digestibility and alleviating methane emission from the animal. Organic nano-Se did not exhibit a significant effect on the rumen microbiota compared to sodium selenite. However, considering the safety factor, it might be recommended to use organic nano-Se in animal diet.


Motoric cognitive risk syndrome (MCR) is a pre-dementia symptom strongly predicting cognitive decline and dementia. Although advancements in elucidating the epidemiology of MCR, the evidence about the association between sarcopenia, sarcopenia parameters, and MCR remains scarce.The purpose of this study was to determine the associations between sarcopenia, sarcopenia parameters, and MCR among community-dwelling Chinese older adults.2), and five-times sit-to-stand test time (FTSSTT). MCR was defined as subjective cognitive complaints and slow gait speed without dementia or impaired mobility. The associations between sarcopenia, sarcopenia parameters, and MCR were conducted using the logistic regression model. The restricted cubic spline with four knots were performed to determine the nonlinear and linear relationships between HGS, ASM/Ht2, FTSSTT, and MCR.A total of 4,184 community-dwelling older adults from the China Health and Retirement Longitudinal Study (CHARLS) in the 2011 waves were included. Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia criteria. Sarcopenia parameters included handgrip strength (HGS), height-adjusted appendicular skeletal muscle mass , p = 0.001], and more FTSSTT  were significantly associated with a higher risk of MCR. There was an inverse linear dose–response between HGS and MCR . The nonlinear relationship between FTSSTT and MCR was found  with FTSSTT ≥29 s being associated with a higher risk of MCR. A dose–response relationship was not found between ASM/Ht2 and MCR .The prevalence of MCR in wave 2011 of CHARLS was 11.2%. After adjustment for potential confounders, we found sarcopenia [odd ratio (OR) (95% CI): 1.70 (1.13 ~ 2.54), Sarcopenia, lower HGS, and higher FTSSTT are associated with MCR among older adults in China, while the latter two exhibit a dose–response relationship with MCR. It is suggested that timely identification and management of sarcopenia and its parameters may help delay the progression of cognitive impairment and promote healthy aging. Given nSarcopenia is a severe geriatric syndrome, mainly defined by an age-related loss of muscle mass and muscle function . Substan2), five-times sit-to-stand test time (FTSSTT), and MCR by the cubic spline analysis.To fill these gaps, we first conducted cross-sectional analyses to investigate the association between sarcopenia and MCR in the middle-aged and older Chinese population using the nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS). Then, we aimed to determine the potential dose–response relationships between sarcopenia parameters, including HGS, height-adjusted appendicular skeletal muscle mass  age ≥ 60 years old ; (2) completing MCR information in baseline; (3) completing sarcopenia information in the baseline; (4) completing covariates in the baseline. 2.22.2.12, and FTSSTT. HGS (kg) was measured by the participant squeezing a Yuejian TM WL-1000 dynamometer twice as hard as possible by holding the dynamometer at a right angle (90°) (2 (kg/m2). Appendicular skeletal muscle mass using a validated anthropometric equation in Chinese residents  as the index of physical function in sarcopenia. The FTSSTT ≥12 s is the poor physical performance cut-off value (According to the diagnostic criteria recommended by the Asian Working Group for Sarcopenia (AWGS) in 2019, sarcopenia was defined as low muscle mass plus low muscle strength or physical performance . Sarcopele (90°) . HGS wasle (90°) . The musesidents . The agresidents . The cutpulation . Therefoff value . Furtherff value .2.2.2MCR syndrome was defined as cognitive complaints and slow gait speed without dementia or impaired mobility. Our study assessed cognitive complaints using a self-reported questionnaire about memory loss: “How would you rate your memory at present?” Respondents were asked to rank their answers on a scale of five: “excellent,” “very good,” “good,” “fair,” and “poor.” Those who reported “fair” or “poor” were recorded as having cognitive complaints. Gait speed was used to assess physical performance, computed by the average time respondents took to walk along a straight 2.5 m path twice. The cut-off slow gait speed was 1.0 standard deviations or below age  and sex  appropriate mean values of gait speed in our cohort  Supplem.2.2.3All covariates were obtained at baseline. We included covariates associated with sarcopenia or MCR reported in previous research . Sociode2.3Characteristics of participants were presented as means ± standard deviations for continuous and frequency with percentage for categorical variables, respectively. The normal distribution was assessed by histogram. Differences between participants with and without MCR were compared using independent sample t-tests, the Mann–Whitney U test for continuous variables, and the chi-square test for categorical variables.Logistic regression models were applied to estimate the association between sarcopenia, sarcopenia parameters, and MCR. Four models were fitted. Model 1 adjusted for age and gender. Model 2 adjusted for the covariates in Model 1 plus marital status, residence, education, smoking status, drinking status, and sleep time. Model 3 adjusted for the covariates in Model 2 plus hypertension, diabetes, heart disease, stroke, CES-D scores, and fall. Model 4 adjusted for the covariates in Model 3 plus BMI.2, FTSSTT, and MCR. The nonlinearity test was performed using the analysis of variance (ANOVA). Nonlinear relationships were defined as p lower than 0.05. The restricted cubic