Background: Heart rate fragmentation (HRF), a new non-invasive metric quantifying cardiac neuroautonomic function, is associated with increasing age and cardiovascular disease. Since these are risk factors for cognitive decline and dementia, in the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether disrupted cardiac neuroautonomic function, evidenced by increased HRF, would be associated with worse cognitive function assessed concurrently and at a later examination, and with greater cognitive decline.Methods: HRF was derived from the ECG channel of the polysomnographic recordings obtained in an ancillary study  conducted in conjunction with MESA exam 5 (2010–2012). Cognitive function was assessed at exam 5 and 6.4 ± 0.5 years later at exam 6 (2016–2018) with tests of global cognitive performance , processing speed  and working memory (Digit Span). Multivariable regression models were used to quantify the associations between HRF indices and cognitive scores.Results: The participants’ mean age was 68 ± 9 years . Higher HRF at baseline was independently associated with lower cognitive scores at both exams 5 and 6. Specifically, in cross-sectional analyses, a one-standard deviation (SD) (13.7%) increase in HRF was associated with a 0.51 (95% CI: 0.17–0.86) points reduction in CASI and a 1.12 (0.34–1.90) points reduction in DSC. Quantitatively similar effects were obtained in longitudinal analyses. A one-SD increase in HRF was associated with a 0.44 (0.03–0.86) and a 1.04 (0.28–1.81) points reduction in CASI and DSC from exams 5 to 6, respectively. HRF added predictive value to the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE-APOE-ε4) risk score and to models adjusted for serum concentration of NT-proBNP, an analyte associated with cognitive impairment and dementia.Conclusion: Increased HRF assessed during sleep was independently associated with diminished cognitive performance (concurrent and future) and with greater cognitive decline. These findings lend support to the links between cardiac neuroautonomic regulation and cognitive function. As a non-invasive, repeatable and inexpensive probe, HRF technology may be useful in monitoring cognitive status, predicting risk of dementia and assessing therapeutic interventions. Risk assessment of cognitive impairment is a major public health priority, especially given the increasing prevalence of dementia syndromes in the aging population. A key barrier to progress is the lack of reliable, quantitative and non-invasive methods that complement expensive brain imaging technologies, semi-quantitative functional tests of cognitive status as well as emerging biochemical and “omics” probes. Important insights into the pathophysiology of cognitive impairment syndromes derive from increasing evidence linking central nervous system dysfunction with perturbations in autonomic function . The majamplitude of variations in sinus normal-to-normal (NN) intervals with the degree of vagal tone modulation , which helps resolve this paradox. Heart rate fragmentation metrics quantify variations in NN intervals due to non-respiratory sinus arrhythmia and other anomalous dynamical variants. We previously reported that: (i) HRF monotonically increases with cross-sectional age both in healthy subjects and in those with coronary artery disease , a major cardiovascular (CV) risk factor also reported to be associated with dementia   disease  and inci disease  in the M disease  and CHARsease  were obtained from an ancillary sleep study conducted in 2010–2013 in conjunction with MESA’s fifth examination. The study included 2,237  participants, who underwent in-home overnight polysomnography (PSG) following a standardized protocol . Two thon = 33), electronic pacemaker (n = 14), missing annotations for sleep stage or QRS complexes (n = 14), <2 h of combined sleep periods scored as rapid eye movement (REM) or non-REM (n = 14), in AF at the time of the PSG (n = 22), prevalent dementia as defined below (n = 23), missing information on dementia status (n = 29) and those for whom (n = 11) the last recorded follow-up for AF events was prior to the PSG study. Overall, HR dynamical measures were calculated for 1,897 participants.The PSG data were scored at a centralized sleep reading center in accordance with published guidelines , 2007. TIn addition to clinical exams, MESA participants were contacted by telephone every nine to twelve months to obtain information about hospital admissions and medical events. For those over age 65 and enrolled in fee-for-service Medicare, claims data were also used to identify diagnosis and procedure codes. Trained personnel abstracted any hospital records suggesting possible CVEs, which were then adjudicated by the MESA Morbidity and Mortality Committee. Non-fatal endpoints in MESA include congestive heart failure, angina, myocardial infarction, percutaneous coronary intervention, coronary bypass grafting or other revascularization procedure, resuscitated cardiac arrest, peripheral arterial disease, stroke (non-hemorrhagic) and transient ischemic attack. Cardiovascular deaths, as adjudicated by committee review, included fatalities directly related to stroke or coronary heart disease. The definition and adjudication of these events have been previously described . The ideIn MESA , three dn = 12) and those missing responses to more than three questions (n = 9) were also considered invalid. Overall, analyses with exam 5 CASI, DS forward, DS backward and DSC scores included 1,823 (96%), 1,881 (99%), 1,884 (99%) and 1,715 (90%) of the 1,897 participants for whom HR dynamical indices were calculated. Participants in the MESA-Sleep cohort with missing or invalid vs. valid DSC scores were on average two years older, had significantly higher systolic blood pressure (BP) and body mass index (BMI) values. A higher percentage had had a CVE (12.5 vs. 8.6%). Their degree of HRF was significantly higher (PNNSS: 68.3 vs. 65.6%).We excluded participants with missing or invalid cognitive scores due to physical  impairments that interfere with performance, language barriers, and circumstantial reasons, such as answering a cell phone call during a test. In the case of CASI, tests with a score <20  of participants in MESA 2 < 90%), and the oxygen desaturation index (ODI), defined as the number of oxygen desaturations ≥ 3% per hour of sleep. The CAC scores, derived from computed tomography imaging using the Agatston method  smoking status, and medication use were self-reported. Systolic and diastolic BPs were measured three times after the participant rested for five minutes; the means of the last two measurements were used here. Diabetes was defined by a fasting blood glucose ≥126 mg/dL or self-reported use of antidiabetic medication. Antihypertensive medication included beta-blockers, calcium channel blockers, angiotensin converting enzyme inhibitors or receptor blockers, vasodilators and diuretics. Depression was defined as a score of more than 15 points in the Center of Epidemiological Studies Depression scale. Antidepressant medication included tricyclic and non-tricyclic (other than monoamine oxidase inhibitors) medications accompanied or not by antipsychotic medications. Alcohol use (a binary variable: yes/no) was defined as consuming ≥ 1 glass of wine or the equivalent per week. Physical activity, defined as the number of metabolic equivalent minutes per week of intentional moderate and vigorous activity, was quantified using the MESA Typical Week Physical Activity Survey, adapted from the Cross-Cultural Activity Participation Study . APOE isn method , was ava  sinus, premature supraventricular or premature ventricular complexes. The sequence of normal-to-normal (NN) intervals between sleep onset and sleep termination were extracted for computation of HRF and traditional HRV indices.The ECG channels of the PSG recordings obtained at MESA ti represent the time of occurrence of a given QRS complex and NNi the time interval (i – ti–1t) between consecutive QRS complexes. Heart rate acceleration, deceleration and no-change intervals (in seconds) are defined as ΔNNi ≤ –n/SF, ΔNNi ≥ n/SF and –n/SF < ΔNNi < n/SF, respectively, where ΔNNi = NNi – NNi–1, n is a positive integer  and SF is the sampling frequency (in Hz) of the ECG signal.  Sequences of negative (positive) ΔNN intervals are termed accelerative (decelerative) segments. The length of a segment is the number of ΔNN intervals it contains.Heart rate fragmentation was quantified by an ensemble of statistical metrics derived from the analysis of NN interval time series, as described in i interval is an inflection point if ΔNNi+1 ×ΔNNi ≤ 0 and ΔNNi+1 ≠ΔNNi. The overall percentage of ΔNN intervals in long segments, PNNLS, is the number of ΔNN intervals in accelerative/decelerative segments with ≥3 ΔNN intervals over the total number of ΔNN intervals. The percentage of ΔNN intervals in short segments, PNNSS, is the number of ΔNN intervals in accelerative/decelerative segments with <3 ΔNN intervals over the number of ΔNN intervals in accelerative/decelerative segments of any length. More fragmented time series have higher PIP and PNNSS values, and lower PNNLS values.We computed three inter-related indices of overall degree of fragmentation . Briefly, PIP, the percentage of “inflection points,” is defined as the combined percentage of transitions from HR acceleration to HR deceleration and vice-versa (“hard” inflection points), and from HR acceleration/deceleration to no-change in HR and vice-versa (“soft” inflection points). Mathematically, a given NNmethod of time series analysis and HR variability to refer to the amplitude of the fluctuations (variability) in HR. (Mean HR is an HRV measure but not a measure of HR variability.) The source codes for HRV computations are available at www.physionet.org  were hypothesized to have (1) lower cognitive scores both at baseline and at exam 6, and (2) larger decreases in cognitive scores from exams 5 to 6.Participants with higher HRF, i.e., higher PIP and PNNSS values and lower PNNLS values, at baseline (exam 5) data. The latter used MESA-Sleep data, our baseline, and MESA exam 6 data obtained 6.4 ± 0.5 (mean ± SD) years later.  Continuous variables are summarized as median and interquartile range, unless otherwise indicated. Categorical variables are presented as numbers and percentages. Differences in baseline characteristics between those with and without cognitive testing at exam 6 were evaluated using the χ2 and Mann-Whitney tests for categorical and continuous variables, respectively. Differences in baseline characteristics across quartiles of PNNSS were assessed using the χ2 and the ANOVA tests for categorical and continuous variables, respectively. Variables with skewed distributions  were transformed using the natural logarithm. In the case of the last three measures, we added 1 to the variables’ values before the logarithmic transformation due to the occurrence of 0 values.This presentation includes both cross-sectional and longitudinal analyses. The former used MESA-Sleep  Risk Score with APOE-ε4 (CAIDE–APOE-ε4), a validated tool to predict late-life dementia risk (20 years later) , alcohol consumption, weekly amounts of moderate and vigorous physical activity, depression, usage of antidepressant medications, total gross family income ≥ $75,000, mean HR and prevalent CV and AF events. Model 5, was further adjusted for NT-proBNP  . Model 3T-proBNP . FinallyC scores , % SWS . These analyses were adjusted for the covariates detailed above in addition to baseline cognitive test scores. Of note, the regression of ΔY = Y2– Y1 on both Y1 and X is equivalent to the regression of Y2 on Y1 and X .The likelihood ratio test was used to evaluate the difference in performance between two nested models. The larger model contained an HRF index in addition to the variables in the base model. A statistically significant result for the likelihood ratio test indicates that the addition of the HRF index to the base model significantly increased its fit, i.e., its predictive value. Statistical significance was set at a exam 5 who did not undergo the sleep examination were relatively younger , less likely to be hypertensive (58% vs. 62%), and more likely to be Hispanic (23.5% vs. 19.1%) [19]. They had lower CAC scores (median [inter-quartile range]: 30 [0–215] vs. 57 [0–338]) and higher DSC scores (52 [39–65] vs. 50 [37–62]). There were no differences in sex, BMI, smoking status, diabetes, number of participants with prevalent CV disease, and in the results of the two other cognitive tests, CASI and the DS.Participants in the MESA-Sleep cohort compared to those enrolled in exam 6. subgroup A) and without (subgroup B) cognitive testing at exam 6. Participants in subgroup A had higher cognitive test scores at exam 5. They were approximately three years younger and healthier overall.Approximately 50% of the participants in the MESA-Sleep cohort underwent cognitive testing at exams 5 and 6.Model 4. Heart rate fragmentation indices were more strongly associated with the DS backward than the DS forward scores. The associations of HRF indices with DS backward scores were significant in Models 1–3 and borderline significant in the two most adjusted models. The associations between HRF indices and DS forward scores were only significant in unadjusted analyses and those adjusted for the CAIDE–APOE-ε4 risk index. Further adjusting the previous analyses for NT-proBNP did not qualitatively change any of our results.In all models, the three HRF indices were strongly associated with the CASI and the DSC scores . The ass2 values of Models 4 (0.325) and 5 (0.326) were only 2% higher than that of Model 3 (0.307). Of note, despite including information on the strongest predictors of cognitive performance, namely age, sex and education, the model with the CAIDE–APOE-ε4 risk index had an adjusted R2 of only 0.072 (75% lower than that of Model 3).The CAIDE–APOE-ε4 risk index attenuated the associations between HRF indices and the cognitive test scores only slightly. In contrast, age, sex, race and education reduced the strength of these associations between 40% and 70%. Additional adjustments had only a relatively small effect. Consistent with these observations is the finding that the adjusted Rp < 0.10) and the DSC (p < 0.05) scores  was positively associated with CASI (Appendix . None ofp < 0.05), DSC (p < 0.05), DS forward (p < 0.1) and DS backward (p < 0.05) scores obtained at exam 6, 6.4 ± 0.5 (mean ± SD) years after exam 5. In fully adjusted analyses, a one-SD increase in PNNSS (13.7%) was associated with −0.61 (95% CI: −1.07 to −0.14), −1.54 (−2.54 to −0.54), −0.14 (−0.31 to 0.02) and −0.17 (−0.31 to −0.04) points decrease in the CASI, DSC, DS forward and DS backward scores, respectively.Heart rate fragmentation indices were associated  with theThere were relatively few (13 out of 80) significant or borderline significant associations between the HRV indices and the cognitive scores Appendix . NotablyThe HRF indices were strongly associated with the changes in cognitive scores . Overallaccelerated with the participants’ age as well as with baseline degree of HRF. In the time period between exams 5 and 6, cognitive performance decreased more for older than younger participants. Similarly, in the same time period, cognitive performance decreased more for participants with higher degrees of HRF. Of note, the associations between HRF and the changes in cognitive scores were not dependent on the participants’ age .In fully adjusted models, a one-SD increase in PNNSS was associated with a decrease of −0.44 (95% CI: −0.86 to −0.03), −1.04 (−1.81 to −0.28), −0.13 (−0.27 to 0.01) and −0.14 (−0.25 to −0.03) points in the CASI, DSC, DS forward and DS backward scores, respectively. There were few (5 out of 80) significant or borderline associations between HRV indices and the longitudinal changes in cognitive scores Appendix . In fullModel 3, open symbols), and the other “fully” adjusted . Specifically, the figure shows the standardized ß coefficients for the associations of PNNSS (blue symbols) and rMSSD (red symbols) with cognitive scores at exams 5 and 6 and the changes in cognitive scores.p < 0.05 or p < 0.1) with the lower cognitive scores at exams 5 and 6 and with larger decrements in scores from exams 5 to 6. Model 4) for CAC, measures of sleep structure (the percentage of time in REM and the percentage time in SWS), a measure of sleep disorder breathing (AHI), and measures of hypoxemia (ODI and the % of time SpO2 < 90%) did not qualitatively change our results (not shown). Finally, we note that no interactions by sex or race were detected in any of the cross-sectional or the longitudinal analyses previously described.Of note, further adjusting the cross-sectional and longitudinal analyses described above (exam 5 (our baseline) using previously described metrics ; (4) HRF metrics added predictive value to the CAIDE–APOE-ε4 risk index and to models with a combination of risk factors for cognitive impairment including NT-proBNP serum concentration; (5) slower HR was cross-sectionally associated with the CASI and DSC scores, and prospectively associated with the DS backward scores; and (5) the HRV indices rMSSD, SDNN and HF power were not cross-sectionally or longitudinally associated with cognitive scores.Our key findings were: (1) in cross-sectional analyses, HRF was inversely associated with all cognitive scores other than the DS forward scores ; (2) in prospective analyses, HRF was inversely associated with all cognitive scores; (3) HRF was associated with the increased degree of HRF was associated with both worse concurrent and future cognitive function. Our analyses also showed that increased baseline HRF was associated with steeper future cognitive decline. For example, in fully adjusted analyses (vs. 60% lost twice the number of points in the DS backward test from exams 5 to 6 [0.44 (0.27–0.60) vs. 0.23 (0.12–0.35) points]. Similarly, we found that older age was associated with greater cognitive decline – the older the participants the larger the longitudinal decrease in cognitive scores. For example, in fully adjusted analyses (exams 5 to 6 for participants aged 75 vs. 65 was approximately twice as high [0.51 (0.35–0.68) vs. 0.23 (0.11–0.34) points]. The results are consistent with the acceleration of cognitive decline with aging as well as with baseline degree of HRF.Overall, our results indicate that an analyses , particianalyses , the decIn both cross-sectional and longitudinal analyses, HRF added predictive value to the CAIDE–APOE-ε4 dementia risk index . This inWe found that HRF was significantly associated with cognitive performance  independent of a combination of widely acknowledged risk factors of cognitive impairment including demographic , socioeconomic , genomic , behavioral , mental health (depression) variables, and CV risk factors . Moreover, HRF added predictive value to models that in addition to the variables mentioned above also included serum concentration of NT-proBNP. This analyte has been reported to be associated with incident dementia in MESA  and otheOur findings are consistent with proposed links between cardiac neuroautonomic regulation and cognitive function . AlthougA second and related possibility is that cardiac neuroautonomic impairment affects cognitive performance via its contribution to arterial BP dysregulation, encompassing but not limited to degraded baroreflex sensitivity . The resA third putative link between cardiac autonomic dysfunction and cognitive impairment is via pathologic alterations in neuro-immunomodulation. The role of the vagus in regulating systemic inflammatory response and tissue damage at multiple anatomic sites has emerged as a major area of investigation . The salOf further note, evidence that parasympathetic disruption may be initiated and perpetuated by peripheral and central neurodegenerative changes seen with aging, CV disease, as well as subclinical Alzheimer’s disease, suggests that HRF may have additional value as a predictor of incident dementias.amplitude of HR fluctuations, as quantified by traditional HRV metrics, was not consistently associated with cognitive performance. Other large epidemiologic studies have also investigated the associations between HRV indices, as putative measures of neuroautonomic function, and cognitive test scores. The results are difficult to reconcile. Some report positive associations  to deceleration (expands) and vice-versa. In this study, we found that the ciations  between ciations .These discrepancies are likely due to the limitations of traditional HRV metrics themselves , namely not distinguishable using traditional HRV measures. This limitation undermines the reliability and translational value of these metrics ,-ε4 allele carriage, the possibility of residual confounding could not be excluded. However, we did try to minimize such possibility by further adjusting the models for CAC, NT-proBNP, sleep structure and hypoxemia variables, which have themselves been associated with incident CV and AF events and/or cognitive decline. We note that the participants who underwent cognitive testing at exam 6 (only 53% of those in our MESA-Sleep study cohort) were on average three years younger and overall healthier than those who did not. Furthermore, at exam 5, participants who would be re-tested at exam 6 performed significantly better in all cognitive tests. Despite this selection bias and the lower statistical power for the longitudinal analyses compared to the cross-sectional ones, our results were still significant. Our findings will need to be validated in other populations.In MESA, assessment of cognitive function is limited to three standard tests, CASI, DSC and DS, which only probe selected cognitive domains. Another limitation is the fact that despite adjusting our analyses for demographic, socioeconomic and behavioral variables, in addition to socioeconomic status, traditional CV risk factors and APOEIn MESA, higher degree of HRF, a marker of cardiac neuroautonomic impairment, was cross-sectionally and prospectively associated with worse cognitive performance. Furthermore, cognitive decline; accelerated with age as well as baseline degree of HRF . The potential translational utility of these findings is enhanced by the observation that HRF added predictive value to well-known risk factors of cognitive decline, such as age and subclinical CV risk markers.hansenk3@u.washington.edu.The data analyzed in this study is subject to the following licenses/restrictions: MESA data can be accessed after submitting a manuscript proposal to MESA Publications & Presentations Committee and obtaining its approval to conduct the research work. Requests to access these datasets should be directed to Karen Hansen, Institutional review boards approved the conduct of the study. Written informed consent was obtained from all participants.MC, SH, and AG: conception and research design. SR (PSG), SH, and TH (cognitive scores): data acquisition. MC: data analysis and preparation of tables and figures. MC and AG: manuscript drafting. All authors: interpretation of results and manuscript editing.SR reports consulting fees from Apnimed Inc., Jazz Pharma and Eisai Inc., unrelated to this work, grant funding from Jazz Pharma unrelated to this work and receipt of loaned equipment from Nox Medical Inc. and Philips Respironics for use in an NIH trial. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Ammonia is a key component in the pathogenesis of hepatic encephalopathy. Branched-chain amino acids (BCAA) have been reported to improve the symptoms of HE induced by hyperammonemia; however, we recently reported that ammonia increases intracellular levels of BCAA and exerts toxic effects on astrocytes.  This follow-up study was designed to confirm the direct effects of BCAA on human astrocytes and clarify their underlying mechanisms using metabolome analysis and evaluation of associated signaling. 4Cl) and then compared the results with the effects of BCAA on hepatocytes and neurons. Subsequently, we used metabolomic analysis to investigate intracellular metabolite levels in astrocytes with and without BCAA treatment.  We performed cytotoxicity and cell proliferation tests on astrocytes following BCAA treatment with and without ammonium chloride (NHβ and mTOR in astrocytes.  The astrocytes showed increased leakage of intracellular lactate dehydrogenase and reduced proliferation rate upon BCAA treatment. Interestingly, our analysis showed a BCAA-induced impairment of intracellular glycolysis/glyconeogenesis as well as amino acid and butyric acid metabolism. Furthermore, BCAA treatment was found to cause decreased levels of Glut-1 and phosphorylated GSK-3 Although further investigations of the effect of BCAA on human astrocytes with hyperammonemia are needed, our work demonstrates that BCAA supplementation has direct negative effects on astrocyte survival and intracellular metabolism. Plasma and brain amino acid (AA) imbalance, particularly low concentration of branched-chain amino acids (BCAA) and high concentration of aromatic amino acids (AAA) in plasma, closely participates in the pathogenesis of hepatic encephalopathy (HE) in liver cirrhosis (LC) and/or portal-systemic shunt, resulting in the disturbance of neurotransmission in the brain . In geneAstrocytes play important roles in central nervous system (CNS) function and in maintaining the BBB through their “end feet,” which interact with the structural components of the barrier. Recent studies have found that astrocytes determine both the functional and structural architecture of the adult brain . AstrocyAmmonia is a key substance in the pathogenesis of HE , 11. We Previous research has highlighted the importance of evaluating the effects of BCAA overdose on the brain to determine BCAA threshold values for adverse effects . HoweverIn this study, we aimed to shed light on the direct effects of BCAA on astrocyte survival and to identify the mechanism underlying the function of BCAA.4Cl) was purchased from Sigma , and BCAA  was kindly supplied by Ajinomoto Pharma Co. Ltd., Tokyo, Japan.The human astrocyte cell line Cryo NHA (CLCC-2565) was purchased from Lonza Walkersville, Inc. . Cells were grown in a medium based on the AGM Bullet Kit (CC-3186) from the abovementioned company. The human hepatoblastoma cell line HepG2 was grown in DMEM supplemented with 10% fetal bovine serum . The mouse neuronal cell line HT22 was kindly provided by Dr. Takumi Satoh . Cells were grown in BCAA-free medium prior to BCAA treatment. Ammonium chloride (NH4 cells/sample) were treated with BCAA. Astrocytes were also treated with NH4Cl, BCAA, and a mixture of NH4Cl and BCAA. After 18 h of treatment, the number of viable astrocytes was evaluated using Cell Count Reagent SF , as previously described [μL of Cell Count Reagent SF was added to each well containing cultured astrocytes in 100 μL medium. Cells were incubated for 1 h, and then, absorbance was measured at 450 nm using a microplate photometer . Changes in cell number were arbitrarily represented using the optical density ratio, defined as the number of stimulated cells divided by that of control cells.Astrocytes, HepG2, and HT22 (1 × 104 cells/sample) were treated with NH4Cl, BCAA, and a mixture of NH4Cl and BCAA. After 4 h of treatment, LDH activity was detected using an LDH Cytotoxicity Assay Kit . Absorbance was read at 490 nm using a microplate reader .Astrocytes (5 × 106 cells/sample) was used for the extraction of intracellular metabolites. The culture medium was aspirated from the dish, and cells were washed twice with a 5% mannitol solution (10 mL first wash and 2 mL second wash). The cells were treated with 800 μL of methanol and left at rest for 30 s to inactivate enzymes and extract the metabolites, according to the manufacturer's instructions. Next, the cell extracts were treated with 550 μL of Milli-Q water containing internal standards  and left at rest for another 30 s. The extract was centrifuged at 2,300 × g for 5 m at 4°C, and 800 μL of the upper aqueous layer was centrifugally filtered through a Millipore 5 kD cutoff filter at 9,000 × g for 120 m at 4°C to remove proteins. The filtrate was concentrated through centrifugation and resuspended in 50 μL of Milli-Q water for the Capillary Electrophoresis Time-of-Flight Mass Spectrometry (CE-TOFMS)  analysis. The detailed methods for CE-TOFMS have been described in previous publications [Metabolomic screening was carried out through a facility service at Human Metabolome Technology (HMT) Inc., Tsuruoka, Japan. The experiment was carried out as described previously . Astrocyications , 20.m/z, migration time for CE-TOFMS measurements (MT), and peak area. Signal peaks corresponding to adduct ions and other products of known metabolites were excluded, and the remaining peaks were annotated as putative metabolites and their isotopic ions from the HMT metabolic database based on their MT and m/z values determined by TOFMS. The tolerance range for the peak annotation was configured at ±0.5 m for MT and ±30 ppm for m/z. In addition, peak areas were normalized against those of the internal standards, and the resultant relative area values were further normalized to sample amounts.Peaks were extracted using the automatic integration software MasterHands  to obtain peak information, including β, and p-mTOR . The antibody against β-actin was purchased from Santa Cruz Biotechnology . Immunoreactive bands were visualized with an enhanced chemiluminescence reagent  and quantified using ImageJ software.Standard Western blotting was carried out as described previously . Total pn = 3). All data are expressed as the mean ± standard deviation. Group comparisons were performed using Welch's t-test. Significance was defined as p < 0.05.Three technical replicates were set for each experiment (p < 0.05) in LDH leakage (p < 0.05) in viability compared with that of nontreated (control) cells  cells . Concernp < 0.05) in the 2,3-diphosphoglyceric acid level, metabolites including fructose-1,6-diphosphate, phosphoenolpyruvic acid, and acetic acid, which are critical in glycolysis/glycogenesis mechanisms, were significantly decreased (p < 0.05) in BCAA-treated cells, compared to the control. As for energy carriers participating in ATP generation, which is the major function of mitochondria, despite ATP and NAD+, which showed no obvious difference between the BCAA-treated and nontreated cells, all other components including ADP, fumaric acid, NADH, and succinic acid were significantly decreased (p < 0.05) upon BCAA treatment. In addition, metabolites of the tricarboxylic acid (TCA) cycle, such as malic acid, fumaric acid, and succinic acid, showed a significant decrease in BCAA-treated cells  because of the high cost of the metabolism assay. Further studies should be conducted to completely understand the effects of BCAA on intracellular metabolism.Metabolome analysis using blood and tissue samples has recently been developed, allowing to comprehensively evaluate the pathways of carbohydrate, AA, nucleotide, and lipid metabolism , 31. Howin vivo observations indicating that astrocytes are primarily responsible for glucose uptake in the brain [Astrocytes play a central role in controlling brain energy metabolism; this is supported by he brain  and thathe brain . In thisIn addition, we found evidence of decreased ALC levels upon BCAA treatment, which suggests a disturbance in intracellular carnitine metabolism. Carnitine deficiency has been proven to result in HE ; ALC plaIn conclusion, although BCAA supplementation for HE treatment caused by LC and/or portal-systemic shunt has benefits that improve consciousness levels , the pre


To describe the pattern of comorbidities in school-aged children with cerebral palsy (CP) and to identify which, if any, were associated with poor school attendance.A cross-sectional study, using the key informant methodology, between December 2017 and July 2018 was conducted in Cross River State, Nigeria. Assessments, confirmation of CP and identification of systemic comorbidities using standard tools and questionnaires were performed. Children confirmed to have CP between the ages 4 to 15 years were included.p < 0.001; CI: 3.6–28.1), visual acuity impairment , epilepsy  manual ability classification scale 4–5  and CP severity (GMFCS V-VI) OR 6.9 p = 0.002, CI: 2.0–24.0.) were seen as increasing the likelihood of poor school attendance.Three hundred and eighty-eight children were confirmed to have CP, 59% males. The mean age was 9.2 years ± SD 4.0; 28% were non-ambulatory (gross motor function classification system (GMFCS) level IV-V) and spastic CP was seen in 70%. Comorbidities included Speech impairment 85%, feeding difficulties 86%, and swallowing difficulties 77%, learning difficulties 88%, abnormal behaviour 62%, visual acuity impairment 54%, objective perceptual visual disorders 46%, communication difficulties 45%, epilepsy 35%, hearing impairment 12% and malnutrition 51%. Learning difficulties (OR 10.1, Comorbidities were common, and some were associated with limited school attendance. A multidisciplinary tailored approach to care, with application of available therapeutic interventions for comorbidities is suggested. This may be useful in reducing barriers to school attendance.The online version contains supplementary material available at 10.1186/s12887-021-02637-9. Cerebral palsy (CP) is a leading cause of childhood disability across the world with significant impact on function and development . The defChildren with CP and disability in general face barriers and challenges to education . BarrierCo-morbidities may contribute to these barriers. Little evidence exists as to whether and which comorbidities are significant barriers to participation in schooling. Identification of these comorbidities may be important to attain effective individualized support measures for education.In Nigeria, there are strong regional disparities in education and socioeconomic indices, with the southern region of the country (where Cross River State is situated) performing better in indices, including of health, education and the millennium development goals . In the The aim of this study was to describe the comorbidities seen in children with CP in this community –based Nigerian population, and to identify which comorbidities were associated with poor school attendance.A population based cross sectional study was conducted in Cross River State (CRS) in Nigeria between December 2017 and July 2018 and has been reported in other articles –15.Primary and secondary education enrolment is compulsory; however, it is paid for by the government for children in the primary school, while the government subsidizes the examination fees for the secondary education. Located in every village is a primary school and in every local government area there is a state government secondary school and a mission secondary school. Enrolment into kindergarten is from 3 years old. Secondary school education is divided into junior secondary and senior secondary schools . There ap = 0.29%) and associated comorbidities [Existing data from this world region suggest a population prevalence of CP of 2.9 per1000 children and about the same estimate for associated comorbidities –19. Consbidities  with a lIn the absence of a cerebral palsy registry, the key informant methodology (KIM) was selected as the most cost effective sampling strategy to identify children with CP and other disabilities in our circumstances. Several researches have validated this method –24. The Identified and referred children were then assessed first of all by a paediatric neurologist in the primary health centre to determine if they met the inclusion criteria for CP. Families were provided with appropriate advice, information and counselling, referral services and intervention where appropriate. CP was defined according to history and neurological examination in line with international criteria . Gross MThe inclusion criteria included, children aged between 4 and 15 years of age at their last birthday, who were confirmed to have CP from history and clinical assessment by a paediatric neurologist . ExclusiComorbid conditions were confirmed by history, clinical and standardized evaluations. Comorbidities investigated included: epilepsy, hearing impairment, feeding difficulties, swallowing difficulties, visual acuity impairment, objective perceptual visual disorders, abnormal behaviour, learning difficulty, speech impairment, communication difficulties and malnutrition.The Lea symbols cut-off point for screening preschool children of 0.8 was used as score for normal visual acuity and > 0.8 were considered to have visual acuity impairment . ObjectiHearing impairment was assessed using three-level voice test (for children able to participate) and was present when a child failed to respond to mid-level spoken voice in either ear. Learning difficulty was assessed, by clinical history, assessment and behavioural observation , 31. TheParticipation in mainstream schooling was recorded alongside whether children were at expected levels within the school programme by parent’s report. Dropout in school was defined as the percentage of students failing to complete a particular school year or school program.Statistical analyses were performed using Stata 15 . Descriptive statistics were reported using means, standard deviations, medians, interquartile ranges, frequencies and percentages. Comparisons between categorical variables were performed using a chi-square test and logistic regression.Comorbidity score was calculated by summation of the frequencies of the following comorbidities: feeding, swallowing, hearing, speech, learning, visual acuity impairments and objective perceptual visual disorders. In addition to; malnutrition, communication difficulties, epilepsy and abnormal behaviours. This was followed by the calculation of the comorbidity mean.P < 0.05. Missing data if less than 30% were included as normal. The influence of co-morbidities and CP severity on school attendance was assessed in a bivariate analysis. Correlations between factors predicting school attendance were the sought.The Kruskal Wallis test was used to determine the association of comorbidity scores with the type of CP. Significance level was set at p < 0.2 level, or not significant at p > 0.2 but with an odds ratio between 0.5 and 2.0 in bivariate logistic regression were also included in the multivariate model. If 2 predictors showed a strong correlation with each other (0.7–1), then only one was included in the multivariate modelling. Age and sex were included regardless.Multiple logistic regression models, adjusted for age and sex, were developed to identify factors associated with poor school attendance. Variables included in the regression models included systemic comorbidities and severity of CP. These were chosen based on biological plausibility and findings from previous studies. In addition, a no selection procedure was used to include other factors: variables significant at A total of 1024 children were identified by the key informants, 343(34%) children referred did not have CP while (388/731(53%) were confirmed to have CP at that point in time. The mean age of the children with CP was 9.2 years (SD) ±4.0). There were 229 (59%) males and 159 (41%) females. Carers reported seeking treatment for CP first in the hospital in 56.7%.Ambulatory children (GMFCS I-III) made up 280/388 (72%) while GMFCS IV-V were 108(28%) of the children with CP. Spastic CP was the most common type , and was bilateral in 163/271(60%) and unilateral in 108(40%).Comorbidity distribution are shown in Table p < 0.001), were four times more likely in children with epilepsy. Irregular antiepileptic medications were used in 7/130(5.4%) children while others used none.Subcategories of abnormal behaviours included; Difficulties getting along with other children 240(63%), reduced kind & helpful behaviour 252(67%), hyperactivity and inattention 162(43%) and abnormal conduct 233(62%). Neonatal seizures 108/388(28%) , GMFCS IV-V, 83/108(77%) . Conversely a negative association was seen with both feeding, 161/334(48%)  and swallowing difficulties 140/299(47%) .Malnutrition was seen in 200/388(51%) and was associated with MACS 4–5, 62/88(70%);  = 10.921, p < 0·0275); Dystonic CP showed the highest number of co-morbidities; 7.4 . Children with more than 5 comorbidities accounted for 65% of children and at least 1 comorbidity was seen in every child , with the Kruskal-Wallis test showing a significant difference in the distribution of the co-morbidity scores between the CP clinical types  had never attended school, and 145 of the 273(53%) who started school dropped out; of the 128/388 (33%) in mainstream school, for 124/128 (97%) children, parents reported that the children were behind in academic performance. As at the time of recruitment, two thirds of children were not in school .R = 0.7) hence swallowing difficulties was deleted from the multivariate model.Of the reported bivariate predictors of school attendance only swallowing and feeding difficulties showed some correlation  and this study highlights that comorbidity is likely to be a major impediment to school attendance for children with CP in low and middle income countries which requires urgent attention.Additional file 1 Supplementary material 1. Number and frequency of comorbidities in children with CP (n = 388)


Pulmonary arterial hypertension (PAH) is a rare but life-limiting condition. Assessments of disease severity and prognosis are essential in the selection of treatment options and the timing of lung transplantation . Right vThis study aimed to determine the prognosis of patients with PAH based on patterns of RV adaption in PAH using RV volume and mass. Ethical approval by the North Sheffield ethics committee and review board approval was obtained (reference c06/Q2308/8).%pred)  Registry between May 12, 2009 to February 1, 2015 were included. The patients were followed up until census or death. RV end-systolic volume was measured on short-axis cine images, corrected for body surface area, adjusted for sex and age, and presented as: RV end-systolic volume index percentage predicted (RVESVI%pred) . Ventric%pred threshold of 227% (lowMasslow (low RVESVI%pred and low VMI), VollowMasshigh (low RVESVI%pred and high VMI), VolhighMasslow (high RVESVI%pred and low VMI), and VolhighMasshigh (high RVESVI%pred and high VMI). Kaplan-Meier plots, Cox regression analysis, and one-way analysis of variance were used to compare the prognoses and variables of different groups. Multivariate Cox regression analysis was used to identify prognostic indicators that were independent of volume/mass group. Subgroup analyses were performed in incident patients.The patients were divided into 4 different volume/mass groups using a RVESVI of 227%  and a me%pred  and VMI  had prognostic value.A total of 564 patients with PAH were identified; 250 (44%) died at follow-up (mean 5.0 ± 2.6 years). RVESVIlowMasslow, 84 VollowMasshigh, 85 VolhighMasslow, and 192 VolhighMasshigh. There were 69% of patients who had concordant remodeling (VollowMasslow and VolhighMasshigh) and 31% had discordant remodeling (VollowMasshigh and VolhighMasslow). VollowMasslow , VollowMasshigh  and VolhighMasshigh  had lower mortality than VolhighMasslow. One-way analysis of variance test showed that VolhighMasslow patients had the highest mean age (67 ± 13 years). At multivariate Cox regression analysis, VolhighMasslow group (p = 0.001) was independent of age, sex, World Health Organization functional class, and pulmonary vascular resistance. For the subgroup analysis of incident treatment-naive patients (n = 383), the threshold for VMI was 0.55. Complete RV mass and volume data were available for 550 patients who were included in the group comparison study. We excluded 14 patients (2.5%) due to missing data. The VMI threshold was 0.53 (median). The numbers of patients in each group were as follows: 189 VolRegarding limitations, the study cohort consisted of patients referred to a single tertiary center and would benefit from prospective validation. Assessment of longitudinal changes in volume/mass classification would be of great interest. The study used the previous diagnostic threshold of pulmonary hypertension (mPAP ≥25 mm Hg and pulmonary vascular resistance >3 WU).highMasslow is a maladaptive cardiac phenotype in PAH and may be important to recognize to guide optimal counselling and therapy. Because individuals with VolhighMasslow were older than other groups, one factor may be that, in older patients with significant pulmonary vascular disease, the RV maladapts with insufficient adaptive hypertrophy to maintain RV function. VolhighMasslow remained prognostic following adjustment for age, suggesting that age does not fully explain the poor outcome, and, at all ages, VolhighMasslow should alert the physician of high risk of adverse outcome. In contrast, VollowMasslow patients had less RV remodeling and maintained better RV function. VollowMasshigh and VolhighMasshigh had better prognoses potentially through adaptive concentric hypertrophy that increases the RV wall thickness (The study has identified that Volhickness .


Urgent start peritoneal dialysis (USPD) is an effective therapeutic method for end-stage renal disease (ESRD). However, whether it is safe to initiate peritoneal dialysis (PD) within 24 h unclear. We examined the short-term outcomes of a break-in period (BI) of 24 h for patients undergoing USPD.This real-world, multicenter, retrospective cohort study evaluated USPD patients from five centers from January 2013 to August 2020. Patients were divided into BI ≤ 24 h or BI > 24 h groups. The Primary outcomes included incidence of mechanical and infectious complications. The secondary outcome was technique failure. Moreover, we presented a subgroup analysis for patients who did not receive temporary hemodialysis (HD).p > 0.05). Multiple logistic regression analysis revealed that BI ≤ 24 h was not an independent risk factor for mechanical complications, catheter migration, or infectious complications (p > 0.05). A BI ≤ 24 h was not an independent significant risk factor for technique failure by multivariate Cox regression analysis (p > 0.05). The subgroup analysis of patients who did not receive temporary HD returned the same results.A total of 871 USPD patients were included: 470 in the BI ≤ 24 h and 401 in the BI > 24 h groups. Mechanical and infectious complications did not differ between the two groups across the follow-up timepoints  (Initiating PD within 24 h of catheter insertion was not associated with increased mechanical complications, infectious complications, or technique failures. End-stage renal disease (ESRD) is a chronic condition in many countries  and patiUrgent start peritoneal dialysis is defined as initiating peritoneal dialysis (PD) less than 14 days after catheter insertion . AlthougSeveral studies evaluating the feasibility of USPD with a shorter BI, found that a BI < 24 h increased the incidence of mechanical complications ,20. HowePatients who required PD for ESRD, diagnosed between 1 January 2013, and 31 August 2020, were eligible for our retrospective study. Subjects were recruited from The Second Hospital of Jilin University; The First Hospital of Jilin University-the Eastern Division; Jilin FAW General Hospital; Jilin City Central Hospital; and Xing’anmeng People’s Hospital. Some patients required temporary HD treatment before and/or after PD for severe uremic symptoms. The inclusion criteria were: (1) the patients were diagnosed with ESRD; (2) PD was initiated between 1 January 2013, and 31 August 2020. The exclusion criteria were (1) patients with incomplete data, (2) non-USPD patients, (3) patients younger than 18 years, (4) patients treated with Chronic HD, which was defined as enrollment in an HD program for more than 3 months and undergoing more than seven HD sessions monthly , and (5)The study design was approved by the Ethics Committee of the Second Hospital of Jilin University with study ID . Due to the retrospective study design, informed consent was not required. The research was conducted in compliance with the Declaration of Helsinki.All patients received the same routine preoperative preparation, which included skin preparation, prophylactic antibiotic administration, and emptying of the bowel and bladder. Prophylactic preoperative antibiotics were given according to International Peritoneal Dialysis Association and the antibiotics were determined by the local spectrum of antibiotic resistance  ,26. PatiPeritoneal dialysis was initiated as APD or continuous ambulatory PD (CAPD) in this study. Peritoneal dialysis was prescribed based on fluid overload, uremia, hyperkalemia, and acid-base imbalance for each patient. Usually, a low-volume abdominal cavity (0.5–1.0 L) was initially assumed by the local treating team, and the volume was progressively increased to two L per cycle within 2 weeks. For CAPD patients, four cycles over 3–4 h were performed per day, while for APD patients, six-nine cycles over 48 min and an overnight dwell were performed per day. The dialysis procedure was performed by a PD nurse until the patient and/or caregiver could perform the process independently.Data collection included (1) patient demographics: sex, age, combined temporary HD performed, dialysis mode during the BI period, cause of ESRD, comorbidities, history of abdominal surgery, date of catheter insertion, and date of PD initiation; (2) laboratory indicators (preoperative): white blood cells (WBC), hemoglobin, albumin, triglyceride, total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), creatinine, uric acid (UA), blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), K, Na, Ca, P, and blood glucose (BG); and (3) complications: date and incidence of mechanical  and infectious complications.3 and 50% polymorphonuclear neutrophils, (3) positive culture from dialysate ); (3) both APD and CAPD were used as initiating dialysis modalities in our study; and (4) The same type of procedure was performed for each patient. Currently, much controversy exists regarding which is the optimal surgical procedure for PD. Some studies have reported that a percutaneous or laparoscopic approach, rather than open surgery, is optimal regarding complications and catheter survival [We found no significant differences in mechanical complications between a BI ≤ 24 h and a BI > 24 h. Our results are more reliable than previous studies for the following additional reasons: (1) the data was collected from multiple centers, which makes this a more representative cohort; (2) this was a real-world multicenter retrospective cohort study, and we retained the data about temporary HD (some of the patients had to undergo temporary HD because open surgery could not be performed immediately) and patients with urgent dialysis indications (such as severe volume overload or pulmonary edema, and severe hyperkalemia [Ksurvival . Howeversurvival ,36. To aPrevious studies have not agreed on whether a BI < 24 h is a risk factor for mechanical complications . Our stuInfectious complications are one of the main causes of technique failure, accounting for 52% of cases . TherefoA study using only APD as the initiating dialysis modality revealed no difference in infectious complications between a BI < 24 h and a BI > 12 days . Using mThe high incidence of technique failure has been recognized as a critical factor in the relatively poor PD retention rates worldwide . The tecThere are several limitations to this study. First, patients were screened by retrospective analysis rather than randomization, which may have introduced a selection bias to this study. Second, due to incomplete data, some potentially important data such as dialysis adequacy were not used as primary endpoints. Third, the data were all from Northeast China, and our results may not be generalizable to other areas of the world.Overall, our results suggest that a BI of less than 24 h did not increase the incidence of mechanical complications, infectious complications, or technique failure compared with a BI of more than 24 h.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.


Currently, there is a paucity of data on the knowledge and practice of preventive measures for Hepatitis E infection in Nigerian populations. This study provided data on the prevalence, knowledge and practices of prevention in an adolescent population from Nigeria.This cross-sectional study was conducted over 3 months among rural Nigerian secondary school adolescents. An interviewer-based questionnaire was used to collect data on sociodemographic profile, knowledge, and practice of preventive measures for Hepatitis E infection. Blood samples collected from participants were analysed for Hepatitis E IgG using Elisa Kits . Data were analysed using SPSS software version 20.0. Tests of association were done with a level of significance set at 5%.P = 0.004} and school {P < 0.001, however logistic regression gave infinite value. Most participants (98.6%) had poor knowledge of Hepatitis E infection, 239(57.7%) had good preventive practices, while 175(42.3%) had average preventive practices.A total of 9 out of the 414 participants tested positive for Hepatitis E IgG antibodies giving a prevalence of 2.2%. Significant factors for Hepatitis E infection were male gender {A low prevalence of HEV infection was recorded among study participants. There was poor knowledge of Hepatitis E, and association could not be established between HEV infection and individual preventive practices.The online version contains supplementary material available at 10.1186/s12889-021-11702-y. Globally, 20.1 million people are estimated to have Hepatitis E infection every year. Of these, 3.4 million become symptomatic, with mortality being as high as 70,000, and 3000 stillbirths annually . A high The concern about the potential long term complications has made its screening to be part of the screening guidelines for blood product transfusion in some developed countries . This haHepatitis E infection is an evolving disease with several risk factors, but the distribution varies depending on the population , sociodemographic factors, provision of clean water, food /hygiene practices, sewage disposal, and health status . Direct In developing countries, HEV infection is a public health problem causing both sporadic and epidemic cases that affects several thousands of human lives , 16. SinThe study was a cross-sectional descriptive study conducted from April to July 2017, among secondary school students in Anambra State, South-East Nigeria. Only secondary school students whose ages are from 10 to 18 years who had resided in Anambra state for at least 2 months (incubation period of HEV) were recruited for the study. The school authorities and class teachers were informed about the study before its commencement. Each parent/guardian of participants less than 18 years old signed the informed consent document for his/her child/ward. Assent was given by participants less than 18 years old. The informed consent form was delivered to the parents/guardians through prospective participants.n = The sample size of 371 was calculated using the formula  n = \docP is the proportion of outcome of interest recorded by Ekanem et al  in NigerA Multi staged sampling technique was used to recruit participants for the study. Firstly, schools were selected using a stratified sampling technique to ensure appropriate representation of participants . Secondly, stratified sampling was used to select participating classes. Each school is already stratified into 6 classes namely JSS1, JSS2, JSS3, SS1, SS2 and SS3 from where study participants were selected. For classes that have arms like JSS1A, JSS1B, JSS1C, simple random sampling technique was used to select the representative class in each set.Thirdly, simple random sampling was employed in selecting participants from each class using the class register as a sampling frame. A total of 6 schools were used for the study. The total population of students in the 21 private schools was 1212, while that of students in the 8 public schools was 1117 giving a ratio of approximately 1:1(1.1:1).School A is a private, boarding, boys’ only school while School B is a public boarding/day boys’ only school. School C is a public, day co-educational school and School D is a private day, co-educational school. School E is girls’ only private boarding school while School F is a girls-only public boarding school.From school A, 76 students were studied, while 70 students were studied in school B, 85 students in school C, 66 students in school D, 76 students in school E, and 41 students in school F. This selection was based on the population of the schools. Participants that opted out of the study from the six schools were replaced by simple random sampling from the classes in the schools.A semi-structured interviewer-administered questionnaire that was pretested in a school that was not part of the study was used for data collection . The infThe study was done using ELISA test kits by Sigma diagnostics, USA (Lot Number: JG7190–12) for the detection of IgG to Hepatitis E virus in human serum. The sensitivity and specificity are both > 98%. Sera from all participants were tested for seroreactivity to anti-HEV IgG antibodies . Positive seroreactivity anti-HEV IgG antibodies indicated a previous/past HEV infection. Positive and negative control specimens that were obtained from the SIGMA ELISA kits were run concurrently with the sera during respective batch analysis for anti-HEV IgG antibodies. They were used to assess the validity of the immunoassay procedure and ensure the analytical quality of the ELISA procedure. Test results were interpreted as a ratio of the absorbance of the sample (As) and the cut-off absorbance (Ac). AS/AC < 0.200 implied a negative result, AS/AC between 0.200 and 0.500 was indeterminate, while AS/AC > 0.500 was positive. A negative result indicated that the participant had not been infected by HEV. A positive result was indicative of previous HEV infection. Test results were disclosed to each participant and their parents/guardians.Knowledge was assessed by summing responses to questions on awareness (maximum of 1 point), routes/modes of transmission (maximum of 4 points), and symptoms/signs (maximum of 5 points), giving a maximum score of 10 points. Scores of 0–4 (< 40%) were adjudged as poor knowledge, 5–6 (50–60%) was average knowledge, while 7–10 (> = 70%) was good knowledge. The practice of preventive measures for Hepatitis E (7 items) was scored by the summation of responses to questions on preventive measures, giving a maximum of 12 points. Questions on Hand wash before meals, Hand wash after toilet use, and Fruit and vegetable wash before consumption, were scored using a 2-point Likert scale , while the question on eating from a common plate was scored using a reverse Likert 3-point scale . The other responses under the Practice of preventive measures  scored a maximum of 1 point each. Scores of 0–5 (< 41%) were categorized as poor practice, 6–8 (50–67%) were scored as average practice, while 9–12(> = 75%) were adjudged as good practice.P-value of < 0.05, providing a confidence interval of 95%. The dependent variable for the analysis was the presence or absence of Hepatitis E infection. The independent variables were the socio-demographic factors, knowledge, and practice of Hepatitis E infection preventive measures.All completed questionnaires and proforma were coded before entry into IBM SPSS Statistics software version 20.0 for Windows which was used for analysis. Quantitative variables like age, knowledge and practice of preventive measures were categorized before analysis. Age was categorized into 10–13 years (early adolescence), 14–16 years (middle adolescence) and > 16 years (late adolescence) . KnowledEthical approval for the study was obtained from the Ethics and Research committee of Nnamdi Azikiwe University Teaching Hospital, Nnewi (NAUTH/CS/66/VOL.9/154/2016/127). Permission was obtained from the Post Primary Schools Board, Nnewi zone, the State Ministry of Education (MOE/SCHD/1570/VOL.I/64), and the principals of the schools. The guidelines on research involving the use of human subjects were strictly adhered to according to the Helsinki Declaration. Participants did not incur any cost by participating in this study and there was no financial inducement.Four hundred and twenty adolescents participated in the study. However, only 414 participants who had determinate results were included in the final analysis. Five samples whose sera could not be separated and one indeterminate result was excluded  were males, and almost half 218(52.7%) were junior secondary school students. Mean age of participants was 14.5 ± 1.8 years. Two hundred and twenty-three students (53.9%) comprised the 14–16-year age group. Day students comprised 213(51.5%) of the study population, while there were 201(48.5%) boarding students. The lower socioeconomic class accounted for 215(51.9%) of the participants.P = 0.004}. However, bivariate analysis showed infinite results. There was no significant association between age group or socioeconomic class and Hepatitis E infection {P > 0.05}. Table Of the 414 participants’ sera analyzed, 9 were positive for HEV IgG giving a seroprevalence rate of 2.2%. All participants who had positive seroreactivity were males. All anti-HEV seropositive participants attended school B. There was a significant association between gender and HEV infection {p = 1.000). Of the 239/414(57.7%) students who had good practices of HEV preventive measures, 2/239 (0.8%) had anti-HEV IgG seropositivity compared to 7/175 (4.0%) seropositivity among participants who had average practice. Table Most participants (98.6%) had poor knowledge of HEV infection compared to 6/414(1.4%) who had average knowledge. No participant had good knowledge. There was no significant association between knowledge summative score and HEV infection (Only 37/414 (8.9%) participants were aware of Hepatitis E infection. Four participants (1.0%) were aware of its transmission through the waterborne route, while 25/414 (6.0%) knew it could be transmitted through blood. None was aware of its spread through either food or direct contact. Twenty-two participants (5.3%) identified yellowness of the eyes as a symptom of HEV infection, while only 10/414 (2.4%) mentioned fever as a symptom. Table On preventive practices towards HEV infection, 160/414(38.6%) participants “always” washed their hands before meals compared to 254/414 (61.4%) participants who washed “sometimes” before meals. Two hundred and twenty-four students (54.1%) always washed hands after toilet use compared to 190/414 (45.9%) who washed hands “sometimes”. Only 141/414(34.1%) participants ate wild game meat compared to 273/414(65.9%) who did not. Four participants (1.0%) used illicit intravenous drugs. Individually, none of the risk factors was significantly associated with HEV infection  and possibly drank from the same water source (borehole water supply). Although there was no significant relationship between HEV and sources of drinking water, the sources of water and purity of these sources may differ among different localities. Thus, it may be necessary to explore the sources of drinking water in schools and communities for possible contamination, in view of the possible cluster of HEV among these students. No significant association was found between socioeconomic class and HEV infection, similar to findings by Ekanem et al  in Crossl [et al  in Spainsociation between social class and HEV infection. This could be because most students in this study had similar sources of drinking water and sewage disposal methods irrespective of their social class.The study showed poor awareness, knowledge of symptoms, and modes of transmission of HEV infection. This may be because Hepatitis E infection is an emerging disease that is not well known in the rural areas. Thus, the need for periodic health education in schools to improve the awareness of HEV infection and other communicable diseases. There was no significant association between knowledge and prevalence of Hepatitis E. There was a good practice of preventive measures among participants, however, the individual risk factors were not independently associated with the prevalence of Hepatitis E infection.Our study assessed the association between HEV infection, practice of preventive measures and knowledge of HEV infection. This is one of the few studies that tried to find an association between knowledge, practice of preventive measures and HEV infection. Previous studies focused mainly on the prevalence while few others studied the risk factors. The result of this study showed that the participants had poor knowledge. Thus, there is need to raise awareness of this emerging disease among the adolescents especially because of the potential for sporadic outbreaks. The study did not find strong association between the rate of infection and preventive practices. This may be due to the low prevalence of the HEV infection recorded in this study. In addition, participants shared similar sociodemographic characteristics, which may have contributed to the observed result. Further studies including people of different sociodemographic characteristics will be needed to ascertain or refute this observation.Conclusion/Recommendation: A low prevalence of HEV infection was recorded among study participants, who also demonstrated poor knowledge of HEV infection, but good or average preventive practices. We infer that HEV infection rate is low among healthy adolescents. The inability of the study to demonstrate a significant association between HEV infection, gender and school due to infinite nature of the data calls for further studies. Future studies may incorporate adolescents with compromised immune conditions and out of school adolescents.The observations of this study should be interpreted with caution. This is because most of the participants are healthy in-school adolescents. Thus, it should not be generalized to immune-compromised and out-of-school adolescents.Additional file 1.


Cholinergic neurotransmitter system dysfunction contributes to cognitive impairment in Alzheimer’s disease and other syndromes. However, the specific cholinergic mechanisms and brain structures involved, time course of alterations, and relationships with specific cognitive deficits are not well understood.VT/fp) was measured using 2-[18F]fluoro-3-(2(S)azetidinylmethoxy)pyridine (2FA) and PET imaging. Voxel-wise analyses of group differences were performed. Relationships between receptor binding and cognition, age, and cholinesterase inhibitor medication use were assessed using binding values in six prespecified regions of interest.This study included 102 older adults: 42 cognitively unimpaired (CU), 28 with mild cognitive impairment (MCI), and 32 with Alzheimer’s disease (AD) dementia. Each participant underwent a neuropsychological assessment. Regional brain α4β2 nicotinic cholinergic receptor binding . Pairwise comparisons revealed lower binding in the AD group compared to the CU group in similar regions. Binding in the entorhinal cortex was lower in the MCI group than in the CU group; binding in the hippocampus was lower in the AD group than in the MCI group. AD participants taking cholinesterase inhibitor medication had lower 2FA binding in the bilateral hippocampus and thalamus compared to those not taking medication. In the CU group, age was negatively associated with 2FA binding in each region of interest . Attention, immediate recall, and delayed recall scores were inversely associated with 2FA binding in most regions across the full sample. In the combined group of CU and MCI participants, attention was inversely associated with 2FA binding in most regions, beyond the effect of hippocampal volume.SPM analysis showed the group Nicotinic cholinergic receptor binding in specific limbic and subcortical regions is lower in MCI and further reduced in AD dementia, compared to CU older adults, and is related to cognitive deficits. Cognitive decline with age may be a consequence of reduced cholinergic receptor density or binding affinity that may also promote vulnerability to other Alzheimer’s processes. Contemporary modification of the “cholinergic deficit” of aging and AD may reveal opportunities to prevent or improve clinical symptoms. Acetylcholine neurotransmitter system dysfunction has been observed across the continuum from cognitive aging to mild cognitive impairment (MCI) and Alzheimer’s disease (AD) –6. BeginMore recent studies indicate that atrophy of basal forebrain cholinergic neurons occurs with normal aging and accelerates after age 65 years, with further volume loss in early AD dementia . ImportaRelationships between cholinergic system dysfunction and other AD pathologies are complex and bidirectional. For example, cholinergic receptors may be adversely affected by beta amyloid peptides , but choEvaluating cholinergic neurotransmission in vivo in cognitive aging and AD can improve the understanding of AD pathophysiology, reveal the role of cholinergic dysfunction in the cascade, and identify treatment targets or biomarkers for treatment response. Relationships between cholinergic dysfunction and cognitive impairment seen in previous studies suggest that cholinergic interventions may help to improve clinical symptoms as well as ameliorate the toxic neurodegenerative cascade. Neuroimaging with cholinergic receptor ligands has been used to measure receptor binding in AD and links to cognitive abilities –34. Our The current cross-sectional study used 2FA PET imaging to measure nicotinic receptor binding in cognitively unimpaired older adults and individuals with MCI and AD dementia. The goal of the study was to compare the regional binding profiles across this continuum, with particular attention to binding in the medial temporal cortex where alterations may have prominent cognitive consequences. A second goal was to assess the relationships between regional nAChR binding and attention, concentration, and memory skills.n = 102) included cognitively unimpaired older adults , individuals with MCI (n = 28), and those with AD dementia (n = 32). A subset of participants  was included in a prior study by our group [n = 27), cholinesterase inhibitor medication , or memantine (n = 20) at a stable dosage for at least 3 months were eligible for the study. Those taking other psychotropic medications were excluded.Study participants  was evaluated using the Lawton and Brody IADL assessment [All participants underwent a research clinical assessment that included medical history interview, review of cognitive symptoms and functional abilities, review of prior clinical neuroimaging studies, and neuropsychological assessment. The results were reviewed by two neuropsychologists to confirm study eligibility and to assign a diagnostic group . Neuropsychological test scores (see below) were converted to sessment  and medisessment  if theresessment . FollowiThe Mini-Mental State Exam (MMSE) and Mattis Dementia Rating Scale were used to assess global cognition. Simple attention was evaluated with the Trails A test and Digit Span. Verbal memory was assessed using the Logical Memory (LM) subtest of the Weschler Memory Scale-Revised and the immediate and delayed free recall tasks of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) word-list memory test. Visuospatial memory was assessed using the Brief Visuospatial Memory Test-Revised (BVMT-R) and the recall condition of the Rey-Osterrieth (Rey O) Complex Figure task.z-scores from the Stroop Word Reading, Stroop Color Naming, and Trails A tasks; (2) an average immediate recall (IR) score was generated by averaging across the three learning-trials z-scores in the CERAD, BVMT-R, and Logical Memory I tests; and (3) an average delayed recall (DR) score was established by averaging across z-scores from the CERAD delayed memory, BVMT-R delayed recall, Rey-O delayed recall, and Logical Memory II tests.Three average scores were generated: (1) an average attention score (ATT) was generated by averaging http://surfer.nmr.mgh.harvard.edu/) [We obtained structural brain MR images using a fast 3D-MPRAGE sequence  on a 1.5-T Magnetom Symphony System scanner . The images were used to help define anatomic regions and to generate gray matter maps for use in the 2FA PET imaging analyses. Hippocampal volume, proportional to intracranial cavity volume, was calculated for each participant using FreeSurfer (rd.edu/) .The 2FA radiotracer utilized in this study was prepared at the VAGLAHS Cyclotron Facility . ProceduPET images were acquired using the Gemini TF PET-CT scanner  in three-dimensional mode. Total scan time was 60 min, and images were reconstructed in 1-min frames using a three-dimensional reconstruction algorithm and Gaussian filtered back projection with a kernel of 8 mm full width at half maximum (FWHM).VT/fp) on PET images was calculated using the values of parent and unbound 2FA activity in the plasma. This method accounts for inter-participant variability in radiotracer metabolism and protein binding. VT/fp approximates nicotinic receptor binding potential and is proportional to Bmax/Kd [Blood samples were collected at the start of PET image acquisition and at 15-min intervals during the 60-min PET acquisition period. Parent (non-metabolized) 2FA in the blood plasma samples was measured using solid-phase extraction , and the Bmax/Kd .VT/fp values by dividing the voxel activity by the activity of parent and unbound 2FA activity in plasma.2FA PET images were processed and analyzed using SPM12. The 60 1-min frames were motion-corrected and then averaged to create one mean subject-level image. Counts within the image voxels were converted to Due to the age of participants and potential cortical atrophy, partial volume correction was applied to the PET images using PETPVE from the SPM Toolbox to normalize 2FA grey matter activity . PETPVE VT/fp in the six core ROIs were used in subsequent ROI analyses.In the second arm of PETPVE, PVEc-GTM, an MNI space region-of-interest (ROI) atlas (Desikan-Killiany ) was manp < .05 corrected using the familywise error procedure (FWE). Planned post hoc tests compared 2FA binding pairwise between the groups at p < .05, FWE-corrected. In addition, we used small volume correction to assess the differences in the medial temporal lobe structures, specifically the bilateral entorhinal cortex and hippocampus. A mask of the bilateral entorhinal and hippocampal regions was created using the neuromorphetrics atlas in SPM (neuromorphometrics.com). Findings within the mask were assessed at the voxel level, p <.05, FWE-corrected.2FA binding differences in the CU, MCI, and AD groups were first compared using a one-way ANOVA in SPM12. The groups were modeled assuming independence and unequal variance, thresholding was used to remove spurious 2FA signal, and implicit masking was applied. The main effects were assessed using a voxel-level significance of VT/fp values were extracted from the six bilateral core ROIs. ROI group analyses were conducted using MANOVAs in SPSS v25, with 2FA binding in each region as the dependent variables and group as the independent variable. Bonferroni-corrected post hoc tests explored the pairwise group differences in those regions with a significant overall group effect.Region-of-interest (ROI) analyses were also conducted to assess the 2FA binding differences among the diagnostic groups in specific anatomical regions. Atrophy-corrected p = .09–.98). Box’s M test was calculated to assess the equality of covariance . A priori power calculation for MANOVA indicated a required total sample of 81 to detect an effect size (f2V) of .16 with 80% power, with alpha set at .05, 3 total groups, and 12 response variables. A priori power calculation for correlational analyses indicated a required total sample of 82 to detect an effect size of 0.3 with 80% power, with alpha set at .05 using a two-tailed test. Power calculations were carried out using GPower 3.1.7 [Multiple tests were conducted to ensure that assumptions for MANOVA analyses were met. Mahalanobis distance was calculated to detect multivariate outliers, and one case was removed from further analysis. The Shapiro-Wilks tests were used to examine the normality of each dependent variable for each diagnostic group (er 3.1.7 .ps < .02). Overall, there was a high proportion of male participants in the sample, as the study primarily recruited veterans. AD participants had received this diagnosis an average of 4.8 years  prior to the time of the 2FA scan.Sample characteristics and clinical assessment scores for participants in the CU, MCI, and AD diagnostic groups are shown in Table t-test showed that AD participants had lower 2FA binding than CU participants in most of the same regions identified in the overall ANOVA , and basal ganglia  Fig. , Table 2OVA Fig. . There wOVA Fig. . There wF = 3.4–15.2, ps = .000002–.038). In post hoc pairwise comparisons, participants with AD had lower 2FA binding than those in the CU group in all ROIs, bilaterally . 2FA binding in the AD group was also lower than that in the MCI group in the bilateral hippocampus. 2FA binding in the MCI group was lower than that in the CU group in the left entorhinal cortex, bilateral insula, and left anterior cingulate.The mean 2FA binding in the six core ROIs  in the three diagnostic groups are shown in Fig. Twenty-three of 32 AD participants and eight of 28 MCI participants were taking a stable dose of AChEI medication at the time of 2FA PET imaging. 2FA binding in the six core ROIs among those taking AChEI medication was compared to those not taking AChEI medication within the AD and MCI groups individually Table . In the ps = .003–.037, Bonferroni-corrected; n = 32 for AD, n = 42 for CU). Participants with MCI had lower binding in the left entorhinal cortex, bilateral insula, and left anterior cingulate, compared to the CU group . There were no significant 2FA binding differences between the AD and MCI groups for any region in this model.When the MANOVA of 2FA binding in ROIs across the groups included AChEI medication use as a covariate in the model, participants with AD had lower binding in the bilateral hippocampus, left entorhinal cortex, bilateral insula, and left caudate, compared to the CU group  and those not taking (n = 15) memantine in any core ROI .We also separately examined the effect of stable memantine treatment on 2FA binding in the AD group. There was no significant binding difference between those taking . Similarly, an overall MANOVA that included antidepressants as a covariate did not change the effect of the diagnostic group on 2FA binding in the six core ROIs.Finally, we examined the potential effect of antidepressant treatment on 2FA binding in each of the diagnostic groups. For all ROIs and all diagnostic groups, there were no significant differences between those taking and those not taking antidepressant medication in any core ROI (r(30) = − .39–.71, p = .000005–.029 for each relationship). Within the MCI group, age was negatively correlated with binding in the right caudate (r(26) = − .41, p = .03). Within the CU group, age was negatively correlated with 2FA binding in all core ROIs in each hemisphere . As an example, the scatterplot for the relationship between age and 2FA binding in the right anterior cingulate is shown in Fig. We examined the effect of age on regional 2FA binding in the core ROIs in each diagnosis group. Within the AD group, there was a significant negative correlation between age and 2FA binding in the bilateral hippocampus, left entorhinal cortex, bilateral insula, right anterior cingulate, and left caudate (r(100) = − .37, p = .00014 with AD = 1, MCI = 2, and CU = 3). To reduce the impact of multicollinearity, the MANOVA was repeated while covarying for age to specifically examine the 2FA binding differences between the MCI and CU groups, as the AD participants were significantly older on average. This analysis, controlling for age, revealed lower 2FA binding in the MCI group compared to the CU group in the left entorhinal cortex and bilateral insula .Across all study participants, age was correlated with diagnosis group membership (r(91) = .23–.34, p = .001–.03). The Immediate Recall (IR) average score was similarly associated with binding in the bilateral hippocampus, insula, caudate, and left entorhinal cortex (r(97) = .21–.30, p = .003–.035 for each relationship). The Delayed Recall (DR) average score was associated with binding in the bilateral hippocampus, insula, thalamus, caudate, and left entorhinal cortex (r(94) = .24–.39, p = .00009–.042 for each relationship).Across all participants, the Attention average score (ATT) was correlated with 2FA binding in the bilateral hippocampus, insula, thalamus, caudate, and right anterior cingulate (n = 68). For ATT, correlations were similar to the full sample, although the relationship with 2FA binding in the thalamus was no longer significant and the relationship with the left entorhinal cortex became significant. IR was not significantly correlated with any ROI (ps > .18). DR was associated with the left caudate and left entorhinal cortex (r(63) = .25–.35, p = .003–.038 for each relationship). Covarying for the use of AChEI medication in the analysis of the combined CU and MCI groups did not substantially change the correlations for ATT or IR, while the relationship between DR and binding in the left caudate was no longer significant. Similarly, when covarying for age, IR and DR associations were unchanged, while ATT was positively associated with binding in the bilateral hippocampus and insula, right anterior cingulate, and right caudate.Because cognitive assessment scores in the AD group showed floor effects, we repeated the analysis in the combined sample of CU and MCI (ps < .001). There was a marginal difference between CU and MCI . Within the combined sample of CU and MCI participants and controlling for hippocampal volume, ATT was associated with 2FA binding in the bilateral hippocampus, insula, and right anterior cingulate (r(63) = .26–.35, p = .004–.038 for each relationship). There were no significant associations between IR and 2FA binding in any ROI. DR was positively associated with binding in the left entorhinal cortex .Finally, we explored whether the inclusion of hippocampal volume in the model would alter the observed relationships between cognitive scores and regional 2FA binding. Of note, there were significant differences in the hippocampal volume between the groups, such that AD had lower volume than CU and MCI  β-amyloid deposition and abnormal tau processing occur very early in the AD continuum , 68; (2)This study addressed cholinergic receptor deficits in AD specifically, but there are also cholinergic disturbances in other neurodegenerative conditions, such as Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). A small number of comparative post-mortem studies suggest that differences in cholinergic disturbances may distinguish these neurodegenerative conditions. For instance, loss of choline acetyltransferase appears to be greater in DLB compared to AD , especiaThis study has several strengths, including a sample sufficiently large to detect moderate group differences in regional cholinergic receptor binding, inclusion of carefully characterized participants, and use of structural MRI in addition to 2FA imaging to assess binding in anatomically defined brain regions and to allow the inclusion of hippocampal volume in evaluating the relationships with cognitive skills. The study also has several limitations. Amyloid biomarkers were not measured, so we were unable to apply an A/T/N framework to the sample. However, the lower hippocampal volumes measured in the study were consistent with those expected in MCI due to AD and in AD dementia, and NIA/AA clinical Alzheimer’s disease criteria were applied by experienced investigators using detailed neuropsychological assessments. Nonetheless, we cannot assume that the MCI and AD participants had elevated cortical amyloid levels, and the results of the study may also apply to those with cognitive deficits resulting from other etiologies. Also, cerebrovascular changes were not included in the models, which could confound the findings. However, structural neuroimaging studies were used to exclude any participant with substantial small vessel cerebrovascular disease or cortical infarct. The MCI and AD groups included predominantly men, and thus, we were unable to assess the effect of sex or a sex × diagnosis interaction. Finally, the modest sample size limited our ability to fully dissect the effects of older age in the AD group, medication treatment, or binding in specific brain regions on the magnitude of cholinergic receptor binding across the groups or relationships with cognitive skills.Overall, the results of this study support a more contemporary view of the “cholinergic hypothesis” of AD, demonstrating reduced cholinoceptive binding in specific limbic and subcortical regions in AD dementia that was also present in some brain regions at the MCI phase. Reduced binding was associated with deficits in attention and recent memory in the overall sample and with lower attention skills in the combined group of cognitively healthy and MCI participants. Among cognitively unimpaired older adults, cholinergic receptor binding appears to decline with age and may represent a mechanism for cognitive aging or confer vulnerability to additional neurodegenerative processes in later life. Further studies can help refine the understanding of these relationships, can reveal regional changes over time and their links to other pathologies, and may help identify opportunities for symptomatic or disease-modifying AD treatments.