To evaluate and compare the predictive value of Face, Arm, Speech Test (FAST) and Balance, Eyes, Face, Arm, Speech, Time (BEFAST) scale in the acute ischemic stroke (AIS).We searched Medline and Ovid databases for relevant literature in the English language. There were no limitations on the date. The sensitivity, specificity, likelihood ratio, and diagnostic odds ratio were pooled for meta-analysis. The symmetric receiver operator characteristic curve and Fagan's Nomogram were drawn, and meta-regression and subgroup analysis were used to explore the source of heterogeneity.CI (0.64–0.86)], specificity was 0.60 [95% CI (0.38–0.78)], the area under the ROC curve was 0.76, and the diagnostic ratio was 1.57, while the sensitivity of BEFAST was 0.68 [95% CI (0.23–0.93)], specificity was 0.85 [95% CI (0.72–0.92)], the area under the ROC curve was 0.86, and the diagnostic odds ratio was 2.44. No publication bias was detected in Deeks' funnel plot. For FAST, meta-regression analysis showed that the prospective design, satisfactory description of the index test, and a broad spectrum of disease contributed to the heterogeneity in sensitivity, while no sources contributed to the heterogeneity in sensitivity. When the pretest probability was set as 20%, the posterior probability in Fagan's Nomogram was 32%; however, when the pretest probability was set as 20% in BEFAST, the posterior probability in Fagan's Nomogram was 52%.A total of 9 studies, including 6,151 participants, were analyzed. The combined sensitivity of FAST was 0.77 [95% Our findings indicated that FAST and BEFAST might be useful in the diagnosis of acute ischemic stroke. The diagnostic value of BEFAST in acute ischemic stroke was higher than in FAST; thus, it might have an important role in the fast recognition of acute ischemic stroke. Stroke is one of the most common acute and severe diseases presented to an emergency department (ED). Stroke is a major global burden, with 10.3 million new strokes and 113 million disability-adjusted life years (DALYs) per year worldwide . TherefoInsufficient knowledge on stroke among the general public may lead to serious consequences. Several screening tools, including the Cincinnati Prehospital Stroke Scale (CPSS), Face, Arm, Speech Test (FAST), Los Angeles Prehospital Stroke, Screen (LAPSS), Melbourne Ambulance Stroke Screen (MASS), Medic Prehospital Assessment for Code Stroke (Med PACS) and Recognition of Stroke in the Emergency Room score (ROSIER), which are characterized by simple, structured, and easy-to-use stroke recognition scores, have been developed to help the public identify if a person is having an acute stroke so as to facilitate rapid access to medical care. Among these scales, the FAST provides the highest sensitivity with 85%. However, the available stroke recognition scores have a huge variety of length and complexity, which complicates choosing the optimal score in the emergency setting . A previBEFAST , which was previously studied to determine whether adding gait or visual abnormalities to the FAST scale would improve stroke detection rates, revealed statistically lower Sensitivity for the detection of AIS in the inpatient population compared with the ED . HoweverIt is necessary to improve the accuracy of scales. This systematic review and meta-analysis aimed to explore the diagnostic value of the FAST and BEFAST for AIS patients; a quantitative reference for clinical practice was provided.Two reviewers (CXJ and ZXX) independently searched the PubMed, Embase, and Cochrane libraries for all the relevant publications published thus far. We chose the keywords “stroke,” “ischemic stroke,” and “hemorrhagic stroke” as text words and MeSH terms to identify related studies, language, region, or publication type. The search was limited to published clinical studies. Search terms are listed as follows:(FAST)[Title/Abstract](BEFAT)[Title/Abstract]1 OR 2(“stroke” or “ischemic stroke” or “hemorrhagic stroke”) [Title/Abstract]3 AND 4From 2011 to 2021Inclusion criteria were: (1) all types of strokes; (2) included FAST or/and BEFAST; (3) clinical study; (4) published within past 10 years; and (5) published in the English language.Exclusion criteria were: (1) no described outcomes; (2) no control groups; (3) impossible to find original paper; and (4) the sensitivity, specificity (Sp), positive predictive value, and negative predictive value cannot be extracted.Two authors (CXJ and ZXX) independently extracted the demographic data and treatment information, and if a disagreement occurred, a third author (XF) was involved. Baseline information extracted from 9 studies contained the first author name, year of publication, title, design type, study subjects , disease degree, and length of the disease. Besides, the primary outcomes included True positives (Tp), False positives (Fp), False negatives (Fn), true negatives (Tn) with FAST and BEFAST.The Agency for Healthcare Research and Quality (AHRQ) was used to rate the methodological quality of cross-sectional studies. An item was scored with “0” if it was answered “NO” or “UNCLEAR”; if it was answered “YES,” then it was scored “1.” Article quality was assessed as follows: low quality = 0–3; moderate-quality = 4–7; and high quality = 8–11. The quality of studies was assessed by using the Newcastle Ottawa scale (NOS), which generated a maximum of nine stars for each study, including four stars for the selection of participants, two stars for the comparability of participants, and three stars for the assessment of outcomes. Quality was assigned according to the final scores, where 7–9 stars indicated high quality, 4–6 stars for middle quality, and 0–3 stars for low quality (Q statistics (chi-square), or inverse variance (I2). I2 <50% and p > 0.1 indicated that these studies could be considered as homogeneous by using a fixed-effect model; otherwise, I2 ≥ 50%, p <0.10, the random effect model, was used for meta-analysis. If heterogeneity among studies was recorded, the potential source of heterogeneity was investigated via meta-regression. A p value <0.05 was considered statistically significant.Stata 15.0 software  was used to perform a meta-analysis. The bivariate model was used to calculate the combined Sensitivity (Se), Specificity (Sp), the positive likelihood ratio (PLR), the negative likelihood ratio (NLR), and diagnostic odds ratio (DOR), and to draw the symmetric receiver operator characteristic curve (SROC) so as to estimate the total diagnostic accuracy. Pre-test probabilities may be estimated from routine data, practice data, or clinical judgment. Post-test probabilities are used to determine whether the probability of diagnosis has raised or fallen, compared with pre-test probabilities. The heterogeneity was assessed by Cochrane's A total of 7,690 papers with FAST and BEFAST  were retrieved from each database. After 1,825 duplicate records were removed, the full text of the remaining 5,865 studies was read. Among those studies, 201 were excluded because the articles were reviews, meta-analyses, or case reports, while 5,642 studies did not have related titles and abstracts. The full text of the remaining 21 studies was read, and 12 studies were removed due to incomplete data. The remaining 9 papers were extracted from the corresponding data according to the data extraction requirements. Seven studies used the FAST; one study used the BEFAST and one study used the FAST and BEFAST. The literature screening process is shown in CI ], Sp was 0.60 [95% CI ], PLR was 1.90 [95% CI ], NLR was 0.39 [95% CI ], area under ROC curve was 0.76, and DOR was 4.82, which indicated the FAST had a medium value in the screen of AIS. As all heterogeneity was I2 > 50%, the random model was used. The details of the combined Se and Sp forest plot are shown in The combined Se of FAST in AIS was 0.77 , as shown in The SROC curve plane test was used to threshold effect. However, there was no typical “shoulder arm” found, indicating no threshold effect. Moreover, Cochran's Q value was 59.49, and the In this study, we evaluated the factors that may affect the heterogeneity, such as non-threshold effect, prospective design (prodesign), satisfactory description of index test (testdescr), an adequate description of study subjects (subjdescr), satisfactory description of ref test (refdescr), report, a broad spectrum of disease (brdspect), and whether the test results were evaluated by a blind method. The meta-regression analysis of the above factors revealed that although the sources of heterogeneity of Se were statistically related to the prodesign, testdescr, and brdspect, the sources of heterogeneity of Sp were not related to these factors, as shown in The Fagan graph was plotted to show the relationship among the prior probability, the likelihood ratio, and the posterior probability. The pretest probability was 20%, and the post-test probability of AIS was 32%. In addition, the PLR was <10 (PLR = 1.90), and the NLR was >0.1(NLR = 0.39), indicating that the diagnosis can neither be confirmed nor excluded. Their diagnostic value of FAST in AIS was limited, as shown in CI ], Sp was 0.85 [95% CI ], PLR was 4.41 [95% CI ], NLR was 0.38 [95% CI ], AUC was 0.86, and DOR was 11.49, which indicated that the BEFAST had a medium value in the screening of AIS. All heterogeneity was I2 > 50%; therefore, the random model was used in The combined Se was 0.68 ; details are shown in The threshold effect was assessed by the SROC curve plane test. As no typical “shoulder arm” was found, there was no threshold effect. A moderate diagnostic value was concluded by the value of the AUC, which was 0.86 [95% The pretest probability was 20%, and the probability of AIS was 52%. In addition, the PLR was <10 (PLR = 4.41), and the NLR was >0.1(NLR = 0.38), which indicated that the diagnosis could be neither confirmed nor excluded. Their diagnostic value of BEFAST in AIS was also limited; details are shown in Comparison of FAST, BEFAST, and FAST in combination with BEFAST was performed using ROC, Se, and Sp analysis. Among them, the BEFAST had the best diagnostic value; details are shown in For prospective studies, the NOS scores varied from 6 to7 stars . For croThe phrase “time is brain” highlights that human nervous tissue is rapidly and permanently lost as stroke progress and that therapeutic intervention should be emergently pursued. Nonetheless, <10% of patients with stroke in hospitals undergo emergency treatment within the thrombolytic time window . CurrentOver recent years, the prehospital stroke scales have become increasingly used to assess acute stroke. Among them, FAST has the highest diagnostic value, with 88.9% of identified stroke/TIA patients within our population. However, the FAST failed to detect 38% of posterior cerebral circulation strokes , 19. PosThere has been an increasing number of Systematic reviews and meta-analyses assessing the diagnostic performance of clinical assessment over recent years. The previous systemic review and meta-analysis have evaluated the diagnostic value of the current common stroke identification scales worldwide. In 2014, a Systematic review showed that prehospital stroke scales varied in their accuracy, missing up to 30% of acute strokes in the field through the evaluation of FAST, CPSS, MASS, LAPSS Ontario Prehospital Stroke Screening Tool (OPSS), and Med PACS for diagnostic value with stroke in urban environment . In 2019Our results showed that the FAST had higher Se than BEFAST in detecting AIS. By contrast, BEFAST had a higher Sp than FAST. In general, BEFAST had the highest diagnostic value; however, FAST, as well as BEFAST, may be useful in the diagnosis of AIS. Previous studies found that 14% of patients with AIS would be missed using FAST alone, and this proportion was reduced to 4.4% with the addition of a history of gait and visual symptoms (BEFAST). Our results were consistent with previous reports .Our findings indicated that FAST, as well as BEFAST, might be useful in the diagnosis of AIS; however, AIS could neither be confirmed nor excluded by the sole use of FAST or BEFAST. The diagnostic value of BEFAST in AIS was higher than FAST; thus, it might have an important role in the fast recognition of AIS. Nonetheless, it still remains unclear whether it could be applied for screening of all patients with stroke in the prehospital setting or in hospital, or whether the test characteristics of the FAST and BEFAST scales could be separately assessed for posterior and anterior circulation. Future prospective studies are needed to explore the diagnostic value of FAST and BEFAST in the anterior and posterior circulation, respectively, so as to improve the recognition rate of stroke, promote timely intervention, and reduce the burden on families and society.First, there was moderate heterogeneity across studies, meta-regression, and subgroup analysis fail output due to the limited BEFAST data. Second, few included studies did not explicitly exclude participants. Both shortcomings should be further investigated and addressed by future studies.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.XC: perform the literature screening, data extraction, data analysis, results representation, and drafting the manuscript for intellectual content. XL: statistical analysis, interpreted the data, and contributed to and revised the manuscript for intellectual content. XW: study initiate and contribute to and revised the manuscript for intellectual content. LZ and YY: revised the manuscript. MG: electronic search and articles election. FX: instruct the detail steps for groups and draft the manuscript. XZ: perform the literature screening, data extraction, data analysis, and results representation. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China, No. 8216050478 to XL, and 82073833 to XW; the Program from Yunnan Provincial Clinical Research Center for Neurological Diseases, No. 202002AA100204 to LZ and XL; the Basic Research Program of Yunnan Provincial Science and Technology Department, No. 202101AT070151, and 20190FE001(-222) to XL; Chengdu Science and Technology Bureau Focuses on Research and Development Support Plan, No. 2019-YF09-00097-SN to FX; the Popular Scientific Research Project of Sichuan Health Commission, No. 20PJ171; and the Yunnan education program, No. SYSX202036 to XL and FX.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


As an age-related syndrome, frailty may play a central role in poor health among older adults. Sarcopenia overlaps with the physical domain of frailty, and most existing studies have analyzed the associated factors of frailty and sarcopenia as an isolated state. Perturbations in metabolism may play an important role in the presence of frailty or sarcopenia; however, the metabolites associated with frailty, especially overlapping with sarcopenia remain unclear. In this study, we aimed to explore whether amino acids, carnitines, acylcarnitines and lysophosphatidylcholines, as specific panels, are significantly correlated with frailty, especially overlapping with sarcopenia, to gain insight into potential biomarkers and possible biological mechanisms and to facilitate their management.n = 150), non-frailty (n = 96), frailty and sarcopenia (n = 52), non-frail and non-sarcopenic control (n = 85). Frailty was evaluated using Freid phenotype criteria, sarcopenia was defined by diagnostic algorithm of Asian Working Group on Sarcopenia, and the participants were diagnosed as frailty and sarcopenia when they met the evaluation criteria of both frailty and sarcopenia. A panel of 29 metabolomic profiles was assayed and included different classes of amino acids, carnitines, acylcarnitines, and lysophosphatidylcholines (LPCs). Multivariate logistic regression was used to screen the metabolic factors contributing to frailty status, and orthogonal partial least squares discriminant analysis was used to explore important factors and distinguish different groups.We applied a targeted high-performance liquid chromatography-tandem mass spectrometry approach in serum samples from 246 Chinese older men (age 79.2 ± 7.8 years) with frailty , LPC16:0 and LPC18:2, while higher levels of octanoyl-L-carnitine (C8), decanoyl-L-carnitine (C10), dodecanoyl-L-carnitine (C12) and tetradecanoyl-L-carnitine (C14). After adjusting for several clinical confounders, tryptophan, LPC18:2, LPC 16:0 and C5 were negatively correlated with frailty, and C8 and C12 were positively related to frailty. We preliminarily identified metabolic profiles  that may distinguish older men with frailty from those without frailty. Importantly, a set of serum amino acids and LPCs  was characterized in the metabotype of older adults with an overlap of frailty and sarcopenia. The metabolites that were most discriminating of frailty status implied that the underlying mechanism might be involved in antioxidation and mitochondrial dysfunction.These present metabolic analyses may provide valuable information on the potential biomarkers and possible biological mechanisms of frailty, and overlapping sarcopenia. The findings obtained may offer insight into their management in older adults. As an age-related clinical syndrome, frailty is caused by a progressive discrepancy between the accumulation of damage and resilience of the body, and can explain some of the health heterogeneity among people with the same chronological age . FrailtyThe biological mechanisms underlying frailty have been extensively studied in recent years. Scientific progress in understanding frailty has been hampered by disagreement about its pathophysiology and operational diagnosis in research and clinical settings . FrailtyWith the aim of expanding knowledge in this area, in the current study, we determined the serum metabolomic profile using targeted tandem mass spectrometry coupled with multivariate statistical analysis, to simultaneously analyze different classes of amino acids, LPCs, carnitines and AcyCNs in older Chinese men. We explored the metabolic factors of frailty, and then narrowed down the range to study the discriminating metabolites of frailty overlapped with sarcopenia. We aimed to explore whether amino acids, carnitine, AcyCNs and LPCs, as specific panels, are significantly correlated with frailty, especially F&S, to gain insight into possible biological mechanisms, as well as to facilitate the management of frailty.A total of 246 elderly men (62–100 years old) attending the Geriatric Medicine department of Beijing Hospital for physical examination from August 2016 to May 2018 were recruited using random numbers after the inclusion and exclusion. The inclusion criteria were as follows: participants were older than age 60 years, had the ability to understand and complete the questionnaires, and did not have severe mental or cognitive disorders. People with malignant tumors, blood system diseases, chronic obstructive pulmonary disease, autoimmune diseases, infectious diseases, and individuals who were taking amino acid supplements were excluded. This study was approved by the Medical Ethics Committee of Beijing Hospital of the National Health Commission.In order to assess the health status related to frailty or sarcopenia, we administered comprehensive geriatric assessment consisting of general clinical information and demographic data. Each participant self-reported their smoking and alcohol drinking status . Polypharmacy was defined as the use of more than five medications . ComorbiIn this study, frailty was defined according to the Fried phenotype criteria, which include exhaustion, weakness, slowness, physical inactivity and weight loss . Exhaust2, kg/m2). Low muscle strength was defined as handgrip strength < 28 kg for men and low physical performance was defined as a 6-m walk speed < 1.0 m/s. The cutoff for height-adjusted muscle mass  via bioelectrical impedance data was <7.0 kg/m2 in men. Participants were diagnosed with F&S when they met the evaluation criteria of both frailty and sarcopenia; non-frail and non-sarcopenic control did not meet the criteria for either sarcopenia or frailty  according to the presence of both low muscle mass and low muscle function  . Appendi frailty .g for 10 min at 4°C. Aliquots of serum were subsequently stored at –80°C until analysis. Blood samples were measured using an automatic biochemical analyzer and enzymatic colorimetric tests for laboratory routine parameters.Blood samples were collected in the morning using venipuncture of the median cubital vein after participants had completed an overnight fast. For serum separation, samples were left at room temperature for 20 min and subsequently centrifuged at 1,000 × A panel of 29 Serum metabolites was measured using our previously reported targeted liquid chromatography-tandem mass spectrometry method for simultaneous quantification of three branched-chain amino acids , three aromatic amino acids , glutamate (Glu), glutamine (Gln), Gln/Glu ratio, alanine, glycine, four subclasses of LPC, carnitine, and 12 species of AcyCN, trimethylamine-N-oxide (TMAO) and betaine , 29. Brit-test. The non-parametric Wilcoxon test was applied to assess differences in non-normally distributed continuous data. Differences in categorical variables between groups were determined via χ2 or Fisher's exact tests. A Benjamini–Hochberg correction was used to account for multiple comparisons. Significance levels in prior exploratory analyses  ≤ 0.30.Continuous variables are expressed as mean ± standard deviation or median , and categorical data are expressed as percentage. The normal distribution of data was ascertained using the Kolmogorov–Smirnov test. Metabolites with a skewed distribution were log-transformed. Comparisons between two groups for normally distributed continuous variables were performed using the analyses , 31 guidp < 0.05.Spearman correlations were used to examine the relationship between metabolites. In multivariable logistic models of metabolites and frailty, clinical potential confounding covariates, that were significantly associated with frailty in the above univariate analyses and previous studies –34 were Orthogonal partial least squares discriminant analysis (OPLS-DA) in SIMCA-P v.14.1 was applied to distinguish those metabolites related to frailty and to enhance the separation between groups using rotating principal component analysis. Among the possible classifiers, OPLS-DA was selected because of its versatility and ability to deal with highly correlated predictors –37 and bThe participants included in the analysis comprised 246 men aged 62–100 years. According to the Fried phenotype criteria, the participants were stratified into 96 non-frailty (39.0%), 132 prefrail men (53.7%) and 18 frail men (7.3%). In this study, prefrail and frail men were combined into the frailty group . In terms of frailty criteria constituents, 57 men (51.8%) in the frail group and 15 men (15.96%) in the non-frailty group had lower grip strength. The frailty group had a slower walking speed, greater reductions in physical activity, and a higher proportion of participants with exhaustion than the non-frailty group. Similarly, the SMI was smaller in the frailty group than in the non-frailty group. Study participants included 65 (26.4%) older men with sarcopenia and 181 (73.6%) non-sarcopenic elderly men; moreover, 52 (21.1%) men had F&S, whereas, 85 (34.6%) men were non-frailty and non-sarcopenia (non-frail and non-sarcopenic control).The main clinical and functional characteristics of the study population are presented in With respect to routine chemistry parameters, frailty participants had lower concentrations of red blood cells and hemoglobin. Serum uric acid and ALT levels in frailty participants were significantly lower than those in non-frailty participants. No other blood chemical parameters, such as albumin, fasting blood glucose, triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and aspartate aminotransferase were found to be significantly different between the two groups.A description of metabolic species levels is provided in r = 0.70).r = 0.86 and 0.73, respectively, whereas, those of C10 with C12, and of C12 with C14 were r = 0.78 and 0.81, respectively.Significant correlations were also observed between acylcarnitines, indicating that they change in ways that are interrelated. Very strong positive correlations between C8 and C10, and between C12 and C14 were observed, and moderate correlations were observed between C8 and C14 and between C10 and C14. The correlation coefficients of C8 with C10 and C12 were p < 0.05 No significant relationship was found between levels of glycine, C10, C14, and frailty in Models 2 and 3, whereas, a significant association was observed in Model 1 . When thTo better understand the correlation between measured metabolic factors and frailty status, OPLS-DA was performed to identify the main components that could discriminate the two groups. Unfortunately, the OPLS-DA score plot yielded no clear separation and merely showed a trend distinguishing frailty elderly men from their non-frailty counterparts . The parWith regard to the OPLS-DA model of F&S vs. non-frail and non-sarcopenic control, the clustering trend was not sufficiently ideal; a separation trend was only found for the main principal components, and the predictive capacity was low, although this model had certain explainability  . This exPermutation tests indicated that the above models were reliable and had a low risk of over-fitting. The area under the curve (AUC) of the above two models were all >0.7 with the discriminatory power to some accuracy .Frailty is associated with a higher risk of disability, hospitalization, and death in older people, playing a central role in poor health later in life. Related biomarkers of frailty can be used in diagnosis and treatment decisions concerning frailty , 39. As Specific patterns of circulating amino acids have been associated with frailty; among amino acid profiles, tryptophan breakdown products have been found in many studies. Tryptophan is an essential amino acid that exerts multiple roles in immune, nervous, and muscular system functions , 41. AltGlycine is a major amino acid and the simplest non-essential amino acid. Recent metabolomics studies have found a relationship between serum levels of glycine and cardiometabolic disease , 29. GlyLPCs are a major class of glycerophospholipids in human blood. The most abundant LPC in human plasma is LPC 16:0, followed by LPC 18:2, LPC 18:0/18:1, LPC 20:4, and other minor LPC species. LPC has been relevant to muscle mass and mitochondrial oxidative capacity in skeletal muscle . PreviouAs short-chain AcyCNs, propionyl (C3), methylmalonyl (C4-DC), and isovalerylcarnitine (C5), as well as medium-/long-chain AcyCNs (C6–C20) are produced during fatty acid oxidation . The maiIn our study, the significant relationship observed between these frailty-related metabolites indicate that they change in interrelated ways. These metabolites are at the crossroads of multiple biological processes, notebly, mitochondrial function and redox homeostasis besides inflammation and insulin resistance, all of which may contribute to frailty or sarcopenia as per the above discussion. As an intermediate product of fatty acid oxidation, significantly positive correlations were observed among the AcyCNs C8, C10, C12, and C14. The accumulation of these medium-/long-chain AcyCNs may point toward the inability of mitochondria to properly metabolize fatty acids , 60. TheIn the present study, in either univariate or multivariate analysis, the three shared metabolites of frailty and F&S included LPC16:0, LPC18:2 and tryptophan. Two reasons may help to explain the relationship between characteristic metabotypes of frailty and that of F&S. First, at definition level, frailty encompasses several domains , and sarcopenia overlaps with the physical domain of frailty. Gait speed and grip strength are both used to define frailty and sarcopenia, and the above mentioned metabolites are related to these two muscle traits . AdditioBody composition, neuroendocrine dysregulation, and immune dysfunction may represent the underlying biologic dynamics that influence the development of frailty in both men and women , 66. AccThere are some limitations in the present study. First, the study population was relatively small; also, a large number of experimental variables were included in the analyses, which may limit the statistical power. Second, the participants in our study were mostly older men with prefrail status; thus, the findings cannot necessarily be generalized to populations owing to social and cultural differences. Third, other factors may affect circulating metabolites levels, such as lifestyle and dietary habits. Thorough investigations regarding the effect of lifestyle variables, dietary intake, and medication on potential biomarkers should be conducted in further studies to understand all important confounders. Last, this study is a cross-sectional study sought to assess the relationship of metabolites with frailty, and a causal relationship and potential diagnostic biomarkers of metabolic changes in frailty should be investigated in future follow-up studies.Our metabolic profiling analysis can provide valuable information regarding the potential biomarkers and possible biological mechanisms in older men. In addition to identifying LPC16:0, LPC18:2, tryptophan, C5, C8 and C12, which appear to be independently correlated with frailty status, we preliminarily demonstrate that the characteristic metabotypes of frailty and that of F&S shared a set of tryptophan, LPC16:0 and LPC18:2, and glycine may specifically discriminate individuals with frailty from non-frailty. The metabolites that were most discriminating of frailty status may imply an underlying mechanism involved in antioxidation and mitochondrial function. These findings offer important references for the management of frailty and sarcopenia. Subsequent studies are needed to confirm our findings and to further determine whether these metabolites can indeed be used as potential biomarkers for frailty.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of the Beijing Hospital of the National Health Commission. The patients/participants provided their written informed consent to participate in this study.LM: designed the study, analyzed the data, and drafted the paper. R-yY: performed the study, detection of metabolites, and contributed to the writing of the manuscript preparation. HS: contributed to the design of the work, and helped in execution of research. D-gW: sample collection and preparation, detection of blood chemical parameters. JShi, W-bW, JShe, Y-mD, and G-qF: performed the study and collected the data. P-lY and JD: helped in execution of research. HX: initiated the study, supervised the writing of the manuscript. All authors contributed to the article and approved the submitted version.The study was supported by the grants from the National Key R&D Program of China , the National Natural Science Foundation of China (No. 81672075) and Beijing Natural Science Foundation (No.7222156).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Ketogenic diet (KD) and pulsatile dexamethasone therapy (PDT) are commonly used in the treatment of children with drug resistant epilepsy. Potential side effects of the KD are hypoglycemia, whereas PDT might lead to hyperglycemia. One practical option to measure glucose concentrations regularly is the flash glucose monitoring system (FGM). In this single-center study in Germany, two pediatric patients with epilepsy (age: 6.0 and 6.8 years) received FGM from the beginning of the KD over six months, in the year 2020, and one patient (9.8 years) was observed for one month on PDT and switched to the KD thereafter. Glucose concentrations were measured by using an FGM system and capillary blood measurement. Seizure frequency, changes in cognition, motor performance, social behavior, and sleep quality were evaluated. The mean hypoglycemia rate per day (65 mg/dL and lower) declined significantly in patient 1 and 2 after three months. Patient 3 showed in total seven hyperglycemic events during PDT. Patient 1 became seizure free. Improvement of attention and memory performance were reported. FGM during the KD as a treatment for drug resistant epilepsies in childhood is a practical option to explore and to avoid hypoglycemia during the KD and hyperglycemia during PDT. Epilepsy is one of the most common neurological diseases found in childhood. Up to one third of the patients with epilepsy treated show pharmaco-resistance . One freDespite the positive results on seizure reduction, one potentially harmful consequence of the KD is the incidence of either acute and severe or chronic and non-severe hypoglycemia ,10,11. T® . In this system, a wired enzyme sensor patch is placed in the musculus triceps brachii, and glucose measurements are shown by swiping a scanner over the sensor. The advantages of the FGM are the precision and stability of the measurements, as well as usage for 14 days without calibration [A practical method to continuously observe glucose concentration is the interstitial glucose measurement using a flash glucose monitoring system (FGM), such as the FreeStyle libreibration . The effibration , and witibration , highligAnother effective treatment of drug resistant epilepsy in children is intravenous corticoid therapy. Several intractable epilepsy syndromes of childhood, such as continuous spike-and-wave during sleep, West Syndrome, and electrical status epilepticus during slow-wave sleep (ESES), when treated with pulsatile dexamethasone therapy (PDT) showed a significant decrease in seizure frequency or improvement of the electroencephalogram ,22. ConcTo date, data concerning continuous glucose measurement in patients with epilepsy on the KD or PDT to quantify hypo- and hyperglycemia rates are lacking. Therefore, the goal of this case series of three pediatric patients with drug resistant epilepsy on the KD or PDT, is to provide an insight into the control of glucose and ketone concentrations with a FGM system.The study was approved by the Ethics Committee of the Ostallgäu-Kaufbeuren hospital group, Germany. Patients and their parents gave consent to participation. Patients were recruited from the children’s unit of Kaufbeuren Hospital.For patient 1 and 2, the observational period began at the initiation of the KD and lasted for six months. Patient 3 received PDT for one month and was subsequently switched to a three-month period of the KD.®). Glucose was determined by using the implanted glucose sensor, FreeStyle libre®. For additional calibration, glucose was determined several times per day by capillary blood glucose measurement. Parents reported the capillary blood glucose measurement in a diary with additional notes about clinically related symptoms such as nausea or fatigue. Hypoglycemia was defined according to the International Society for Pediatric and Adolescent Diabetes (ISDAP) Clinical Practice Consensus Guidelines 2014, as a serum glucose level of 65 mg/dL or lower [Glucose and ketone concentrations were controlled using a flash glucose monitoring system , motor skills, social behavior, emotional state, and sleep quality , each measured before, during, and after the treatment.The girl was born by caesarean section. At the age of 5.4 years, generalized seizures occurred. In the electroencephalogram (EEG), interictal epileptiform discharges (IEDs) over both hemispheres were registered. During the following years, an increasing number of seizures occurred including one grand mal seizure with status epilepticus. Family history was negative, cognitive performance and attention was declining, as reported by the mother. MRI of the brain showed no abnormalities. Clinical, biochemical, metabolic, and cardiologic (electrocardiogram (ECG), 24 h ECG, blood pressure measurement and echocardiography), as well as genetic evaluation, revealed no abnormal findings.After initial treatment with levetiracetam, she was switched to valproate due to aggressive behavior and an increasing frequency of atonic seizures. Consecutively, rufinamide and clobazam were added in combination.KD—Observational period:At age 6.0 years, the girl was diagnosed with ESES. A 2.5:1 KD consisting of 2.5 times the amount of fat as carbohydrates was initiated, alongside a treatment with valproate and clobazam. For example, this equates to 2.5 g of fat per 1 g of carbohydrates. Eleven weeks after the beginning of the KD, lamotrigine administration was started and clobazam was withdrawn.The boy was born by vaginal delivery. Starting at the age of 3.7 years, he showed focal myoclonia with pathological EEG (grade III). MRI of the brain showed no abnormalities. Clinical, ophthalmologic, biochemical, metabolic, and genetic evaluation revealed no abnormal findings. First, he was treated with levetiracetam, clobazam, and zonisamid. Due to continuing seizures, a cortisone therapy was initiated at age 4.8 years, with no significant decrease in interictal activity. During the clinical evaluation of the cortisone therapy, cardiologic evaluation revealed a pulmonary valve insufficiency and a tricuspid insufficiency.Although the boy was treated consecutively with topiramate, potassium bromid, and perampanel, myoclonic seizures increased in frequency and severity. The patient showed up to 100 myoclonia per day with severe falls. Additionally, ADHD was diagnosed, and amphetamine was administered.KD—Observational period:At age 6.8 years, the KD was started in conjunction with a parallel treatment with perampanel, clobazame, and zonisamid. After three months, the 3:1 KD consisting of three times the amount of fat as carbohydrates was switched to a 2.5:1 KD, due to weight gain and dry skin.The girl was born by vaginal delivery. Postnatally, microcephaly was registered, and the development of language and fine motor skills were delayed. At the age of 7.4 years, ADHD was diagnosed and, therefore, the girl was treated with methylphenidate, which was later switched to guanfacine and then later to risperidone. In the EEG, focal and generalized IEDs, as well as generalized slowing were found, and the girl was diagnosed with ESES. MRI of the brain showed no abnormalities. Biochemical and metabolism evaluation revealed no abnormal findings. Genetic analyses showed a mutation of FBXO11, which can be associated with intellectual disability and behavioral anomalies .Previously, the girl was treated with levetiracetam, valproate, sultiam, and lamotrigine, which led to behavioral problems.PDT and KD—Observational period:2 of body surface for three days each week at three-week intervals, administered in 10 cycles. The observational period was 30 days (including two cycles). The PDT effectuated neither significant clinical nor EEG improvement. Therefore, a 3:1 KD was subsequently initiated for three months.At the age of 9.8 years, PDT was started with a dose of 20 mg/mt-test. Correlations between glucose and ketone concentrations were calculated using the Spearman correlation coefficient with Holmes multiple comparison correction. All analyses were performed two-tailed with p-values ≤ 0.05 indicating statistical significance. Statistical analyses were performed using the Statistical Package for Social Sciences for Windows  and R language script.Hypoglycemia rate was calculated as the percentage of hypoglycemic measurements of the total number of glucose measurements per day registered by the FGM. Comparisons between hypoglycemia rates were performed using the non-parametric Welsh’s Glucose concentrationsPatient 1 had a total amount of 1979 glucose concentration measurements  registered over the observational period of six months. Thereof, 1064 measurements of glucose concentration  were registered during the first three months and 915 measurements  were registered during the following three months (months 4–6 since the beginning of the KD).Overall, 473 events of moderate hypoglycemia with a minimum of 34 mg/dL, not related to day or night, were recorded (Mean ± SD: 59.8 mg/dL ± 4.5 mg/dL). During the first three months, 287 events , and during the second three months, 186 events  of moderate hypoglycemia were measured. Moreover, 54 events of significant hypoglycemia (serum glucose 54 mg/dL or lower) occurred throughout the six month observational period, where 35 were registered during the first three months, and 19 were registered during the second three months.p = 0.028) (The hypoglycemia rate (65 mg/dL and lower) per day was calculated for the observational period. The difference between the hypoglycemia rate in the first three months (Mean ± SD: 0.18 ± 0.27) and the last three months (Mean ± SD: 0.09 ± 0.15) was statistically significant (= 0.028) .Ketone concentrationsp = 0.004).In total, 1066 ketone concentrations were registered  over the observational period of six months. During the first three months, 529 ketone concentrations , and during the second three months, 537 ketone concentrations  were measured. The correlation between ketones and glucose concentration was statistically significant , motor performance, emotional state, and sleep quality. In the questionnaire, concerning language and social behavior, no differences were observed.Glucose concentrationsPatient 2 had a total amount of 1336 glucose concentrations  registered during the observational period of six months. Thereof, 676 measurements of glucose concentration  were registered during the first three months and 660 measurements  were registered during the following three months (months 4–6 since the beginning of the KD).Overall, 319 events of moderate hypoglycemia with a minimum of 41 mg/dL, irrespective of day or night, were recorded (Mean ± SD: 59.3 mg/dL ± 4.9 mg/dL). During the first three months, 188 events , and during the second three months, 131 events  of moderate hypoglycemia were measured. Moreover, 48 events of significant hypoglycemia (serum glucose level 54 mg/dL or lower) were recorded over the six month observational period, of which 29 were registered during the first three months and 19 were registered throughout the following three months.p = 0.002)  and the last three months (Mean ± SD: 0.20 ± 0.16) was statistically significant (= 0.002) .Ketone concentrationsp = 0.01).In total, 906 ketone concentrations were registered  during the observational period of six months. During the first three months, 396 ketone concentrations , and during the second three months, 510 ketone concentrations  were measured. The correlation between ketones and glucose concentration was statistically significant , motor performance, social behavior, emotional stability, and sleep quality. Language improvement was only marginal.Phase 1—PDTPatient 3 had a total amount of 96 glucose concentrations measured in capillary blood and registered over the observational period of one month.Overall, seven events of hyperglycemia with a maximum of 160 mg/dL, and two events of hypoglycemia with a minimum of 54 mg/dL, not related to day or night, were recorded (Mean ± SD: 98.9 mg/dL ± 22.7 mg/dL) . MoreovePhase 2—KDIn the phase of the KD, a total measurement of 847 glucose concentrations  were registered over the observational period of three months. Overall, 48 events of moderate hypoglycemia with a minimum of 44 mg/dL, not related to day or night, were recorded (Mean ± SD: 60.9 mg/dL ± 4.5 mg/dL). Moreover, five events of significant hypoglycemia (serum glucose level 54 mg/dL or lower) were registered throughout the observational period of three months. The mean hypoglycemia rate per day was 0.2 (SD 0.26). A total of 241 ketone concentrations were registered  during the observational period of three months.Overall, no seizures associated with hypoglycemia or ketone concentrations outside the therapeutic range were registered during the observational period. The mother reported improved cognition related to concentration and memory. No differences were observed regarding language, motor performance, social behavior, emotional stability, and sleep quality.The comparison between the mean hypoglycemia rate per day of the first three months and the last three months of the KD in patient 1 and 2 are presented in In this case series, the glucose concentrations of three pediatric patients were observed during the KD and PDT as treatment options for drug resistant epilepsies in childhood. The most important finding is that hypoglycemia, as a well-known adverse effect of the KD with potential long-term harmful consequences, is especially common in the beginning of the KD and declines significantly thereafter.Our results are, therefore, in line with our previous findings in a pediatric patient with Dravet Syndrome using an FGM system over an observational period of six months, where a decline in the hypoglycemia rate three months after the beginning of the KD was shown . In addiDue to the high effort of regular blood measurements, glucose concentrations are often not controlled during the KD in clinical practice. The FGM system offers a permanent measurement of glucose concentrations and can be used for 14 days without calibration. Our two patients that were observed over six months, showed a significant decline in the hypoglycemia rate after three months. This is also in line with previous findings describing hypoglycemia, particularly during diet initiation . Our thiNone of the children showed seizures throughout the observational period that were linked to hypoglycemia or ketone concentrations beyond the therapeutic range. Greater ketone concentrations within the therapeutic range are essential for an adequate ketosis, which plays a major role in the pathophysiological basis of the KD. However, as we found a weak negative correlation between glucose and ketone concentration, comparable to our previous findings , glucoseOverall, all three patients responded well to the KD and showed an improvement of the EEG up to seizure freedom. These findings are equivalent to other studies demonstrating the positive effect of the KD in children with pharmaco-resistant epilepsy ,4,33,34.Patient 3 of our case series received PDT for one month before switching to the KD for three months. Hyperglycemia can occur as a side effect during PDT, and chronic hyperglycemia in particular may have harmful effects on brain development and cognition ,23,25,26Our results showed that hypoglycemia is an adverse effect especially when starting the KD. This is in line with previous studies ,20. HoweThe main limitation of this study is the low number of patients. On the one hand, the three cases cannot be compared regarding sex, age, or type of epilepsy. On the other hand, similar trends in glucose concentrations were evident in all patients, pointing to the transferability of the results to different types of drug resistant epilepsies.The KD is an option in the treatment of pharmaco-resistant epilepsy in children. Hypoglycemic events occurred particularly at the beginning of the KD and declined thereafter; hyperglycemic events during PDT were rare in our case. To avoid long-term negative impacts of acute and chronic hypoglycemia, glucose concentration should be monitored regularly. The FGM or CGM systems might be a practical and easy tool for children with epilepsy who are on the KD or are receiving PDT.


Children and youth are recommended to achieve at least 60 min/day of moderate-to-vigorous physical activity, no more than 2 h/day of recreational screen time, and a sleep duration of 9–11 h/night for 11–13-year-olds or 8–10 h/night for 14–17-year-olds. Meeting the physical activity, screen time, and sleep duration recommendations have previously been associated with substance use among adolescents. However, previous research has mainly examined these factors individually rather than looking at how these indicators could concurrently relate to substance use in this age group. Therefore, this study examined the associations between meeting the 24-h movement guidelines for screen time, sleep duration, and physical activity (independent variables) with substance use outcomes including alcohol consumption, cannabis use, and cigarette smoking (dependent variables) among adolescents. Self-reported data from a cross-sectional and representative sample of 10,236 students (mean age = 15.1 years) in Ontario, Canada were analyzed. Logistic regression models stratified by gender were adjusted for potential confounders. Combinations of 24-h movement guidelines was differentially associated with substance use in boys and girls. Overall, findings showed that meeting 24-h movement guidelines is associated with lower odds of alcohol consumption, cannabis use, and cigarette smoking differentially with type of recommendation met and gender. Given that the associations between 24-h movement guidelines and substance use differ between boys and girls, future efforts should take this into consideration. Substance use in adolescence is a major public health problem around the world. It is often initiated in adolescence and continues into adulthood . TobaccoSome factors that have received greater attention over the past decades are physical activity, screen time, and sleep duration. In general, active living and sufficient sleep duration have many health benefits and contribute substantially to the quality of life across the lifespan ,12,13,14However, these lifestyle behaviors  have often been examined in isolation, ignoring how they interact with each other. The Canadian 24-h Movement Guidelines for Children and Youth account for the interaction and codependence between physical activity, sedentary behavior, and sleep . The guiResearch has indicated that boys are more likely than girls to engage in some types of substance use, and previous studies have found important gender differences in the relationship between physical activity and alcohol consumption, cannabis use, and cigarette smoking . RecentlMost research studies have mainly examined the associations between physical activity, screen time, and sleep duration and substance use among adolescents individually rather than looking at how these indicators could concurrently relate to substance use in this age group. However, the relationships between different combinations of movement behaviors and substance use among adolescents is largely unknown. It is thus unknown whether adhering to all or certain combinations of guideline recommendations is associated with a better substance use profile among adolescents. Gaining such knowledge is important because substance use, such as alcohol consumption, cannabis use, and cigarette smoking are of particular concern among adolescents ,33, theyTo address this knowledge gap, and to inform public health efforts against adolescent substance use, the present study examined the associations between adherence to the recommendations in the Canadian 24-h Movement Guidelines and substance use among adolescents. It was hypothesized that adherence to the Canadian 24-h Movement Guidelines would be associated with lower substance use among adolescents, particularly among boys and younger adolescents because they tend to meet the guidelines more frequently than girls and older adolescents.Data from the 2017 cycle of the Ontario Student Drug Use and Health Survey  were analyzed. The OSDUHS is a biennial cross-sectional survey of Ontario students enrolled in grades 7 through 12 (aged 11 to 20 years or over) in publicly funded schools, representing nearly 93% of the Ontario adolescent population . The surThe measures for individual movement behaviors were obtained from the Centre for Disease Control (CDC)’s Youth Risk Behavior Survey (YRBS) .Physical activity was measured using an item that asked students how many of the last 7 days they were physically active for at least 60 min each day. Students were asked to (1) add up all the time they spent in any types of physical activity that increased their heart rate and made them breathe hard some of the time ; and (2) to include both school and non-school activities. Response options ranged from 0 to 7 days. For analysis, “7 days” corresponded to students that met the physical activity guideline recommendation . The remScreen time was assessed using an item that asked students to indicate how many hours a day, on average, they spend watching TV/movies/videos, texting, playing video/computer games, emailing, or surfing the Internet in their free time. Spending no more than 2 h per day of screen time represented adherence to the screen time recommendation . Not meeSleep duration was assessed using a question that asked on an average school night, how many hours of sleep do students get. A binary variable was created defining adherence to the sleep duration based on the recommended range , contrasting with getting insufficient sleep . This seSimilar to the independent variables of physical activity, screen time, and sleep duration, outcome measures were also derived from the CDC’s YRBS . Alcoholz-score, and subjective socioeconomic status (SES). Age was measured in years, gender determined by being boy or girl, and ethnicity captured different ethnoracial backgrounds, including White, Black, East and South-East Asian, South Asian, and Other. Subjective SES was assessed using an adapted version of the MacArthur Scale of Subjective Social Status [2) and converted it into z-scores following the World Health Organization’s reference data [Covariates included age, ethnicity, gender, body mass index (BMI) l Status . Studentnce data .2 test adjusted for the complex survey design  and an adjusted Wald test were used to test (for continuous variables) the statistical differences between boys and girls and between 11- to 14-year-olds and 15- to 20-year-olds. Correlations between substance use and meeting individual movement recommendations were examined using a combination of pairwise Pearson’s and Spearman correlations. The strength of the correlation coefficients was categorized as follows: weak (less than 0.4), moderate (0.4 to 0.7), and strong (more than 0.7) [p < 0.05) for all outcomes. However, for cannabis use only, a two-way interaction between age and movement behaviors was significant, but not three-way interaction between gender, age, and movement behaviors; thus, analyses for cannabis use were also stratified by age groups. Meeting individual guideline recommendations was binary coded as 0 (not meeting the guideline) or 1 (meeting the guideline). A new variable was constructed to represent different combinations of the three guideline recommendations, thus generating eight categories  where meeting none of the guidelines was treated as the reference category.Participant characteristics were described via proportions and means. A Pearson’s χhan 0.7) . Subsequz-score, and subjective SES as potential confounders. A total of 10,236 participants out of 11,435 were retained for our analyses, because they had complete information on all variables of interest. Compared to included participant, those who were excluded (due to missing data) were more likely to be aged 11-to-14-years (58.6% vs. 37.7%), less likely to be of a White ethnicity (48.0% vs. 56.2%), had higher BMI z-scores, and were more likely to meet the sleep duration recommendation (44.8% vs. 33.8%)  and substance use outcomes of alcohol consumption, tobacco smoking, and cannabis use (dependent variables) were examined using logistic regression analyses. The regression models controlled for ethnicity, gender, BMI . 33.8%) . Given tp = 0.093). Boys were more likely than girls to meet the physical activity recommendation only (p < 0.001), whereas girls were more likely than boys to meet the screen time recommendation only (p < 0.001). Boys were more likely than girls to meet all three recommendations (p < 0.001). Boys were also more likely than girls to report smoking tobacco cigarette (p = 0.037). The prevalence of adherence to the screen time, sleep duration, and physical activity recommendations was greater for 11 to 14-year-olds than for 15-to-20-year-old counterparts (p < 0.001). Conversely, 15-to-20-year-olds were more likely than 11-to-14-year-olds to report smoking tobacco cigarette, consuming alcohol, and using cannabis (p < 0.001) (< 0.001) .Correlation coefficients among substance use and meeting individual guideline recommendations are presented in As shown in As shown in Results of sensitivity analyses using more severe levels of substance use as the exposure are outlined in This is the first study to examine the association between all possible combinations of screen time, sleep duration, and physical activity with substance use among adolescents. Past research has mainly focused on investigating the associations between a single recommendation of the guidelines and substance use among adolescents ,20,21,32Meeting movement behavior guidelines has been associated with improved indicators of physical, mental, and social health, such as less impulsivity, better self-regulation, cognition, and decision-making, higher social connectedness, and better psychosocial functioning ,47. All Our results showed that adherence to the physical activity recommendation was associated with lower odds of smoking tobacco cigarette and cannabis use among boys. Whereas among girls, meeting both the physical activity and sleep duration recommendations was associated with lower odds of smoking tobacco cigarette; and, adherence to the physical activity recommendation only or all three recommendations were associated with lower odds of cannabis use. Our results are in line with previous research suggesting that physical activity may protect adolescents from smoking and cannabis use ,51. In aAdherence to the sleep duration recommendation only was associated with lower odds of alcohol consumption among boys. However, adherence to the sleep duration recommendation only, screen time recommendation only, or both was associated with lower odds of alcohol consumption among girls. These findings identify sleep duration as an important correlate of alcohol consumption and are somewhat consistent with previous studies that have found that short sleep duration is associated with the age of onset and total alcohol consumption among adolescents ,21,54 anSurprisingly, meeting both the physical activity and screen time recommendations was associated with greater odds of alcohol consumption. These findings are contrary to our hypothesis that adherence to the 24-h movement guidelines would be negatively associated with substance use among adolescents and deserve further investigation. There is compelling evidence that physical activity, particularly competitive sport, is positively associated with current and future alcohol use among adolescents and young adults ,68. ReseOur results showed that meeting both the physical activity and screen time recommendations was associated with lower odds of cannabis use among boys. Whereas among girls, adherence to the physical activity recommendation only or all three recommendations was associated with lower odds of cannabis use. Our results are somewhat consistent with previous studies indicating a negative association between physical activity and cannabis use . For exaResults further indicated that adherence to the sleep duration recommendation only or both the sleep duration and screen time recommendations was associated with lower odds of cannabis use among 11- to 14-year-olds but not among 15- to 20-year-olds. Our results are consistent with previous studies that have identified sleep duration as an important correlate of cannabis use among adolescents. For example, in a prospective study of over 800 US adolescents aged 12 to 16 years, Miller et al.  found thStrengths of this study include: (1) The fact that it was based on a large and representative sample of the Ontario school population; (2) an assessment of multiple substance use outcomes, specifically alcohol consumption, cannabis use, and cigarette smoking; (3) a focus on adherence to different combinations of movement behavior recommendations, as previous studies have been limited to adherence to individual recommendations; and (4) the inclusion of a comprehensive set of covariates that statistically controlled for important confounding variables, strengthening the internal validity of the findings. Some limitations of the study should be noted. First, the cross-sectional nature of the data precludes temporality and inference of causality between adherence to the 24-h movement guidelines and substance use. Second, physical activity, screen time, sleep duration, and substance use were based on self-reports, and may be subject to recall or desirability biases. Third, the present study did not measure types of physical activity nor screen time. Research has shown that different types/intensities of physical activity and different types of screen time could be differentially associated with substance use in children and adolescents ,78. FourFindings from this study suggest that adherence to the 24-h movement behavior recommendations is differentially associated with lower odds of alcohol consumption, cannabis use, and cigarette smoking among adolescent boys and girls. Overall, meeting all of the 24-h movement behavior guidelines was not associated with substance use in boys, and even in girls, only less cannabis use was. Rather, certain individual or combinations of guidelines were more associated with substance use in boys and girls. No gradient or dose response was documented in our data. More specifically, our study identifies physical activity as an important correlate of reduced cigarette smoking, short sleep duration as an important correlate of alcohol consumption, and both physical activity and sleep duration as important correlates of lower cannabis use among adolescents. Replications studies using a larger sample size, objective measures of 24-h movement behaviors, and prospective data are needed to confirm our findings, explain the observed differences across gender and age, and examine if encouraging students to meet the 24-h movement guidelines could protect against substance use.


Kidney transplantation can prevent renal failure and associated complications in patients with end-stage renal disease. Despite the good quality of life, de novo cancers after kidney transplantation are a major complication impacting survival and there is an urgent need to establish immunosuppressive protocols to prevent de novo cancers. We conducted a multi-center retrospective study of 2002 patients who underwent kidney transplantation between 1965 and 2020 to examine patient and graft survival rates and cumulative cancer incidence in the following groups categorized based on specific induction immunosuppressive therapies: group 1, antiproliferative agents and steroids; group 2, calcineurin inhibitors (CNIs), antiproliferative agents and steroids; group 3, CNIs, mycophenolate mofetil, and steroids; and group 4, mammalian target of rapamycin inhibitors including everolimus, CNIs, mycophenolate mofetil, and steroids. The patient and graft survival rates were significantly higher in groups 3 and 4. The cumulative cancer incidence rate significantly increased with the use of more potent immunosuppressants, and the time to develop cancer was shorter. Only one patient in group 4 developed de novo cancer. Potent immunosuppressants might improve graft survival rate while inducing de novo cancer after kidney transplantation. Our data also suggest that everolimus might suppress cancer development after kidney transplantation. In patients with end-stage renal disease, kidney transplantation is a promising treatment to prevent renal failure and associated complications . The intThe phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway is a major critical node for a wide range of normal cellular functions. Moreover, activation of the PI3K/Akt/mTOR pathway contributes to carcinogenesis  and playThe mTORis are also used as immunosuppressive agents to prevent allograft rejection in transplant patients ,14. ImmuIn the present study, we aimed to investigate cancer trends and cancer-specific and all-cause mortality rates in kidney transplant recipients receiving different induction immunosuppression protocols. In addition, we examined the efficacy of the mTORi, everolimus, in cancer prevention.n = 933), Hyogo Prefectural Nishinomiya Hospital (n = 654), and Osaka General Medical Center (n = 415) between 1 June 1965 and 30 June 2020. All data were collected and analyzed on 30 September 2020 using the REDCap® electronic registration software . We performed cancer screening including computed tomography and abdominal ultrasonography for all recipients once a year and registered the results to the software.In this multi-center retrospective study, we reviewed the medical records of 2002 patients who underwent kidney transplantation in Osaka University Hospital  and prednisolone; group 2, patients who received CNIs (cyclosporine A or tacrolimus), antiproliferative agents (azathioprine or mizoribine), and prednisolone; group 3, patients who received CNIs, mycophenolate mofetil (MMF), and prednisolone; and group 4, patients who received CNIs, MMF, mTORi, and prednisolone. This group targeted patients who started taking mTORis immediately after the kidney transplantation and continued for more than a year. But in some patients, mTORis were added at least three months after the kidney transplantation. Moreover, 21 patients who received CNIs, mTORis, and prednisolone for induction immunosuppressive therapy were included in group 4. The target trough levels of CNIs at one year after kidney transplantation were 80–100 ng/mL  and 4–6 ng/mL .The collected data included relevant information such as transplant and cancer history; dialysis duration before kidney transplantation; renal allograft conditions including rejection; and history of transplantation, transfusion, and comorbidities for the analyses of demographic characteristics. In addition, data were collected to determine the rates of patient survival, graft survival, cumulative cancer incidence, and cancer types.Antilymphocyte globulin and the anti-CD25 antibody basiliximab were added to induction immunosuppressive therapy in patients undergoing kidney transplantation from 1993 to 2003 and from 2004 to 2019, respectively. Splenectomy or rituximab infusion was performed in patients undergoing ABO-incompatible kidney transplantation. Additionally, kidney biopsies were routinely performed at 3 and 12 months after kidney transplantation in patients with elevated serum creatinine levels. In patients with biopsy-proven rejection, methylprednisolone was administered for three days. The same approach was used in patients who could not be evaluated by kidney biopsy but were clinically diagnosed with rejection . In patients with steroid-resistant rejection, gusperimus hydrochloride or anti-CD3 monoclonal antibody was used after methylprednisolone treatment until 2010. Starting in 2011, thymoglobulin was used as an alternative therapy for T cell-mediated rejection. For antibody-mediated rejection, plasma exchange, rituximab infusion, and intravenous immunoglobulin therapy were used.The primary study outcome was all-cause mortality, and the secondary study outcomes were cancer-specific mortality, death-censored allograft survival rate, and cumulative cancer incidence rate. The study protocol was approved by the Institutional Review Board of Osaka University Hospital , Hyogo Prefectural Nishinomiya Hospital , and Osaka General Medical Center . All procedures were performed in accordance with the 1975 Helsinki Declaration.p-value of <0.05.The SPSS statistical software version 27  was used for all analyses. Categorical variables were presented as percentages or frequencies, and continuous variables were presented as means with standard deviation. Differences in group characteristics, graft survival, and overall survival among groups were compared. Univariate analyses were performed using the Mann–Whitney, Kruskal–Wallis, chi-square, and Fisher’s exact tests to compare continuous and categorical variables, as appropriate. The Kaplan–Meier method with the log-rank test was used to compare patient and graft survival rates. The statistical significance level was defined as a two-tailed p < 0.001, between each group). Moreover, the number of transplantations from ABO-incompatible  or unrelated donors  and the number of preemptive kidney transplantations  were statistically significantly higher in recent years.Of a total of 2002 recipients, 15 patients who received induction immunosuppressive monotherapy with steroids were excluded from the study. Therefore, 1987 patients were included in the final analysis . The sump < 0.001). Moreover, the age of cancer diagnosis was significantly different among the four groups (p < 0.001). The patient with cancer in group 4 was diagnosed at 47 years of age, previously received kidney transplantation in 2013, and received multidrug immunosuppressive therapy with tacrolimus, MMF, and prednisolone for six years after the first transplantation. Finally, there was no significant difference in sex among the four groups.In the overall cohort, 242 patients were diagnosed with de novo cancers, including 30 patients who developed two primary cancers and three patients who developed three primary cancers after transplantation . The mean = 10, 23.8%) whereas post-transplant lymphoproliferative disorders , renal cell carcinoma , and breast cancer  were the most common malignant neoplasms in groups 2 and 3. Hepatocellular carcinoma  and gastric cancer , two frequent malignant neoplasms in groups 1 and 2, were less common in group 3 . The number of patients with prostate cancer increased gradually, with 1 (2.4%), 4 (3.4%), and 5 (6.3%) patients in groups 1, 2, and 3, respectively. Lung cancer, one of the most common cancers in the general population, was diagnosed in only a few patients in each of the groups 1  and 2 .The comparison of cancer types among the four group is presented in p = 0.007, Gray’s test). This result suggested that the addition of mTORi to conventional immunosuppressive therapy may reduce the cancer incidence rate. Since the prognosis of skin cancer except melanoma is unlikely to generate a clinically relevant change in survival, the cumulative cancer incidence excluding non-melanoma skin cancers was also calculated. The 5-year survival rates were 0.0%, 1.1%, 4.7%, and 0.4% in groups 1, 2, 3, and 4, respectively .The 5-year cumulative de novo all cancer incidence rates after kidney transplantation were 0.0%, 1.0%, 5.3%, and 0.4% in groups 1, 2, 3, and 4, respectively a. Moreovectively b. The 10p < 0.001, log-rank test) except for that between groups 3 and 4 (p = 0.252). Moreover, the 5-year cancer-specific survival rates after kidney transplantation were 100%, 99.4%, 99.1%, and 100% in groups 1, 2, 3, and 4, respectively .As shown in ectively b. The dip < 0.001, log-rank test).The 5- and 10-year death-censored graft survival rates after kidney transplantation were 69.4% and 60.3% in group 1, 84.2% and 73.0% in group 2, and 92.8% and 85.9% in group 3, respectively . The 5-yIn the present multi-center, retrospective study of 1987 patients who underwent kidney transplantation during a long time period between 1965 and 2020, we found that the cumulative cancer incidence rate after kidney transplantation increased with the introduction of new and more effective immunosuppressive drugs. These results lend further support to our previous report revealing that the aggressiveness of immunosuppressive treatment regimens or the use of potent immunosuppressives might increase the risk of de novo cancer after kidney transplantation despite the improvement of graft survival rates .De novo cancer after kidney transplantation is one of the most threatening complications that reduces graft survival  and is aA study previously reported that patients on mTORi-based therapy had a 59% reduced relative risk of developing new cancers  than those on CNI-based therapy , suggestn = 2, type C only; n = 6, both; n = 3, respectively). Blood transfusion associated with end-stage renal disease is also a cause of hepatitis. It is strongly likely that the decrease in the rate of hepatitis due to the development of erythropoiesis-stimulating agents and direct-acting antivirals has led to a decrease in the rate of HCC after kidney transplantation. On the other hand, the rates of renal cell carcinoma and prostate cancer increased in group 3 compared to groups 1 and 2. The duration of hemodialysis before kidney transplantation was also significantly longer in group 3. The preoperative dialysis period before kidney transplantation was previously reported to be correlated with the rate of renal cell carcinoma [Of course, incidence and survival rates of specific cancers are not determined by whether mTORi is used for induction immunosuppressive therapy. The background characteristics contributing to specific cancer incidences should be carefully considered. For example, our results indicated that the incidence of hepatocellular carcinoma (HCC) was lower in group 3 than in groups 1 and 2. Hepatitis B and C virus infections are the main causes of HCC. Our data also showed that 11 of 13 cases were infected with at least hepatitis B or C. . However, various adverse events  occurred at high rates, and it was often difficult to continue ,41,42. FThe present study has several notable strengths. This study was based on a large population of kidney transplant recipients from several high-volume centers. The study analyses were based on a comprehensive dataset with a long duration and very few missing values. The completeness of the dataset suggests that selection and ascertainment biases in exposure and study factors were minimal. However, the present study has several limitations that should also be acknowledged. First, this was a retrospective study, and the observation period of group 4 was notably shorter than that of the other groups. Therefore, although mTORi has been shown to reduce cancer morbidity with short-term observations, we believe that the efficacy of mTORi needs to be reassessed at long-term observations. Second, despite the adjustment for all confounding factors, there may be unmeasured residual effects such as details on the dose and duration of immunosuppressants used for the treatment of primary disease and incomplete details on smoking habits and alcohol consumption, which might have altered the strength and magnitude of association of cancer risk after transplantation. Third, some patients in groups 1, 2, and 3 received mTORis after the cancer diagnosis, although the treatment was initiated several years after the kidney transplantation. Finally, cancer treatment approaches and reductions in immunosuppressant doses in patients who developed cancer were determined by the attending physician in each case. However, despite these limitations, the current study findings are important as they are based on the largest Japanese cancer registry data of patients with kidney transplants. Especially, it is noteworthy that in group 4, the prevalence of de novo cancers at the early phase after kidney transplantation was clearly lower than in the other groups, despite the significantly older recipients.Despite the improvement of patient and graft survival rates with the increasing potency of immunosuppressants, the cumulative cancer incidence rate after kidney transplantation increased, with a tendency for a shorter time from kidney transplantation to cancer development. The addition of mTORis to conventional induction immunosuppressive therapy was not only associated with improved patient and graft survival rates but also with reduced cancer incidence, at least in the short term after kidney transplantation. The current study findings have potential clinical significance, including the optimization of effective immunosuppressive therapies to prevent the development of post-transplantation cancer, which requires further long-term studies.


Francisella tularensis is one of several biothreat agents for which a licensed vaccine is needed to protect against this pathogen. To aid in the development of a vaccine protective against pneumonic tularemia, we generated and characterized a panel of F. tularensis isolates that can be used as challenge strains to assess vaccine efficacy. Our panel consists of both historical and contemporary isolates derived from clinical and environmental sources, including human, tick, and rabbit isolates. Whole genome sequencing was performed to assess the genetic diversity in comparison to the reference genome F. tularensis Schu S4. Average nucleotide identity analysis showed >99% genomic similarity across the strains in our panel, and pan-genome analysis revealed a core genome of 1,707 genes, and an accessory genome of 233 genes. Three of the strains in our panel, FRAN254 (tick-derived), FRAN255 (a type B strain), and FRAN256 (a human isolate) exhibited variation from the other strains. Moreover, we identified several unique mutations within the Francisella Pathogenicity Island across multiple strains in our panel, revealing unexpected diversity in this region. Notably, FRAN031 (Scherm) completely lacked the second pathogenicity island but retained virulence in mice. In contrast, FRAN037 (Coll) was attenuated in a murine pneumonic tularemia model and had mutations in pdpB and iglA which likely led to attenuation. All of the strains, except FRAN037, retained full virulence, indicating their effectiveness as challenge strains for future vaccine testing. Overall, we provide a well-characterized panel of virulent F. tularensis strains that can be utilized in ongoing efforts to develop an effective vaccine against pneumonic tularemia to ensure protection is achieved across a range F. tularensis strains. Francisella tularensis is a gram-negative bacterium that causes the potentially life threatening and debilitating disease tularemia. F. tularensis is able to infect a wide range of animal species, including humans. F. tularensis can be transmitted to humans through a number of routes, the most common being the bite of an infected insect or other arthropod vector (F. tularensis subsp. tularensis (type A) and the less virulent F. tularensis subsp. holarctica (type B).d vector . Human id vector . In pneud vector . The risF. tularensis had been weaponized for the potential use by several countries  Department of Health and Human Services as a Tier 1 Select Agent  derived from a type B strain of et Union . In the lunteers . Howeverlunteers . In addiF. tularensis challenge model  against another type A isolate, FSC033, showing that Schu S4 was less virulent during intradermal and aerosol infection of mice  with 12.5% glycerol and stored at –70°C until needed. Single use vials from each lot were randomly checked for purity by observing colony morphologies on chocolate agar after 24, 48, and 72 h at 35°C in 5% CO2. The randomly selected aliquots were also Gram-stained to confirm appropriate staining and morphology under a microscope. Where indicated, F. tularensis was grown in Chamberlain’s Defined Medium (CDM) (All um (CDM)  or brainde novo hybrid assembled using Spades  and assembled using HGAP4 , with deg Spades  and Unicg Spades . If comp setting , and man setting  and Mauv setting . Reads w setting , and err setting . GenbankFrancisella panel and the reference strain Schu S4, and with paralog splitting disabled. Core genes were defined as genes present in all ten strains, while the shell and cloud genes were defined as genes present in two or more strains, and genes present in 1 strain, respectively. The shell and cloud genes constitute the accessory genome. Results were visualized using Phandango . All samples were performed in quadruplicate and included medium controls to confirm sterility and for use as blanks to calculate the absorbance of the cultures.Growth assays were performed in BHI or CDM, as indicated. Assays were performed using an Infinite M200 Pro (Tecan) microplate reader in 96-well microtiter plates at 37°C with shaking. The ODF. tularensis strains. Cultures were prepared at approximately equal colony forming unit (CFU) concentrations in PBS, lysed in gel loading buffer solution, and boiled for at least 45 min and confirmed to be inactivated. Samples were fractioned on NuPage Novex 4–12% Bis-Tris gels. For western analysis, fractionated material was transferred onto a nitrocellulouse membrane using an iBlot Gel Transfer Device. After transfer, the membranes were blocked with 1% skim milk in Tris Buffered Saline + Tween 20. Samples were blotted with mouse monoclonal anti-LPS antibody  or anti-capsule antibody  . Bands were visualized using 3,3′,5,5′-Tetramethylbenzidine Membrane Peroxidase substrate .Whole-cell extracts were collected for LPS analysis from plate grown dy 11B7;  at dilutTM), were seeded (∼2.5 × 105 cells/well) into 24-well plates and cultured 2 days  at which time the cells had formed confluent monolayers. The cells were maintained in Dulbecco’s Modified Eagle’s medium containing 10% heat-inactivated fetal bovine serum (Corning 10-013-CV). For the intracellular assays, F. tularensis was suspended in phosphate buffered saline (PBS) from a 24 h plate, and then diluted 1:5 in tissue culture medium. The bacterial suspension was added to the macrophages in 200 μl of medium to achieve a multiplicity of infection (MOI) of ∼100:1, and the MOI was confirmed from this suspension by serial dilutions and plating on chocolate agar plates. The bacteria and macrophages were allowed to co-incubate for 2 h at 37oC with 5% CO2. Next, the medium containing the extracellular bacteria was aspirated and replaced with fresh tissue culture medium supplemented with 25 μg/ml of gentamycin for an additional 2 h. After this incubation, samples from the tissue culture wells were washed three times with PBS. The monolayer was then lysed with 200 μl of sterile water, immediately scraped, and suspended in 800 μl of PBS. The suspension was serially diluted in PBS and plated onto chocolate agar plates. The remaining tissue culture wells were assayed for CFU recovery at the 24 h post-infection time point as described above.J774A.1 cells, a murine macrophage-like cell line obtained from the American Type Culture Collection (TIB-67F. tularensis strains was assessed in BALB/c mice (7–9 week-old obtained from Charles River Laboratories) by intranasal challenge as previously described  was estimated by the Kaplan–Meier method. Comparisons of the median TTD between strains are obtained from a log-normal accelerated failure time model of the form Log(TTD) = m∗Log(Dose) + b, where m and b are strain-specific slope and intercept terms. A Wald test was used to compare the model estimated median TTD at the middle of the dose curve. Analysis was implemented in PROC LIFEREG and PROC PROBIT, SAS version 9.4 .Growth analysis of bacterial strains in broth media was analyzed as previously described . A logisF. tularensis isolates, which were obtained from historical and contemporary environmental and clinical sources and prepared according ISO standards and guidelines for biological reference materials. These isolates were down-selected to the 10 potential candidate strains that were used in this study , which is housed at the United States Army Medical Research Institute for Infectious Diseases (USAMRIID), contains distinct is study  by looseF. tularensis isolates.Three of the 10 strains in our panel  were derived from lyophilized samples see , not lonF. tularensis subtypes were included in our panel. Molecular sub-typing based on SNPs as described previously (Six of the strains used in this study (FRAN250-FRAN251 and FRAN253-FRAN256) had been isolated from clinical and environmental samples collected in the central U.S. during the past 5 years and donated to the BRMR by the Minnesota Department of Health (MDH). Four of the MDH strains came from human clinical samples, one was propagated from a rabbit spleen, and the sixth was extracted from a tick . We delieviously , showed F. tularensis studies. We selected this widely studied Schu S4 isolate, despite its uncertain propagation history, to compare to FRAN249, which we had propagated directly from a 1958 lyophilized sample. Since Schu S4 was originally propagated from a single colony pick in 1951 , which is commonly used in  in 1951 , the lyoirulence . For thiF. tularensis panel. To provide a measure of nucleotide level diversity across the panel for the entire genome, we calculated the pairwise Average Nucleotide Identity (ANI), and constructed a distance tree based on this analysis  using the micropan package in R. ectively . PCA ploch other . Both FRF. tularensis strains  of multiple strains within our panel, described below.Data from our UpSet plot showed a large number of genes that are mutated in the FRAN254, FRAN255, and FRAN256 strains compared to the rest of our panel. We next aimed to characterize the function of these genes and the types of mutations present. BLAST search and multiple sequence alignments were carried out for each individual gene, and functional categories were assigned to each gene. F. tularensis panel revealed diverse mutations across both FPI in several strains. These mutations occurred in the pdpA, pdpB, iglF, pdpC, and pdpD genes of the first FPI, and in the pdpC, iglA, and pdpD genes of the second FPI   to form CFU that were countable . Growth  Schu S4 . In cont Schu S4 . FRAN256< 0.001) .F. tularensis pathogenesis, we analyzed the ability of the 10 strains to grow intracellularly within J774 cells. As shown in As the ability to replicate within host cells is a hallmark of F. tularensis virulence  and FRAN037 (Coll). The mouse LD50 values for these strains was originally reported as the dilution of a standard suspension which killed 50% of the mice by intraperitoneal challenge and assayed to be 10–9.2 and 10–8.8, respectively  was also found to be <1 CFU. In contrast, no mice succumbed to challenge with the FRAN037 (Coll) strain at any of the challenged doses; thus, the LD50 would be >2,080 CFU. Based upon the results described here, we will not be advancing FRAN037 (Coll) to be part of the diversity panel.Two additional historical ectively . To conf50 determined to be <1 CFU.As no additional data were available for the clinical and environmental isolates obtained from the MDH other than listed in F. tularensis strain that showed any significant difference in TTD across all tested challenge doses was FRAN255 when compared to the other lethal strains. The P-values when comparing TTD of FRAN255 to the other virulent strains was calculated to be as follows: FRAN249 (P = 0.0281), FRAN244 (P ≤ 0.0001), FRAN031 (P = 0.0008), FRAN250 (P ≤ 0.0001), FRAN251 (P = 0.0004), FRAN252 (P = 0.0005), FRAN253 (P = 0.0007), FRAN254 (P = 0.0051), and FRAN256 (P = 0.0001). However, as described above, FRAN255 also displayed a slower growth on agar plates compared to all the other strains in our panel (The only virulent ur panel  and in Bur panel .Francisella is the lipopolysaccharide (LPS) and O-antigen capsule, which plays an important role in evasion of the host immune response . We identified an average of 3,551 nucleotide differences among strains, with a range of 23 (closely related strains) to 13,401 (distantly related strains) differences. Further characterization of these strains by pan-genome analysis showed a total of 1,707 genes in the core genome. The accessory genome was found to contain 107 shell genes and 126 cloud genes that vary from strain to strain within the panel, and which could affect the responsiveness of these strains to vaccine treatments. A recent study characterized the pan-genome of 26 Francisella strains, and found the genus contained 4,053 genes, with a relatively small core genome of 692 genes  and FRAN037 (Coll) clinical isolate strains were described as being highly virulent , and thefor mice .pdpB1 gene. PdpB has been designated a homolog of IcmF, a known component of the type VI secretion system (T6SS). Multiple studies have demonstrated PdpB localizes to the inner membrane and is required for intracellular growth, supporting its role as a structural T6SS protein  or this occurred at some point once prior to preparation for long term storage.The exact reasons for the occurrence of the FPI mutations identified in these historical strains remains to be determined. For the purpose of this study, we attempted to use isolates as close to the original isolate as available in the USAMRIID repository . Based updpA1 gene, the first gene encoded by the FPI. Studies by pdpA of F. novicida was necessary for virulence in mice, replication in murine macrophages, and involved in interruption of host cell signaling. However, PdpA is not believed to be a structural component of the T6SS, since it bears no homology to structural T6SS proteins from other bacteria, and the exact biological role of PdpA is not well defined. In our study, FRAN249 showed no virulence difference in the mouse intranasal infection model; however, a functional pdpA copy is present on the second FPI which could compensate for a non-functional pdpA. Indeed, the function of many of the FPI proteins have been defined using F. novicida, which contains only a single FPI. Given that all of our strains, except FRAN037, retained virulence in the mouse model of intranasal infection, a simple explanation could be that a functional copy of the gene was supplied on the duplicated pathogenicity island.The 1958 version of Schu S4, FRAN249, harbored a frameshift mutation in the pdpC, pdpD, and several hypothetical proteins, while the pdpA, pdpB, and iglABCD genes remained intact , they contain the same mutations: 1647delT in iglF1 and 2045delA in pdpC1.Other mutations in the FPI have been previously reported in a comparative genomics study between the Schu S4 strain and WY96, representing type A1 and type A2 strains, respectively . Of the d intact . Our stupdpC contain a single bp deletion causing a frameshift and premature stop codon. A previous study assessed the effect of loss of pdpC in LVS on expression of the surrounding FPI genes and showed that membrane integrity was still maintained in the mutant, but it was unable to escape the phagosome and was significantly attenuated during intradermal infection of mice. Interestingly the pdpC LVS mutant exhibited a cytopathogenic response, due to its fragmentation of the phagosomal membrane and subsequent triggering of the inflammasome , encoding a 371 amino acid chaperone-like protein, is divided into two ORFs in Schu S4  both copies of iglABCD are necessary for optimal virulence in mice . Interestingly, FRAN254, FRAN255, and FRAN256 harbor one functional copy of this gene, and two copies containing frameshift mutations. In the F. tularensis Schu S4 genome, these genes correspond to locus tags FTT_0354, FTT_0378c, and FTT_1263c. A protein databank search of this sequence also showed that it harbors 54% sequence similarity, although only 11% query cover, to the glucosyltransferase domain (GTD) of the Clostridium difficile toxin A (TcdA). Upon binding of the TcdA toxin to host cells, the GTD portion of the toxin is released and acts upon Rho GTPases in the cytoplasm to inactivate them via glucosylation, which triggers downstream cytopathic and cytotoxic effects  grew significantly better in BHI than the other F. tularensis strains tested. The exact reason for enhanced growth of the Schu S4 in supplemented BHI as compared to the other strains tested here remains to be determined. Previous work showed that growth of Francisella in BHI broth elicited protein expression profiles similar to that of Francisella grown in macrophages, whereas growth in CDM and Mueller Hinton broth yielded different profiles  can be found in the article/The animal study was reviewed and approved by The United States Army of Medical Research Institute of Infectious Diseases Institutional Animal Care and Use Committee (USAMRIID IACUC).BB, JR, KM, DR, and JB contributed conception and design of the study and wrote the manuscript. BB, JR, KM, CK, RT, AL, KC, JS, AR, CC, DR, and JB participated in the experimentation and acquisition of data. BB, JR, KM, DF, DR, and JB were involved in the analysis or interpretation of data for the work. All the authors contributed to manuscript revision, read and approved the submitted version.Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the U.S. Army.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.