spline with four knots was performed to determine the nonlinear and linear relationships between HGS, ASM/Ht2, FTSSTT, and MCR. The confounders  were considered in the model.We further analyzed the dose–response relationships between sarcopenia parameters, including HGS, ASM/HtAll statistical tests were represented as the odd ratio (OR) with 95% confidence interval (CI). All analyzes were conducted using IBM SPSS version 26.0 and R statistical software.33.1Among 4,148 participants, 463 (11.2%) individuals had MCR, 3490 (83.4%) individuals had subjective cognitive complaint, 533 (13.2%) individuals had gait slowing and 604 (14.6%) individuals were absence of SCD and gait slowing. The mean age of study participants was 67.3 ± 6.1 years, and 47.7% were female.p = 0.006) and had a higher proportion of divorced/widowed/single (p = 0.010) than partnered. We found no difference between sex distribution and MCR status. Participants with MCR had slightly lower sleep time (p < 0.001), lower BMI scores (p = 0.011), and higher CES-D scores (p < 0.001). No significant difference in other sample characteristics was found between those with and without MCR. The prevalence of MCR in baseline participants was 16.4% (84/511) in sarcopenia and 10.3% (379/3673) in non-sarcopenia.The descriptive characteristics of the participants are shown in 3.22, although it was significantly related to MCR in the crude model, it was not significantly associated with MCR  after adjusting for demographics covariates.3.32, we did not find a dose–response relationship between ASM/Ht2 and MCR . Regarding the FTSSTT, we found a direct nonlinear dose–response association between the FTSSTT and MCR , with the rate slowly at first and fast afterward. The FTSSTT is estimated at 29 s while the OR = 1.4Based on nationally representative data of older Chinese adults, our study found that MCR was significantly associated with sarcopenia and the muscle function part of sarcopenia parameters, including HGS and FTSSTT. Results were still robust after controlling for the covariates associated with MCR and sarcopenia. Furthermore, we found a significant linear dose–response relationship between the HGS and MCR and a significant nonlinear dose–response relationship between the FTSSTT and MCR.To our knowledge, this is the first large nationally representative study highlighting the significant association between MCR and sarcopenia, assessed by using the AWGS 2019 criteria. Our outcomes were consistent with previous studies conducted in 846 Chinese community-dwelling older adults  and 397 Importantly, we further evaluated the dose–response relationship between MCR and sarcopenia parameters. We found significant linear or nonlinear dose–response relationships between HGS, FTSSTT, and MCR, indicating more details and improving a deeper comprehension of the relationships. The increased odds of MCR linearly (SD) related to the decrease in HGS and nonlinear related to the increase in FTSSTT slowly at first and fast afterward. Precise trajectory shapes strengthened the robustness of significant associations between sarcopenia parameters and MCR. In addition, the cut-off point of FTSSTT was 29 s. While the value was above 29 s, the FTSSTT might be recognized as a risk factor for MCR. It is clinically significant to screen for MCR when the FTSSTT is 29 s and above.The underlying mechanisms of sarcopenia involved in MCR have not been determined. It is suspected that both shared common risk factors , includiThere are several strengths of our study. Based on a large and nationally representative survey in China, our study made the results more generalized and reliable. In addition, to our knowledge, this study constitutes the first attempt to determine the dose–response relationships between sarcopenia parameters and MCR and clearly showed trajectories of the relationship between MCR and sarcopenia parameters. More importantly, our findings supported the validity of the primary algorithm of muscle function in sarcopenia diagnosis. Nevertheless, there are some limitations to this study. First, it is still potential that other confounding factors are omitted, although we have tried our best to include covariates based on prior knowledge as much as possible. Further, due to the limited sample of CHARLS, we did not investigate physical activity as an essential. Second, some people who did not complete the survey were excluded, potentially causing selection bias. Third, given the limitations of records available in the CHARLS, some variables were assessed by self-report , which might be subject to recall bias.5We demonstrated that sarcopenia, lower HGS, and higher FTSSTT are associated with higher MCR risk among Chinese adults aged 60 and above. Furthermore, significant inverse and linear dose–response relationships between HGS and MCR, as well as a significant direct nonlinear relationship between FTSSTT and MCR. Nevertheless, it is recommended that timely identification and management of sarcopenia and its parameters, particularly the FTSSTT, may be beneficial to prevent the incidence of MCR, delay the progression of cognitive impairment, and promote healthy aging.http://charls.pku.edu.cn/en.Publicly available datasets were analyzed in this study. This data can be found at: The studies involving humans were approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.DJ: Conceptualization, Formal analysis, Writing – original draft. XC: Conceptualization, Formal analysis, Writing – original draft. JH: Visualization, Writing – review & editing. LW: Writing – review & editing, Data curation. YC: Writing – review & editing, Data curation. HF: Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing. MH: Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing.