text:
Articles & Specials
Ganiveta
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Teaching in a technology rich environment affords you the opportunity to use many online resources. I have learned from experience that students struggle to type in web addresses correctly. I found myself walking around and typing in the same address numerous times. What if you are a teacher who has checked out the iPad cart and you need your students to complete a series of tasks that require them to go to several different websites? What if you are in a "Bring Your Own Device" (BYOD) and you want students to quickly get to a location on those devices? I have the answer for you! QR codes will solve your problems. QR stands for quick response and these little scan codes are easy to create. There are tons of ways to use QR Codes in the classroom but first lets see how easy they are to create.
I was inspired by Kristy, @LoudenClearBlog, to reflect on last school year and think about what I'd like to focus on this year for 2017-2018. I've had a very restful summer. I chose to focus on family and professional growth this summer. I've since gone back to school and we just ended week 4 of 36. Although I had a hard time narrowing my list down to 5, I think I have it squared away and I'm ready to apply my list for a productive and successful school year.


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Q: Weird behaviour encountered using java.sql.TimeStamp and a mysql database The weird behavior is that a java.sql.Timestamp that I create using the System.currentTimeMillis() method, is stored in my MySQL database as 1970-01-01 01:00:00.
The two timestamps I am creating are to mark the beginning and end of a monitoring task I am trying to perform, what follows are excepts from the code where the behavior occurs
final long startTime = System.currentTimeMillis();
while(numberOfTimeStepsPassed < numTimeStep) {
/*
* Code in here
*/
}
final long endTime = System.currentTimeMillis();
return mysqlConnection.insertDataInformation(matrixOfRawData, name,Long.toString(startTime),
                                                 Long.toString(endTime), Integer.toString(numTimeStep),
                                                 Integer.toString(matrixOfRawData[0].length), owner,
                                                 type);

And here is the code used for inserting the time stamps and other data into the MySQL database
public String insertDataInformation(final  double [][] matrix,
                                    final String ... params) {
    getConnection(lookUpName);
    String id = "";
    PreparedStatement dataInformationInsert = null;
    try {
        dataInformationInsert =
                databaseConnection.prepareStatement(DATA_INFORMATION_PREPARED_STATEMENT);
        id = DatabaseUtils.createUniqueId();
        int stepsMonitored = Integer.parseInt(params[STEPS_MONITORED]);
        int numberOfMarkets = Integer.parseInt(params[NUMBER_OF_MARKETS]);
        dataInformationInsert.setNString(ID_INDEX, id);
        dataInformationInsert.setNString(NAME_INDEX, params[0]);
        dataInformationInsert.setTimestamp(START_INDEX, new Timestamp(Long.parseLong(params[START_INDEX])));
        dataInformationInsert.setTimestamp(END_INDEX, new Timestamp(Long.parseLong(params[END_INDEX])));
        dataInformationInsert.setInt(STEPS_INDEX, stepsMonitored);
        dataInformationInsert.setInt(MARKETS_INDEX, numberOfMarkets);
        dataInformationInsert.setNString(OWNER_INDEX, params[OWNER]);
        dataInformationInsert.setNString(TYPE_INDEX, params[TYPE]);
        dataInformationInsert.executeUpdate();
        insertRawMatrix(matrix, id, Integer.toString(stepsMonitored), Integer.toString(numberOfMarkets));
    } catch (SQLException sqple) {
        // TODO Auto-generated catch block
        sqple.printStackTrace();
        System.out.println(sqple.getSQLState());
    } finally {
        close(dataInformationInsert);
        dataInformationInsert = null;
        close(databaseConnection);
    }
    return id;
}

The important lines of code are :
dataInformationInsert.setTimestamp(START_INDEX, new Timestamp(Long.parseLong(params[START_INDEX])));
dataInformationInsert.setTimestamp(END_INDEX, new Timestamp(Long.parseLong(params[END_INDEX])));

The JavaDocs on the TimeStamp ( http://docs.oracle.com/javase/1.5.0/docs/api/java/sql/Timestamp.html ) says that it takes in time in milliseconds since 1st January 1970 and a simple print test confirms this.
What I am looking for is:

*

*A reason for this behavior when trying to store timestamps in a MySQL database through java.sql.Timestamp?

*Any solutions to this behavior?

*Any possible alternatives?

*Any possible improvements?

EDIT:
Been asked to include what START_INDEX and END_INDEX are:
 private static final int END_INDEX = 4;
 private static final int START_INDEX = 3;

Apologises for not putting them in the original post.

A: Okay, look at your call:
insertDataInformation(matrixOfRawData, name, Long.toString(startTime),
                      Long.toString(endTime), Integer.toString(numTimeStep),
                      Integer.toString(matrixOfRawData[0].length), owner,
                      type);

So params will have values:
0: name
1: start time
2: end time
3: numTimeStep
4: matrixOfRowData[0].length
5: owner
6: type

Then you're doing:
dataInformationInsert.setTimestamp(START_INDEX,
    new Timestamp(Long.parseLong(params[START_INDEX])));

... where START_INDEX is 3.
So you're using the value corresponding to numTimeStep as the value for the timestamp... I suspect you don't want to do that.
I would strongly advise you to create a simple object type (possibly a nested type in the same class) to let you pass these parameters in a strongly typed, simple to get right fashion. The string conversion and the access by index are both unwarranted, and can easily give rise to errors.

redpajama_set_name: RedPajamaStackExchange


Dynamint is for aches and pains, and for muscular and joint problems. Dynamint has a refreshing peppermint smell and is non-greasy upon application.Upon application the cream provides a gentle cooling sensation following by a feeling of 'applied heat'. Dynamint can also be used before sporting activity in an aid to preventing injury.


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Review article| Volume 37, 101427, January 2020
The multiple sclerosis gut microbiota: A systematic review
Ali Mirza
Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
Jessica D. Forbes
Department of Internal Medicine, University of Manitoba, University of Manitoba IBD Clinical and Research Centre, Winnipeg, MB, Canada
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
Department of Laboratory Medicine & Pathobiology, University of Toronto, ON, Canada
Feng Zhu
Charles N. Bernstein
Gary Van Domselaar
Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
Morag Graham
Emmanuelle Waubant
University of California San Francisco, San Francisco, CA, United States
Helen Tremlett
Correspondence to: Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine (Neurology), University of British Columbia, Room S126, UBC Hospital, 2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada.
Published:October 02, 2019DOI:https://doi.org/10.1016/j.msard.2019.101427
Previous ArticleThe effect of emerging nutraceutical interventions for clinical and biological outcomes in multiple sclerosis: A systematic review
Next ArticleCorrelation between EDSS scores and cervical spinal cord atrophy at 3T MRI in multiple sclerosis: A systematic review and meta-analysis
No major differences in the overall gut microbiota composition in MS cases vs. controls.
Abundance of six taxa differed in MS cases vs. controls, similarly observed across 2 ≥ studies.
Studies were generally too modest in size to adequately assess potential effect modifiers.
To systematically review and synthesize the literature on the multiple sclerosis (MS) gut microbiota composition as compared to persons without MS.
We systematically searched MEDLINE, EMBASE, and Web of Science databases for relevant published articles (2008–2018).
Of 415 articles identified ten fulfilled criteria. All studies used a case-control design, six sourced participants from the US, two Germany, one Italy, and one Japan. Nine focused exclusively on adults and one on children, totaling 286 MS and 296 control participants. Over 90% of cases had relapsing-remitting MS; disease duration ranged from 10.6 ± 6.5 months to 15.3 ± 8.6 years (mean±SD). Nine studies examined stool and one evaluated duodenal mucosa. Diverse platforms were used to quantify microbes: Illumina MiSeq, Roche 454, microarray, and fluorescence in situ hybridization. None of eight studies reported a significant alpha-diversity differences between cases and controls. Two of seven studies reported a difference in beta-diversity (P ≤ 0.002). At the taxa-level, ≥2 studies observed: lower relative abundance of Prevotella, Faecalibacterium prausnitzii, Bacteroides coprophilus, Bacteroides fragilis, and higher Methanobrevibacter and Akkermansia muciniphila in MS cases versus controls. Exposure to an immunomodulatory drug (IMD), relative to no exposure, was associated with individual taxonomic differences in three of three studies.
Gut microbiota diversity did not differ between MS cases and controls in the majority of studies. However, taxonomic differences were found, with consistent patterns emerging across studies. Longitudinal studies are warranted to elucidate the relationship between IMD exposure and differences in the gut microbiota composition.
A growing body of evidence points to the gut microbiota playing a role in immune-mediated, neurological disease, such as multiple sclerosis (MS) (
Rooks and Garrett, 2016
Rooks M.G.
Garrett W.S.Gut microbiota,
metabolites and host immunity.
Nat. Rev. Immunol. 2016; 16: 341-352https://doi.org/10.1038/nri.2016.42
Tremlett et al., 2017
Tremlett H.
Bauer K.C.
Appel-Cresswell S.
Finlay B.B.
Waubant E.
The gut microbiome in human neurological disease: a review.
Ann. Neurol. 2017; 81: 369-382https://doi.org/10.1002/ana.24901
). An important initial step to understanding the relationship between the gut microbiota and MS is to survey the gut microbial community. Recent studies on MS have focused on surveying the gut bacterial (and archaeal) communities. A common goal has been to investigate whether there are differences in the MS gut microbiota composition between MS cases and controls, measured as the overall microbiota composition (diversity) and relative abundance of individual resident microbes. Some studies also assessed potential effect modifiers (or confounders), such as exposure to an immunomodulatory drug (IMD) used to treat MS.
We conducted a systematic review in order to comprehensively collate the body of evidence surrounding the relationship between the gut microbiota and MS. Our objective was to include published articles in which the gut microbiota profiles had been compared between individuals with and without MS.
Our systematic review was designed to address the following specific questions: (1) Does the gut microbiota composition differ between MS cases and controls (participants without MS), as assessed by (a) diversity metrics and/or by (b) taxa-level relative abundances? (2) What are the main effect modifiers (confounders) identified to date in studies evaluating the gut microbiota in MS?
This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines (
Moher et al., 2010
Liberati A.
Tetzlaff J.
Group P.
Preferred reporting items for systematic reviews and meta-analyses: the Prisma statement.
Int. J. Surg. 2010; 8: 336-341https://doi.org/10.1016/j.ijsu.2010.02.007
). The systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) database (registration no. CRD42018089173) and the protocol is in accordance with the PRISMA-P (2015) guidelines (
Shamseer et al., 2015
Shamseer L
Preferred reporting items for systematic review and meta-analysis protocols. (PRISMA-P) 2015: elaboration and explanation.
BMJ. 2015; 350: g7647https://doi.org/10.1136/bmj.g7647
2.1 Eligibility criteria
Original research articles assessing the potential gut microbiota differences in diversity or taxonomic relative abundance between MS cases and controls (individuals without MS) were eligible for inclusion. We included any of the following study designs: cohort, cross-sectional, case-control, and comparative cohort studies. Other study designs were excluded, such as intervention studies (unless pre-intervention samples were available for cases/controls) and studies without a control group (e.g., case series). No restrictions were imposed with respect to the age of study participants, geographical location or setting (e.g., community or hospital), or disease course(s) under study (e.g., relapsing-onset, primary progressive).
2.2 Literature search strategy
We performed a systematic literature search of MEDLINE, EMBASE, and Web of Science databases for original research articles published in English between January 1st, 2008 and February 8th, 2018, which we subsequently updated to June 19th, 2018. At the time of publication, a final update to August 24th, 2019 was included and reported as an addendum. The search strategies for each database are shown in Fig. 1A. We did not include conference abstracts, unpublished work or the grey literature (e.g., presentations, posters, websites or dissertations).
Fig. 1Literature search strategies and PRISMA flow diagram.
A. Systematic literature search strategies of MEDLINE, EMBASE, and Web of Science databases for original research articles. B. Selection of articles for inclusion in the systematic review of the multiple sclerosis microbiota (2008–18).
2.3 Eligibility assessment, data extraction, and quality assessment
The literature search results were uploaded to Mendeley for screening. Titles and abstracts were screened based on the study inclusion and exclusion criteria by two independent reviewers (AM and JF). Any disagreement was resolved between the reviewers. The full texts of all screened-in abstracts were then retrieved and assessed for eligibility and relevant information retrieved were extracted by one reviewer (AM), as outlined in Appendix 1. Two independent reviewers (AM and JF) assessed the risk of bias in individuals studies specific to our current systematic review-related questions using the US's National Institutes of Health (NIH) tool for Quality Assessment of Case-Control Studies (
NIH National Heart
NIH National Heart, Lung, and Blood Institute. Study quality assessment tools, https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools.
). No study was excluded based on the risk of bias (rated as good, fair, and poor), in part because a study could be assigned as 'poor', inferring a high risk of bias, if the microbiota quantification platform was not valid to address our study question(s).
3.1 Study and participant characteristics
Of 415 articles identified (based on titles and abstracts), ten fulfilled criteria for inclusion (
Cantarel et al., 2015
Cantarel B.L
Gut microbiota in multiple sclerosis: possible influence of immunomodulators.
J. Investig. Med. 2015; 63: 729-734https://doi.org/10.1097/JIM.0000000000000192
Miyake et al., 2015
Miyake S
Dysbiosis in the gut microbiota of patients with multiple sclerosis, with a striking depletion of species belonging to clostridia XIVa and IV clusters.
PLoS One. 2015; 10e0137429https://doi.org/10.1371/journal.pone.0137429
Chen J
Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls.
Sci. Rep. 2016; 6: 28484https://doi.org/10.1038/srep28484
Cree et al., 2016
Cree B.A.C.
Spencer C.M.
Varrin-Doyer M.
Baranzini S.E.
Zamvil S.S.
Gut microbiome analysis in neuromyelitis optica reveals overabundance of clostridium perfringens.
Tremlett H
Gut microbiota in early pediatric multiple sclerosis: a case-control study.
Eur. J. Neurol. 2016; 23: 1308-1321https://doi.org/10.1111/ene.13026
Jangi et al., 2016
Jangi S
Alterations of the human gut microbiome in multiple sclerosis.
Nat. Commun. 2016; 7: 12015https://doi.org/10.1038/ncomms12015
Cosorich et al., 2017
Cosorich I
High frequency of intestinal T17 cells correlates with microbiota alterations and disease activity in multiple sclerosis.
Sci Adv. 2017; 3e1700492https://doi.org/10.1126/sciadv.1700492
Swidsinski et al., 2017
Swidsinski A
Reduced mass and diversity of the colonic microbiome in patients with multiple sclerosis and their improvement with ketogenic diet.
Front Microbiol. 2017; 8: 1141https://doi.org/10.3389/fmicb.2017.01141
Berer et al., 2017
Berer K
Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice.
Proc. Natl. Acad. Sci. U. S. A. 2017; https://doi.org/10.1073/pnas.1711233114
Cekanaviciute et al., 2017
Cekanaviciute E
Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models.
Proc. Natl. Acad. Sci. 2017; 201711235https://doi.org/10.1073/pnas.1711235114
). A flow chart outlining the screening process is provided in Fig. 1B (
). All ten studies used a case-control design for a total of 286 MS cases and 296 controls. Nine studies enrolled adults, of which one focused solely on twins discordant for MS, and one enrolled children. Nine studies collected stool samples from participants while one collected duodenal mucosal samples. Characteristics of the included studies are summarized in Table 1. Study quality was 'fair' for nine articles and 'poor' for one. The study identified as poor used an obsolete method (fluorescence in situ hybridization; FISH) for characterizing the gut microbiota, thus making it a high risk of bias in the context of our systematic review-specific questions (
Table 1The multiple sclerosis gut microbiota: summary of the included studies.
First Author, Year of Publication, Country
Biological Sample Type
Number of Participants (MS / Control)
Age (Years) Near Time of Sample Collection (MS / Control)
Race & Ethnicity (MS / Control)
Body Mass Index (kg/m2, MS / Control)
Diet Assessement
NIH Quality (or 'Risk of Bias') Assessement
Cantarel, 2015, United States Intervention, case-control, pilot study Stool 7 / 8 Median 42 (30–48) / 38 (29–51) White: 7 (100%) / 8 (100%) Hispanic: 0 (0%) /0 (0%) MS and controls combined range: 18 - 30 NA Fair
Miyake, 2015, Japan Case-control Stool 20 / 40 36.0 ± 7.2 / 28.5 ± 9.8 NA NA NA Fair
Chen, 2016, United States Case-control Stool 31 / 36 42.9 ± 10.6 / 40.3 ± 7.3 NA 28.0 ± 6.3 / 27.8 ± 4.7 NA Fair
Cree, 2016, United States Case-control Stool 16 / 16 54 ± 11.8 / 54 ± 15.8 White: 13 (81%) / 11 (69%)
Black: 0 (0%) / 2 (13%)
Asian: 1 (6%) / 2 (13%)
Other: 2 (13%) / 1 (6%) 23.3 ± 3.59 / 23.8 ± 4.10 Yes; Block Dietary Data Systems (NutritionQuest©) Fair.
Tremlett, 2016, United States Case-control, pilot study Stool 18 / 17 12.5 ± 4.44 / 13.5 ± 3.08 White: 9 (50%) / 13
Hispanic: 8 (44%) / 6
(35%) 22.2 ± 5.66 / 22.8 ± 7.10. Missing 1 Yes; Block Kids Food Screener (NutritionQuest©) Fair
Jangi, 2016, United States Case-control Stool 60 / 43 49.7 ± 8.50 / 42.2 ± 9.61 White: 58 (97%) / 43 (100%)
Black: 2 (3%) / 0 (0%)
Hispanic: 1 (2%) / 0 (0%) 27.2 ± 4.7 / 26.4 ± 6.3 Yes; method not reported. Fair
Cosorich, 2017, Italy Case-control Duodenal mucosa tissue 19 / 17 41 ± 2 / 48 ± 3 NA NA Yes; method not reported. Fair
Swidsinski, 2017, Germany Intervention, case-control Stool 10 / 14 NA NA NA NA Poor / High risk of bias. Taxa quantification method for assessing our study questions is obsolete
Berer, 2017, Germany Co-twin, case-control Stool 34 / 34 MS and controls combined: 41.3 ± 10.8 (21–63) NA NA Yes; method not reported. Fair
Cekanaviciute, 2017, United States Case-control Stool 71 / 71 40.7 ± 11.9 (19–64) / 44.6 ± 14.4 (22–71). Missing 9 controls and 4 cases NA NA NA Fair
Characteristics of the study participants relate to the time of microbiota sample collection (typically stool).
were missing clinical data for 8 subjects; they did not report which clinical data was missing. Continuous data are expressed as mean ± SD. NA, not available; MS, multiple sclerosis; BMI, body mass index; NIH, National Institutes of Health.
Across the nine studies which reported participant demographics, females predominated. Overall the number (%) of females/males were: 182/104 (64%/36%) for cases and 181/111 (61%/38%) for controls (sex was missing for four controls in one study (
)). The average ages of cases and controls ranged from 12–54 and 13–54 years, respectively across studies (age was missing for nine controls and four cases in one study (
)). Across the four studies that reported race and/or ethnicity, the majority of participants were Caucasian, totaling 87/101 (86%) of MS cases and 75/84 (89%) of controls. Six studies recruited participants from the United States, two from Germany, one from Italy, and one from Japan. The most commonly reported lifestyle factors were diet (five studies) and BMI (five studies), both diet and BMI were available in three studies (Table 1). Diet was collated via a validated food frequency questionnaire in two US-based studies; three did not specify. Both diet metrics and BMI (based on descriptive group means) were similar when cases were compared to controls, except for one study, which, for MS cases, observed a higher intake of specific dietary elements (i.e., carotenoids) (
The majority (267/286; 93%) of MS cases had a relapsing-remitting disease course at the time of sample collection. Five studies used the McDonald 2010 criteria for MS diagnosis, one used the Poser criteria and four did not specify (
Poser et al., 1983
Poser C.M
New diagnostic criteria for multiple sclerosis: guidelines for research protocols.
Ann. Neurol. 1983; 13: 227-231https://doi.org/10.1002/ana.410130302
Thompson et al., 2018
Thompson A.J
Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria..
Lancet Neurol. 2018; 17: 162-173https://doi.org/10.1016/S1474-4422(17)30470-2
). Five studies reported the disease duration of the MS cases, which ranged, on average from 0.9–15.3 years (Table 2).
Table 2Clinical characteristics of the participants with MS in the included studies.
First Author, Year of Publication
Age Onset of MS (Years)
MS Disease Duration (Years)
Diagnostic Criteria
EDSS Near Time of Sample Collection
MS Disease Course
IMD/IMS Exposed Near Time of Sample Collection
Number of Participants Exposed to a Specific IMD/IMS drug
Systemic Corticosteroids
0ᶜ
Interferon-β
Glatiramer Acetate
Fingolimod
Cantarel, 2015 NA NA McDonald 3.0 or less RR 7 (100%) 5 (71%) 0 5 (71%) 0% 0 0 0 0ᵃ
Miyake, 2015 NA 8.8 ± 6.0 McDonald NA RR 20 (100%) 9 (45%) 9 (45%) 0 0% 0 0 0 5 (25%)
Chen, 2016 35.4 ± 10.4 NA McDonald < 6, n = 22;
> 6, n = 2 RR 31 (100%) 20 (65%) 14 (45%) 1 (3%) 5 (16%) 0 0 0 NA
Cree, 2016 NA 15.3 ± 8.6 NA NA RR 9 (56.3%), SP 4 (25%), PP 3 (18.8%) 5 (31%) 0 0 0 5 (31%) 0 0 NA
Tremlett, 2016 12.1 ± 4.7 0.88 ± 0.54 McDonald (range 0–4.0)
< 2.0, n=7;
2.0 to < 3.0, n=8;
>3.0, n=3 RR 18 (100%) 9 (50%)ᵇ 3 (17%) 5 (28%) 1 (6%) 0 0 0 6 (33%)ᵇ
Jangi, 2016 NA 12.8 ± 8.3 NA 1.2 (1.0 SD) RR 60 (100%) 32 (53%)ᶜ 18 (30%) 14 (23%) 0 0 0 0 0ᵃ
Cosorich, 2017 NA NA Poser (range 0–5.5)
3.0 to < 6.0, n=7 RR/NEDA 9 (47%),
RR/EDA 10 (53%) 19 (100%) 7 (37%) 9 (47%) 0 0 3 (16%) 0ᶜ
Swidsinski, 2017 NA NA NA NA RR 10 (100%) NA NA NA NA NA NA NA NA
Berer, 2017 28.0 ± 9.0 13.2 ± 9.6 McDonald NA CIS 3 (9%),
RR 22 (65%),
SP 7 (21%),
PP 2 (6%) 19 (56%)ᶜ 13 (38%) 1 (3%) 4 (12%) 0 0 1 0ᶜ
PP 2 (6%)
Cekanaviciute, 2017 NA NA NA NA RR 71 (100%) 0 (0%)ᶜ 0 0 0 0 0 0 0ᶜ
Total 118 (43%) 64 (23%) 35 (13%) 10 (4%) 5 (2%) 3 (1%) 1 11 (5%)
Unless otherwise stated, characteristics shown relate to the time of microbiota sample collection. The frequency of exposures to an immunomodulatory drug, immunosuppressant and systemic corticosteroids at the time of microbiota sample collection were typically within 2 or 3 months prior to sample collection. One study did not report treatment status. Systemic corticosteroids are not included in the number of MS cases exposed to IMD/IMS (column 7). All percentages are rounded to the nearest whole numbers. Continuous data are expressed as mean ± SD. NA, not available; MS, multiple sclerosis; RR, relapse-remitting multiple sclerosis; SP, secondary progressive multiple sclerosis; PP, primary progressive multiple sclerosis; CIS, clinically isolated syndrome; RR-EDA, evidence of disease activity in patients with relapse-remitting multiple sclerosis; NA, not available; RR-NEDA, no evidence of disease activity in patients with relapse-remitting multiple sclerosis; F, female; M, male; EDSS, Expanded Disability Status Scale. IMD, Immunomodulatory drug; IMS, immunosuppressant; ᵃExposed within 1 month; ᵇExposed within 2 months; ᶜExposed within 3 months.
Medication exposure status was reported in nine of ten studies; all focused on IMDs or immunosuppressants (IMS) used to treat MS. Overall, 118 (43%) of MS cases (n = 276) were exposed to an IMD or IMS near the time of sample collection; 64 (23%) to β‐interferon, 35 (13%) glatiramer acetate, 18 (7%) other IMDs, and 1 (<1%) IMS (azathioprine). IMD or IMS exposure was typically defined as exposed in the two or three months prior to the time of microbiota sample collection. The pediatric study included IMD naïve MS cases, explicitly defined as never exposed to an IMD (
). Of the seven studies that reported use of systemic corticosteroids, 11/229 (5%) of MS cases were exposed to systemic corticosteroids near the time of sample collection (Table 2).
3.2 Sample handling and sequencing procedures
Eight of the ten studies mentioned at least some aspects of the methods related to sample collection. A US-based group sampled participant's microbiota using culture swabs, another US-based group collected stool directly into a dry container, and the Italy-based group collected mucosal biopsies into a culturing solution containing antibiotics (
). Four studies shipped stool samples overnight (shipped with ice with the exception of one study) while four groups stored or processed the sample the same day of the collection (
). Samples not sequenced the same day of collection were stored at −70 °C or −80 °C prior to DNA extraction (
Seven studies sequenced various regions of the 16S rRNA gene using a Next-Generation Sequencing (NGS) platform (either Illumina MiSeq or Roche 454). One study used both Roche 454 and Illumina MiSeq (Table 3) (
). Two studies used a DNA microarray platform only (Affymetrix PhyloChip G3) and one used FISH to probe and profile the 16S rRNA genes (
). The 16S rRNA variable-region gene sequenced varied between studies. The method of generating 'Operational Taxonomic Units' (OTUs) also varied. OTUs are clusters of similar sequences—typically > 97%—that are assumed to represent a single taxon; for 16S rRNA, OTUs typically have genus-to-species level of taxonomic specificity. The different methods of generating OTUs among the studies that used an NGS platform include: de novo OTU clustering (four studies) and closed reference OTUs (three studies). Despite these differences, all studies that used an NGS platform clustered the 16S rRNA sequences into OTUs based on a 97% similarity threshold (Table 3).
Table 3Technical and computational methods used to process and quantify the microbiota.
First Author, Date of Publication
Microbiota Quantifying Instrument, 16S rRNA Region
Method Generating OTUs
Normalization of Sample Sequence Depth
Cantarel, 2015 DNA microarray (Affymetrix PhyloChip) The array contains representative sequences from OTUs, which were clustered at 95% similarity NA
Miyake, 2015 Roche 454, V1-V2 Individual taxa analysis: Closed reference OTUs at 97% similarity. Diversity analysis: De novo OTU clustering at 96% similarity Rarefied to 3000 sequence per sample
Chen, 2016 Illumina MiSeq,V3-V5 De novo OTU clustering at 97% similarity using IM-TORNADO Rarefied to 10,000 sequence per sample
Cree, 2016 DNA microarray (Affymetrix PhyloChip) NA NA
Tremlett, 2016 Illumina MiSeq, V4 De novo OTU clustering at 97% similarity using QIIME Rarefied to 201,546 sequence per sample
Jangi, 2016 Roche 454, V3-V5;Illumina MiSeq, V4 De novo OTU clustering at 97% similarity using Mothur NA
Cosorich, 2017 Roche 454, V3-V5 De novo OTU clustering generaed using QIIME At least 3000 sequence per sample
Swidsinski, 2017 Fluorescence in situhybridization (FISH) NA NA
Berer, 2017 Roche 454, V3–V5 Closed reference OTUs with 97% similarity using QIIME Diversity analysis: Rarefied to 10,975 sequences per sample.Individual taxa analysis: variance-stabilizing transformation
Cekanaviciute, 2017 Illumina MiSeq, V4 Closed reference OTUs with 97% similarity using QIIME Diversity analysis: Rarefied to 10,000 sequence per sampleIndividual taxa analysis: variance-stabilizing transformation
Closed-reference OTU assignment assigns query sequences to OTUs generated from an external reference database, whereas sequences in de novo OTU clustering are clustered against one another. The two common methods for normalizing read counts were rarefying and scaling. Rarefying refers to randomly discarding reads in each sample until each sample has an equal number of sequences. Scaling often includes transforming, e.g., variance stabilizing transformation. OTU, operational taxonomic units; NA, not available; V, variable region of 16S rRNA gene; IM-TORNADO, Illinois Mayo Taxon Organization from RNA Dataset Operations; Qiime, Quantitative Insights Into Microbial Ecology.
The twin cohort study also sequenced the gut metagenome (the collective genomes of all the gut microbes in a stool sample), although authors reported that none of the results reached significance, and no data was provided (
3.3 Gut microbiota diversity
Eight of ten studies assessed the gut microbiota diversity (alpha- or beta-diversity), Table 4. None of the alpha-diversity metrics, e.g., the number of different species within a sample, differed significantly between cases and controls. Out of seven studies that calculated beta-diversity (the number of microbial species that are not the same in two different environments), two studies reported a difference in a beta-diversity metric, between cases and controls (Table 4) (
). No studies reported whether potential confounders, such as IMD exposure, were relevant to the significant alpha- or beta-diversity findings.
Table 4Gut Microbiota Diversity: MS cases versus controls.
Diversity Metric
MS vs Controls (Main Analyses)
IMD-Related Subgroup Analyses
Statistical Test Used
Main Findings (R and P-values)
IMD Exposed MS vs IMD Unexposed MS
IMD Unexposed MS vs Control
Cantarel, 2015 β-diversity (weighted UniFrac) PERMANOVA P = 0.74 P = 0.66 NA
Miyake, 2015 α-diversity (richness: Choa1) Welch's test P > 0.05 NA NA
α-diversity (diversity: Shannon index) Welch's test P > 0.05 NA NA
β-diversity (weighted UniFrac) ANOSIM R = 0.24, P ≤ 0.0009 NA NA
β-diversity (unweighted UniFrac) ANOSIM R = 0.21, P ≤ 0.002 NA NA
Chen, 2016 α-diversity (richness: observed OTUs) NA P = 0.73 NA NA
α-diversity (diversity: Shannon index) NA P > 0.05 NA NA
β-diversity (Bray-Curtis) PERMANOVA P < 0.001 NA NA
Cree, 2016 NA NA NA NA NA
Tremlett, 2016 α-diversity (evenness) Mann-Whitney P > 0.2 NA P > 0.05
α-diversity (richness) Mann-Whitney P > 0.2 NA P > 0.05
α-diversity (Faith's phylogenic diversity) Mann-Whitney P > 0.2 NA P > 0.05
β-diversity (Canberra) PERMANOVA P > 0.05 P = 0.016 NA
Jangi, 2016 α-diversity (diversity: Shannon index) Wilcoxon rank-sum test P > 0.05 NA NA
β-diversity (weighted UniFrac) AMOVA P > 0.05 NA NA
β-diversity (unweighted UniFrac) AMOVA P > 0.05 NA NA
β-diversity (Bray-curtis) AMOVA P > 0.05 NA NA
Cosorich, 2017 α-diversity (richness: observed OTUs) Student's t-test P > 0.05 NA NA
Swidsinski, 2017 NA NA NA NA NA
Berer, 2017 α-diversity (Faith's phylogenetic diversity) NA P > 0.05 NA NA
β-diversity (weighted UniFrac) NA P > 0.05 NA NA
Cekanaviciute, 2017 α-diversity (richness: Choa1) NA NA NA P > 0.05
β-diversity (unweighted UniFrac) NA NA NA P > 0.05
Diversity tests that were statistically significant (P < 0.05) are in bold. Blank cells indicate a diversity test result was not reported. Not all diversity metrics were reported for every alpha-diversity measure. IMD Exposed: MS cases exposed to an immunomodulatory drug within 3 months of sample collection. IMD, Immunomodulatory drug; ANOSIM, The ANalysis Of SIMilarity; PERMANOVA, PERmutational Multivariate ANalysis Of VAriance; AMOVA, Analysis of MOlecular Variance; NA, not available.
IMD exposure and gut microbiota diversity were assessed in two US-based studies (
). Alpha-diversity did not differ between IMD exposed and unexposed MS cases in either study, although beta-diversity did differ in the pediatric MS study (Table 4) (
3.4 Taxa-level findings
Taxa-level differences between cases and controls were reported as follows: phylum level (seven studies), genus (seven studies), and species/OTU level (eight studies). In total, two genera and four species (none of which reached significance at the phylum level) similarly differed in their relative abundances between MS cases compared to controls in a consistent direction for two or more studies (Table 5). Specifically, at the genus level, lower relative abundances of Prevotella were observed in three studies and a higher relative abundance of the Archaea Methanobrevibacter was observed in two studies. At the species level, there was a higher relative abundance of Akkermansia (muciniphila) and Faecalibacterium prausnitzii, which was observed in four studies each. Also, a lower relative abundance of Bacteroides coprophilus was reported in three studies and a lower Bacteroides fragilis abundance was reported in two studies (Table 5). Different statistical tests were used to assess differences in OTU abundance, including: models based on the negative binomial distribution (four studies), t-tests (Welch or Student, three studies), Wilcoxon rank sum test (two studies) and ANOVA (one study, Table 6).
Table 5Key findings from taxa-level relative abundances: MS cases versus controls (all MS cases versus controls are initially shown, regardless of immunomodulatory drug (IMD) exposure. In addition, findings from IMD unexposed MS cases relative to controls are also depicted).
Taxa listed here are differentially significant across 2 or more studies. Red and green cells indicate a lower and higher relative abundance, respectively. Empty cells indicates that the respected study did not report the differential abundance of the respected taxa between the two groups. 'MS vs Control' refers to all of the MS participants included in the study, regardless of IMD exposure, compared to the control participants. 'IMD unexposed MS vs Control' refers to the MS cases unexposed to an IMD at the time of microbiota sample collection, compared to the controls. Genus Akkermansiais represented as Akkermansia muciniphila. The 4 studies that compared taxa-level findings between IMD unexposed MS cases vs. controls are (1st author, num. MS cases vs. controls): Tremlett, n = 9 vs. n = 17; Jangi, n = 28 vs n = 43; Berer, n = 17 vs. n = 17; Cekanaviciute, n = 71 vs. n = 71. If a study reported a higher and lower relative abundances with the same taxonomy assignment, the cell was split into two colors, as was the case for Faecalibacterium prausnitzii. If a study reported a taxonomy assignment confidence score, only scores of 95% or better were included in the table. All taxa are statistically significant (P < 0.05) after FDR adjustment. NS, not significant; IMD, immunomodulatory drug; untr, IMD untreated; tr, IMD treated; MS, multiple sclerosis; NS, not significant.
Table 6Operational taxonomic unit (OTU)-level findings: MS cases versus controls.
Differential Abundance Statistical Method
Total OTUs Generated
Number of OTUs or Species Differentialy Abundant After Multiple-Testing Adjustment
Cantarel, 2015 Wilcoxon rank sum test, with Bonferroni correction NA Total 359 OTUs
Miyake, 2015 Welch's t-test, with Benjamini-Hochberg correction. 130 OTUs Total 21 OTUs (2 OTUs enriched, 19 OTUs reduced)
Chen, 2016 Wilcoxon rank-sum test, with Benjamini-Hochberg correction NA NA
Cree, 2016 ANOVA test, with Bonferroni correction 2621 OTUs 0 OTUs (277 OTUs before adjustment)
Tremlett, 2016 Negative binomial regression, with Bonferroni correction 25,134 OTUs Total 323 OTUs (160 OTUs enriched and 163 taxa OTUs reduced MS).
Jangi, 2016 DESeq2, with Benjamini and Hochberg correction Roche 454: 4317 OTUs. 426 OTUs (after filtering). MiSeq: 10,620 OTUs. 1191 OTUs (after filtering) NA
Cosorich, 2017 t-Student test NA None statistically significant
Swidsinski, 2017 t-Student test NA NA
Berer, 2017 DESeq2, with Benjamini and Hochberg correction NA None statistically significant
Cekanaviciute (2017) DESeq2, with Benjamini and Hochberg correction 1462 OTUs (after filtering) 247 OTUs (161 reduced in MS and 86 enriched in MS)
Different statistical tests were used to assess differences in OTU abundance. DESeq2 is a differential gene expression analysis based on the negative binomial distribution. Filtering is the process in which undesired (e.g., unreliable) OTUs are removed. Often when filtering is used, OTUs present in less than 5% of samples are discarded. In some cases, it was not possible to determine if the total OTU count was filtered or not before reporting. ANOVA, Analysis of variance; NA, not available.
Three studies compared gut microbiota taxa- or OTU-level findings according to IMD exposure status via a sub-group analysis (
). When IMD unexposed MS cases were compared to controls (Table 5), a higher relative abundance of the following taxa was found Methanobrevibacter (two studies, with a combined total of 37/60 cases/controls) (
) and A. muciniphila (four studies, with 125/148 cases/controls) (
). Lower relative abundances were observed for Prevotella (two studies, with 99/114 cases/controls), (
) B. coprophilus and B. fragilis (two studies, with 80/87 cases/controls) (
). Findings for F. prausnitzii were mixed (
We reviewed the recent literature (2008–2018) on the MS gut microbiota composition. Of the ten studies comparing the gut microbiota between MS participants and controls, the majority found no major differences in the overall composition of the gut microbiota in children or adults with MS relative to controls, as judged by alpha- or beta-diversity measures. Instead, subtle differences in the gut microbial communities were generally observed. At least two or more studies reported a higher relative abundance of Akkermansia and Methanobrevibacter and a lower relative abundance of Prevotella, Bacteroides (coprophilus and fragilis) and Faecalibacterium prausnitzii for MS cases relative to controls. Studies were generally too modest in size to adequately assess potential effect modifiers (confounders) such as drug exposure relevant to diversity or taxa-level findings.
4.1 Microbiota diversity
No study observed a significant difference in alpha-diversity between MS cases and controls and the majority found no differences in beta-diversity. However, the metrics and methods used varied across studies. While this makes comparisons challenging, the use of different diversity measures was not unexpected, as no single index perfectly summarizes local diversity (
Morris et al., 2014
Morris E.K
Choosing and using diversity indices: insights for ecological applications from the German biodiversity exploratories.
Ecol. Evol. 2014; 4: 3514-3524https://doi.org/10.1002/ece3.1155
). Beta-diversity specifically quantifies the variation in the taxonomic composition between samples; two of seven studies reported a significant difference between MS cases and controls (
). However, it remains possible that findings were affected by IMD exposure; differences in beta-diversity were found in one study when IMD exposure was examined (
4.2 Individual taxa
We identified several taxa that differed in their relative abundance between MS cases and controls across two or more studies, though their role in MS are largely unknown. Methanobrevibacter, an archaeal anaerobe and methanogen, was enriched in MS cases relative to controls (
Gaci et al., 2014
Gaci N.
Borrel G.
Tottey W.
O'Toole P.W.
Brugère J.-.F.
Archaea and the human gut: new beginning of an old story.
World J. Gastroenterol. 2014; 20: 16062-16078https://doi.org/10.3748/wjg.v20.i43.16062
). Consistent with this are the higher methane breath test results observed in MS patients compared to controls (
). However, enrichment of methanogens has also been associated with constipation (
Falony et al., 2016
Falony G
Population-level analysis of gut microbiome variation.
Science. 2016; 352: 560-564https://doi.org/10.1126/science.aad3503
Vandeputte et al., 2016
Vandeputte D
Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates.
Gut. 2016; 65: 57-62https://doi.org/10.1136/gutjnl-2015-309618
), a condition which is common in MS. A. muciniphila was also enriched in MS cases relative to controls. A similar relationship was reported in Parkinson's disease (
Bedarf et al., 2017
Bedarf J.R
Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naïve Parkinson's disease patients.
Genome Med. 2017; 9: 39https://doi.org/10.1186/s13073-017-0428-y
Collado et al., 2007
Collado M.C.
Derrien M.
Isolauri E.
de Vos W.M.
Salminen S
Intestinal integrity and Akkermansia muciniphila, a mucin-degrading member of the intestinal microbiota present in infants, adults, and the elderly.
Appl. Environ. Microbiol. 2007; 73: 7767-7770https://doi.org/10.1128/AEM.01477-07
Heintz-Buschart et al., 2018
Heintz-Buschart A
The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder.
Mov. Disord. 2018; 33: 88-98https://doi.org/10.1002/mds.27105
Hill-Burns et al., 2017
Hill-Burns E.M
Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome.
Mov. Disord. 2017; 32: 739-749https://doi.org/10.1002/mds.26942
). A. muciniphila has been shown to elicit a pro-inflammatory T lymphocyte response in vitro; however, in vivo studies using mouse models of MS have so far failed to elicit a similar reponse (
). Intriguingly, A. muciniphila may be beneficial in the setting of obesity or metabolic disorders, by supporting metabolic health and improving the intestinal barrier (
Greer et al., 2016
Greer R.L
Akkermansia muciniphila mediates negative effects of IFNγ on glucose metabolism.
Plovier et al., 2017
Plovier H
A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice.
Nat. Med. 2017; 23: 107-113https://doi.org/10.1038/nm.4236
Schneeberger et al., 2015
Schneeberger M
Akkermansia muciniphila inversely correlates with the onset of inflammation, altered adipose tissue metabolism and metabolic disorders during obesity in mice.
). These context-specific observations highlight the complexity of the gut microbiome, and a need to understand the underlying biology.
The remaining taxa identified—all of which are also common commensal bacteria of the human gastrointestinal tract—were all lower in relative abundance for MS cases relative to controls. Faecalibacterium prausnitzii is known for mitigating inflammation and may be depleted in the gut of individuals with other diseases, such as inflammatory bowel disease and irritable bowel syndrome (
Liu et al., 2017
Liu H.-.N
Altered molecular signature of intestinal microbiota in irritable bowel syndrome patients compared with healthy controls: a systematic review and meta-analysis.
Dig. Liver Dis. 2017; 49: 331-337https://doi.org/10.1016/j.dld.2017.01.142
Lopez-Siles et al., 2017
Lopez-Siles M.
Duncan S.H.
Garcia-Gil L.J.
Martinez-Medina M.
F.aecalibacterium prausnitzii: from microbiology to diagnostics and prognostics..
ISME J. 2017; 11: 841-852https://doi.org/10.1038/ismej.2016.176
Prosberg et al., 2016
Prosberg M.
Bendtsen F.
Vind I.
Petersen A.M.
Gluud L.L.
The association between the gut microbiota and the inflammatory bowel disease activity: a systematic review and meta-analysis.
Scand. J. Gastroenterol. 2016; 51: 1407-1415https://doi.org/10.1080/00365521.2016.1216587
Wright et al., 2015
Wright E.K
Recent advances in characterizing the gastrointestinal microbiome in crohn's disease: a systematic review.
Inflamm. Bowel Dis. 2015; 21: 1219-1228https://doi.org/10.1097/MIB.0000000000000382
Two studies reported conflicting relative abundances, within each study, for several OTUs classified as F. prausnitzii (Table 5) (
). These conflicting OTUs may actually be two different recently discovered phylogroups within the species F. prausnitzii which have recently been identified (
). The two phylogroups share 97% 16S rRNA gene sequence similarity but have different metabolic properties. Future studies planning to assign taxonomy may find it helpful to further classify F. prausnitzii into phylogroups when possible to better resolve the mapping contradiction and serve as a better discriminating biomarker (
The effects of Prevotella may differ by species. P. histicola has been shown to suppress or prevent disease activity in a mouse model of MS (
Mangalam et al., 2017
Mangalam A
Human gut-derived commensal bacteria suppress CNS inflammatory and demyelinating disease.
Cell Rep. 2017; 20: 1269-1277https://doi.org/10.1016/j.celrep.2017.07.031
). Interestingly, the relative abundance of Prevotella was lower in relapsing-remitting MS patients with 'evidence of disease activity' relative to those with 'no evidence of disease activity' in one study (
). Prevotella species were also present in the oral microbiota of new-onset rheumatoid arthritis participants, but not in controls, suggesting a possible role in this autoimmune inflammatory condition (
Scher et al., 2012
Scher J.U
Periodontal disease and the oral microbiota in new-onset rheumatoid arthritis.
Arthritis Rheum. 2012; 64: 3083-3094https://doi.org/10.1002/art.34539
B. fragilis is thought to benefit human health by, for example, breaking down dietary fibers to produce short-chain fatty acids and anti-inflammatory polysaccharides (
Lukiw, 2016
Lukiw W.J.
Lipopolysaccharide and inflammatory signaling in Alzheimer's disease.
Ochoa-Repáraz et al., 2010
Ochoa-Repáraz J
A polysaccharide from the human commensal Bacteroides fragilis protects against CNS demyelinating disease.
Mucosal Immunol. 2010; 3: 487-495https://doi.org/10.1038/mi.2010.29
). B. fragilis is also considered a pathobiont, having an inflammatory pathogenic potential via its production of endotoxins (
). While there is limited relevant literature for Bacteroides coprophilus, this species merits further investigation for its potential role in MS.
Experimental studies allude to a pro-inflammatory MS gut microbiota. Neurological symptoms were exacerbated in animal models of MS when stool from individuals with MS was transplanted into the gut of mice with spontaneous or induced autoimmune encephalomyelitis, further supporting the association of the gut microbiota with MS (
Procaccini et al., 2015
Procaccini C.
De Rosa V.
Pucino V.
Formisano L.
Matarese G.
Animal models of multiple sclerosis.
Eur. J. Pharmacol. 2015; 759: 182-191https://doi.org/10.1016/j.ejphar.2015.03.042
4.3 Potential confounders
Of the few confounding factors assessed to date in MS, exposure to disease-modifying drugs appears to be a likely candidate. However, most studies were too modest in size to formally assess the effect of confounders, hence much remains unknown. For example, at least 20 samples per group have been suggested in order to detect differences in taxonomic relative abundances (
Weiss et al., 2017
Weiss S
Normalization and microbial differential abundance strategies depend upon data characteristics.
Microbiome. 2017; 5: 27https://doi.org/10.1186/s40168-017-0237-y
). Exposure to several medications as well as stool consistency (a reflection of gut transit time) are considered important factors in explaining microbiome variation and are related to MS itself (
He et al., 2018
He Y
Regional variation limits applications of healthy gut microbiome reference ranges and disease models.
Nat. Med. 2018; 24: 1532-1535https://doi.org/10.1038/s41591-018-0164-x
Maier et al., 2018
Maier L
Extensive impact of non-antibiotic drugs on human gut bacteria.
Nature. 2018; 555: 623-628https://doi.org/10.1038/nature25979
). A cross-sectional study assessing the differences between the gut microbiota of MS cases treated with either dimethyl fumarate (DMF; n = 33 cases) or glatiramer acetate (GA, n = 60) relative to IMD naïve cases (n = 75) was published in 2018, and although did not fulfill our inclusion criteria (due to absence of controls without MS), it is worthy of comment (
Katz Sand et al., 2019
Katz Sand I.
Disease-modifying therapies alter gut microbial composition in MS.
Neurol. Neuroimmunol. Neuroinflamm. 2019; 6: e517https://doi.org/10.1212/NXI.0000000000000517
). Authors reported that MS cases exposed to either DMF or GA had lower relative abundances of the Lachnospiraceae and Veillonellaceae families compared to IMD naïve cases (
Constipation (reflecting a slow gut transit time) is common in MS, may influence the gut microbiota composition and contribute to a pro-inflammatory local environment. Microbiota from chronically constipated individuals was demonstrated to damage the intestinal barrier and further contribute to constipation (
Cao et al., 2017
Cao H
Dysbiosis contributes to chronic constipation development via regulation of serotonin transporter in the intestine.
Sci. Rep. 2017; 7: 10322https://doi.org/10.1038/s41598-017-10835-8
). An enrichment of A. muciniphila and Methanobrevibacter spp. could be related to a slow gut transit and constipation, as shown in other conditions, including Parkinson disease (
Chia et al., 1995
Chia Y.W
Prevalence of bowel dysfunction in patients with multiple sclerosis and bladder dysfunction.
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Stocchi and Torti, 2017
Stocchi F.
Torti M.
Constipation in Parkinson's disease.
Int. Rev. Neurobiol. 2017; 134: 811-826https://doi.org/10.1016/bs.irn.2017.06.003
). Methanogens may thrive in a gut with reduced motility, and may contribute to a slow colonic transit by augmenting methane production which acts as a neuromuscular transmitter, and has been shown to slow bowel movement (
Pimentel et al., 2006
Pimentel M
Methane, a gas produced by enteric bacteria, slows intestinal transit and augments small intestinal contractile activity.
Am. J. Physiol. Gastrointest. Liver Physiol. 2006; 290: G1089-G1095https://doi.org/10.1152/ajpgi.00574.2004
). Understanding how these factors relate to MS and the gut microbiota's composition and function may clarify a possible causal role of the gut microbiota in MS. Alternatively, findings might point towards an opportunity to modify the gut microbiota to improve outcomes in MS. Future studies could assess stool consistency using proxy markers, such as the Bristol Stool Scale (
Koh et al., 2010
Koh H.
Lee M.J.
Kim M.J.
Shin J.I.
Chung K.S.
Simple diagnostic approach to childhood fecal retention using the leech score and bristol stool form scale in medical practice.
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). Polypharmacy is common in MS and ideally, all recent drug exposure should be captured (
). The relationship between the IMDs used to treat MS and the gut microbiota is particularly intriguing and could provide additional mechanistic insights. Sufficiently powered, prospective longitudinal studies are needed to better understand the complex and likely dynamic relationship between MS, the gut microbiome, comorbidities, medication exposure, diet, and other lifestyle factors.
4.4 Heterogeneity of study design
Heterogeneity in the microbiota composition across studies may relate to differences in the sourcing of cases and controls and their characteristics, including: the broad age range of participants (from children to adults); (
) MS course (2 studies included participants with primary or secondary progressive MS (
)) and disease duration (which ranged from a few months to decades); host geographic location (although all studies were from largely westernized populations) and ethnicity (
Deschasaux et al., 2018
Deschasaux M
Depicting the composition of gut microbiota in a population with varied ethnic origins but shared geography.
Nat. Med. 2018; 24: 1526-1531https://doi.org/10.1038/s41591-018-0160-1
Gaulke and Sharpton, 2018
Gaulke C.A.
Sharpton T.J.
The influence of ethnicity and geography on human gut microbiome composition.
McDonald et al., 2018
McDonald D
American gut: an open platform for citizen science microbiome research.
mSystems. 2018; 3https://doi.org/10.1128/mSystems.00031-18
). The degree to which these differences contribute to variation in the gut microbiota are complex, context specific and is not fully understood (
). For example, although it is possible that individuals with a progressive disease course might differ in terms of their gut microbiota composition from those with a relapsing disease course, insufficient data and cases were available. Further, teasing apart the effects of age, disease duration, accrual of comorbidities and medication exposures from the underlying disease course would likely require access to a sizable cohort of individuals with progressive and relapsing MS.
Technical methods for quantifying and analyzing the gut microbiota also differed, including the choice of: quantification instrument, 16S rRNA sequences regions(s), and gastrointestinal tract site sampled. Computational methods also differed, including: the bioinformatics pipeline used to generate OTUs, OTU abundance normalization, and statistical tests employed. While the method of generating OTUs varied, all studies using an NGS platform generated OTUs at the same taxonomic resolution by clustering the 16S rRNA sequences based on a 97% similarity threshold.
4.5 Strengths and limitations
The strengths of this review include its systematic, reproducible approach, and pre-registered protocol. Our systematic review also provides insights into the heterogeneity in microbiome study design including an overview of the differences in the computational pipelines. However, all studies included were relatively modest in size, with the total number of available data pertaining to 286 MS cases and 296 controls from a limited number of regions in the world. It remains possible that associations have been missed, particularly with the lower abundant taxa. For simplicity, we only reported findings on taxa that were similarly observed across two or more studies. Further, all studies were considered together, including one which sampled duodenal mucosal tissue. It remains possible that different physiological niches in the gastrointestinal tract will harbor distinct microbiota communities of relevance in MS. Interrogation of the gut microbiota in MS was primarily conducted using 16S rRNA sequencing which is typically unable to assign taxonomy below species level and is incomplete at low taxonomic ranks. It was not possible to match and compare individual OTUs identified across studies. We found no published study investigating the virome or mycobiome (fungi microbiome) in MS.
4.6 Concluding remarks
To our knowledge, this article is the first to systematically review the scientific literature investigation the link between the gut microbiome and MS. Despite the modest cohort sizes, diversity in the geographical location of participants and sample processing and bioinformatics pipelines used, consistent patterns are emerging: several taxa were similarly identified as being over or underrepresented in MS versus controls. A better understanding of a possible causal role of the microbiota in either facilitating the onset of MS, or outcomes in MS, including perpetuating comorbidities will facilitate our ability to harness the microbiome to affect positive change in MS.
5. Addendum
5.1 Summary of articles published between June 20th 2018 and August 24th, 2019
The systematic literature search was updated on August 24th, 2019 by one reviewer (AM). Of 122 new articles identified, three fulfilled the inclusion criteria, one from the US, one from Canada, and one from China (
Multiple sclerosis-associated changes in the composition and immune functions of spore-forming bacteria.
Forbes et al., 2018
Forbes J.D
A comparative study of the gut microbiota in immune-mediated inflammatory diseases-does a common dysbiosis exist.
Microbiome. 2018; 6: 221https://doi.org/10.1186/s40168-018-0603-4
Zeng Q
Gut dysbiosis and lack of short chain fatty acids in a Chinese cohort of patients with multiple sclerosis.
Neurochem. Int. 2019; 129104468https://doi.org/10.1016/j.neuint.2019.104468
Briefly, the US-based study included stool samples from 25 RRMS cases, all unexposed to IMDs or corticosteroids 3 months prior to stool collection (80% were women, mean age = 44.0 years), and 24 controls (12.5% women, mean age = 49.3 years). All bacteria as well as the spore-forming bacterial fractions alone were sequenced at the 16S rRNA V4 region, using the Illumina NextSeq platform and clustered into closed-reference OTUs (97% sequence similarity). No differences were observed in alpha-diversity (Chao1) or beta-diversity (unweighted UniFrac) between cases and controls for either the spore-forming bacteria or total bacteria. Differences between MS cases and controls in the relative abundance of OTUs of spore-forming bacteria fractions including: lower Ruminococcus gnavus, Ruminococcus bromii, Veillonella dispar, and a higher relative abundance of Propionibacterium acnes, Staphylococcus epidermidis, Clostridium perfringens, and Clostridium citroniae were reported (all P < 0.05). Taxa-level differences between cases and controls among total bacteria and the effects of possible confounders were not reported (
The Canada-based study included stool samples from 19 MS cases (average age = 47.3 years; 14 were women; MS course was not reported) and 23 healthy controls (average age = 32.4 years; 12 were women). In addition, the authors included 20 Crohn's disease cases, 19 ulcerative colitis cases, and 21 rheumatoid arthritis cases (not reported here). DNA extracts were sequenced at the 16S rRNA V4 region using the Illumina MiSeq platform, clustered into de novo OTUs (97% sequence similarity). Because the dataset had an unusually low abundance of Gram-negative bacteria, the differential taxa abundance testing included only OTUs from Gram-positives phyla (i.e., OTUs within the phyla Firmicutes, Actinobacteria, and Tenericutes). The author's main goal was to compare across all the immune-mediated diseases relative to controls. Here, we report only the comparisons between the MS cases and controls. Alpha-diversity (i.e., Chao1, ACE, Shannon index, and Simpson diversity index, based on all phyla) did not differ between MS cases and controls. Beta-diversity was not directly compared between MS cases and controls. Significant differences between MS cases and healthy controls in the relative abundance of gram-positive bacteria at the genera level included: Lower Butyricicoccus, Dialister, Faecalibacterium (consistent with a previous finding (
)), Fusicatenibacter, Gemmiger, Lachnospira, Sporobacter, and Subdoligranulum in MS cases relative to controls and higher Actinomyces, Eggerthella, Anaerofustis, Clostridium group III, Clostridium group XlVa, Clostridium sensu stricto, Faecalicoccus, Streptococcus and Turicibacter in MS cases relative to healthy controls (P < 0.05, Kruskal–Wallis test and Dunn's post hoc tests for multiple comparisons, with FDR correction) (
The third study included stool samples from 34 RRMS cases (21 unexposed and 13 exposed to an immunosuppressant [e.g., azathioprine, methotrexate, or mycophenolate]) and 34 healthy controls from China (in addition to 34 individuals with neuromyelitis optica spectrum disorder). DNA extracts were sequenced at the 16S rRNA V3-V4 region using the Illumina MiSeq platform and clustered into de novo OTUs (97% sequence similarity). Alpha-diversity (i.e., Chao1, Shannon index, and Simpson diversity index) did not differ between all MS cases and healthy controls. Although beta-diversity did differ for both exposed MS cases and unexposed MS cases compared to healthy controls, (using a non-phylogenetic gain distance metric, P < 0.01 and P < 0.05, respectively; Mann−Whitney U test), the authors used an unconventional approach, by comparing distance values computed from the first principal coordinate of a principal coordinate analysis. The relative abundance of Prevotella was lower for the MS cases compared to controls, consistent with findings from prior studies in MS (exposed MS cases vs. controls, P < 0.05 and unexposed MS cases vs. controls, P < 0.0001; Mann−Whitney U test). As in the prior Canadian study (
), the relative abundance of Streptococcus was higher for the MS cases compared to controls, (exposed MS cases vs. controls, P < 0.001 and unexposed MS cases vs. controls, P < 0.0001) (
5.2 Summary comments
The new articles support the conclusion that there is no major differences in the overall composition of the gut microbiota in individuals with MS relative to controls, as assessed using alpha- or beta-diversity measures. Two studies consistently identified two taxa that differed in their relative abundance between MS cases and controls: lower Faecalibacterium and higher Streptococcus in MS cases relative to controls (
). The former observation concurs with a finding from a study in our systematic review, the latter represents a 'new' observation.
AM and HT contributed to conception and design of the study, acquisition, analysis and interpretation of data, and drafted the first version of the manuscript, tables and figures. JF, FZ, CB, GV, MG, and EW contributed to acquisition and interpretation of data and provided critical review of the manuscript.
Potential conflict of interest
HT is the Canada Research Chair for Neuroepidemiology and Multiple Sclerosis. Current research support received from the National Multiple Sclerosis Society, the Canadian Institutes of Health Research, the Multiple Sclerosis Society of Canada and the Multiple Sclerosis Scientific Research Foundation. In addition, in the last five years, has received research support from the Multiple Sclerosis Society of Canada (Don Paty Career Development Award); the Michael Smith Foundation for Health Research (Scholar Award) and the UK MS Trust; speaker honoraria and/or travel expenses to attend CME conferences from the Consortium of MS Centres (2013, 2018), the National MS Society (2014, 2016, 2018), ECTRIMS (2013, 2014, 2015, 2016, 2017, 2018, 2019), Biogen Idec (2014), American Academy of Neurology (2013, 2014, 2015, 2016, 2019). All speaker honoraria are either declined or donated to an MS charity or to an unrestricted grant for use by HT's research group.
AM, FZ and JF were funded through research grants held by HT. AM received funding from the Multiple Sclerosis Society of Canada.
CB, GV, MG, and EW have no conflict of interest to report.
The study authors received funding from The Multiple Sclerosis Scientific and Research Foundation, EGID: 2636 (PI: Tremlett). Ali Mirza was supported by an endMS Doctoral Studentship Award from the Multiple Sclerosis Society of Canada, EGID: 3246.
Appendix 1. Information retrieved and extracted from each included study
1. Publication information: name of author(s) and year of publication,
2. Study information: study design, geographic location of recruits (e.g., National Center of Neurology and Psychiatry Hospital, Tokyo, Japan), MS diagnosis criteria (e.g., McDonald criteria), and eligibility criteria, and enrolment period.
3. Case-control demographics and characteristics close to the time of microbiota sample collection: age, sex, race/ethnicity, MS disease course (e.g., relapsing-remitting onset MS or primary progressive), case or control status, MS disease duration, disability level (e.g., the Expanded Disability Status Scale (EDSS) score), lifestyle factors, as available (e.g., BMI, diet-related metrics). Medication use, including drugs used to treat MS, e.g., the immunomodulatory drug (IMDs), captured as therapeutic class or generic name (e.g., interferon-beta, glatiramer acetate) and IMD treatment status [treated/untreated/naïve (as defined by the study authors)]. Systemic corticosteroid around the time of sample collection (yes, no). Other medication use, including antibiotics.
4. Microbiota sampling and quantification information: body site sampled (e.g., stool, mucosa biopsy of small intestines, etc.), number of samples collected, number of samples excluded, DNA isolation kit, microbiota quantification instrument, sequence molecule/ region, primer sequence, method of generating OTUs ('Operational Taxonomic Units'; species-like taxonomy), and OTU statistical normalization method.
5. Microbiota analysis results: Total OTUs, differential abundance statistical method, taxa-level [phylum, genus, species (or individual OTUs)] differences between cases and control, number OTUs differentially abundant before and after multiple-testing adjustment, potential confounding factors considered in the study design and/or adjusted statistically in the analyses, diversity metric(s) considered, diversity comparisons between groups, e.g., MS vs. controls, and when available, untreated MS vs controls and treated MS vs untreated MS.
Accepted: September 30, 2019
Received in revised form: September 6, 2019
Received: July 10, 2019
DOI: https://doi.org/10.1016/j.msard.2019.101427
© 2019 Elsevier B.V. All rights reserved.

redpajama_set_name: RedPajamaCommonCrawl


text:
PlayStation 3 Steam Xbox 360
Star Trek The Video Game
Bandai NAMCO, Digital Extremes
Digital Release: PlayStation 3, Steam
April 23, 2013 (EU, US)
July 23, 2013 (AU, EU, US)
Delisting: April 02, 2016 - Steam
April 2016 - PlayStation 3, Xbox 360
Developer: Digital Extremes
Publisher: Bandai NAMCO
Available On: Retail:
Links: SteamDB page
Xbox.com page [Archive]
Star Trek The Video Game (2009) was delisted from Steam on April 2nd, 2016. It was likely delisted around this same time on PlayStation 3 and Xbox 360. The game was most likely delisted due to expired licensing from Paramount Pictures. The game remains available on physical media.
The 2009 Star Trek film cast will be contributing their voices for the game, including Chris Pine as Kirk and Zachary Quinto as Spock.
Set after events of the Star Trek (2009) reboot, continue the sweeping journey through the new universe with a completely original story
Uncover new areas on the Enterprise and other ships, explore never-before-seen sectors throughout the galaxy including exotic planets, treacherous jungles, remote space stations and other locales
Built from the ground up as a co-op experience, Star Trek packs two vastly different gameplay styles and unique character abilities into one game. The result – the most fully realized and varied co-op experience of this console generation
Play for the first time as two of the most well-known characters in science fiction, as only this new Star Trek game could allow. With fate of the galaxy on the line, players must rely on each other to create a kick-ass team
Thanks to Valery for submitting this game to the site


text:
Don Quixote, Ballet Philippines' Quintessential 48th Season ender Ft. American Baseball Player Joseph Gatti
By Palawanderer - February 06, 2018
Ballet Philippines, the first resident company of Cultural Center of the Philippines, founded in 1969 by National Artist for Dance Alice Reyes and Eddie Elejar, is the preeminent classical and contemporary dance company in the country widely recognized today as a cornerstone of contemporary Filipino identity. Ballet Philippines presents this classic lavish and flourish tell tale of Miguel Cervantes following the lofty adventure of Don Quixote in Barcelona where he meets an innkeeper daughter, Kitri, whom he thought his ladylove Dulcinea.
Historically speaking, DON QUIXOTE was first staged in 1973 and 2011 was its last performance. This timeless splendor celebrating its crystal year in Ballet Philippines' stage, is a perfect show for first timer because of romantic-comedy theme, known for dizzying turns, signature leaps and death-defying lifts.
Joseph Gatti.
For nearly three decades, spanning four continents, Adam Sage, current Associate Artistic Director and Ballet Master of Ballet Philippines is this year's "regisseur" Not only that he has mentored, coached and choreographed 50 works to his credentials, he performed as Don Quixote in 1981 production of Ballet Philippines. Appearing as International Guest Artist in the titular tole is 23 year old Joseph Gatti, born in Warwick (New York) and raised in Orlando (Florida).
Being the first American male dancer to win gold at the New York International Ballet Competition, a former Principal Dancer of Cincinnati Ballet and Corella Ballet and First Soloist of Boston Ballet, he was amazed how Filipino dancers supports each other during rehearsals. Sportsman Gatti who loved playing baseball, was mentored and influenced by Sage, arrived in Manila January 31, Wednesday is enjoying the Philippines for the first time. Playing opposite to Gatti as Kitri, is returning Resident Guest Artist for the fourth times this season is the beautiful Candice Adea.
The first Filipina to win First Prize at the 7th Helsinki International Ballet and Silver Medalist at the 2010 USA International Ballet Competition, quoted by National Artist for Dance Alice Reyes as a lucky girl to share a stage with Gatti. Adea is reprising her role, she played Kitri in 2011. Other Guest Artists to appear onstage are Jojo Mamangun as Don Quixote and Ronelson Yadao as Espada. Resident artists Jemima Reyes and Monica Gana as Kitri alternates, Denise Parungao and Katrene San Miguel as Mercedes alternates and Victor Maguad and Ian Ocampo as Basilio alternates.
Text and Photos by Gilbert Kim Sancha.
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text:
Gustavo A. Martínez, David Sotomayor-Ramírez, José A. Castro, APPLICATION OF THE CARIBBEAN P INDEX TO SOILS RECEIVING ORGANIC AMENDMENTS , The Journal of Agriculture of the University of Puerto Rico: Vol. 86 No. 3-4 (2002): Vol. 86, No. 3-4, July - October 2002
David Sotomayor-Ramírez, John Ramírez-Ávila, Edwin Más, Gustavo A. Martínez, Erosion and nutrient loss reduction with an alternative planting method for coffee (Coffea arabica) , The Journal of Agriculture of the University of Puerto Rico: Vol. 92 No. 3-4 (2008): Vol. 92, No. 3-4, July - October 2008
David Sotomayor-Ramírez, Yusmary Espinoza, Soil aggregation and organic carbon fractions in the Rio Grande de Arecibo watershed , The Journal of Agriculture of the University of Puerto Rico: Vol. 94 No. 1-2 (2010): Vol. 94, No. 1-2, January - April 2010
Thomas R. Sinclair, Yoana C. Newman, María de L. Lugo, Elide Valencia, Ann R. Blount, Potential for year-round forage production in Puerto Rico and St. Croix , The Journal of Agriculture of the University of Puerto Rico: Vol. 89 No. 3-4 (2005): Vol. 89, No. 3-4 July - October 2005
Amanda Acero-Camelo, Elide Valencia, Abner A. Rodríguez, Paul F. Randel, Calliandra calothyrsus supplementation effects on weight gain and efficacy of control of gastrointestinal nematodes in weanling goats , The Journal of Agriculture of the University of Puerto Rico: Vol. 93 No. 1-2 (2009): Vol. 93, No. 1-2, January - April 2009
Elide Valencia, Abner A. Rodríguez-Carias, SILAGE YIELD, FERMENTATION CHARACTERISTICS AND AEROBIC STABILITY OF TWO CORN HYBRIDS , The Journal of Agriculture of the University of Puerto Rico: Vol. 92 No. 1-2 (2008): Vol. 92, No. 1-2, January - April 2008
Abner A. Rodríguez-Carías, José Israel Suárez-Rodríguez, Jonathan Collazo, John Fernández-Van Cleve, Feeding systems and productive and physiological parameters of lambs raised under heat stress , The Journal of Agriculture of the University of Puerto Rico: Vol. 104 No. 2 (2020): Vol. 104 No. 2, 2020
José Paulino-Paulino, Eric W. Harmsen, David Sotomayor-Ramírez, Luis E. Rivera, Nitrate leaching under different levels of irrigation for three turfgrasses in southern Puerto Rico , The Journal of Agriculture of the University of Puerto Rico: Vol. 92 No. 3-4 (2008): Vol. 92, No. 3-4, July - October 2008
David Sotomayor-Ramírez, Ancizar Lugo-Ospina, Rafael Ramos-Santana, Vegetation influence on soil quality in a highly degraded tropical soil , The Journal of Agriculture of the University of Puerto Rico: Vol. 88 No. 1-2 (2004): Vol. 88, No. 1-2 January - April 2004
David Sotomayor-Ramírez, Gustavo A. Martínez, John Ramírez-Ávila, Edwin Más, Effectiveness of grass filter strips for runoff nutrient and sediment reduction in dairy sludge-amended pastures , The Journal of Agriculture of the University of Puerto Rico: Vol. 92 No. 1-2 (2008): Vol. 92, No. 1-2, January - April 2008
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Skin-care refrigerators are extremely popular within the beauty community.
On Friday, YouTuber Safiya Nygaard told her Twitter followers that she'd purchased a skin-care fridge.
The tweet started an online debate about whether or not it's necessary to purchase a separate fridge solely for beauty products.
The practice has existed for years, though more brands have begun selling beauty fridges within the last year.
According to some beauty gurus, skin-care products can work more effectively when kept cold. But rather than storing serums and face masks next to produce, some people prefer to keep their beauty regimens inside "skin-care fridges."
Beauty and style YouTuber Safiya Nygaard is one of them. On Friday, Nygaard took to Twitter to share that she'd purchased a designated beauty fridge for her skin-care products.
While many fans loved the YouTuber's dedication to her skin-care routine, others were confused as to what she meant by her tweet.
Many people were shocked to learn that skin-care fridges exist.
Others felt that Nygaard made a smart decision by purchasing the fridge, and explained why they loved their own.
Other Twitter users argued that buying an extra fridge solely for beauty products might be unnecessary.
Technically, skin-care fridges aren't a new concept. As one Twitter user stated, many people have been storing their beauty products in cold climates for decades.
However, the practice has become extremely popular over the last year. Currently, retailers like Urban Outfitters, Macy's, and Nordstrom all offer miniature refrigerators designed specifically to store beauty products.
As for whether or not skin-care fridges actually work, that depends on who you ask. While many beauty enthusiasts swear by the practice, many dermatologists say that there's actually no benefit to cooling your moisturizers and facial oils.
In a 2018 interview with Shape, Dr. Howard Sobel said keeping skin-care products cold "is not really necessary" because there is "no difference in the actual properties and benefits."
However, some professionals say that de-puffing creams and gels can work better when chilled. In a 2017 interview with Allure, Elizabeth Tanzi, the founder and director of Capital Laser & Skin Care, said cold temperatures can help eye products "to vasoconstrict," or constrict blood vessels, "and may help with puffiness."
Dr. Joshua Zeichner also told Allure that refrigerating products can "help extend their shelf life," as most beauty products are not intended to be kept at high room temperatures.
Of course, the one thing that everyone can agree on is that regular refrigerators work just fine.
Safiya Nygaard did not immediately respond to INSIDER's request for comment.


Try out the best healthy flourless and gluten free recipes, suitable also for people suffering from celiac disease. You will find here many tasty and healthy inspirations for savory breakfast, lunch, dinner as well as amazing flourless desserts. Recipes are easy to prepare and the whole family will surely enjoy them. In many recipes, flour can be easily replaced e.g. by poppy seeds, ground nuts, legumes, cocoa, protein powder or other interesting ingredients.
Healthy and fit gluten free recipes are here not only for people with celiac disease but also for everyone who would like to exclude flour from their diet because of other reasons. If you don't suffer from celiac disease, you can still eat the "usual" flour but it's good to include into your dietary plan other grains or gluten free flour made of buckwheat, coconut or almonds that is much more nutritious.
Except for main dishes, I will also show you healthy gluten-free breakfasts, soups, cakes and desserts. Besides that, you will find here easy gluten free recipes for snacks that are suitable before or after lunch or anytime throughout the day. Gluten-free diet doesn't have to be unpleasant. There are many various and healthy flourless meals that are tasty and made quickly and easily. Join me and enjoy the best flourless and gluten-free fit recipes too.


The Gold Rush Snowmobile Trail is one step closer to completion in B.C.'s Cariboo region, with the opening of a new bridge over Moffat Creek near Horsefly.
Construction of the $160,000 bridge and adjoining trail was funded by the ministry in partnership with the BC Snowmobile Federation, National Trails Coalition, Northern Development Initiative Trust, Cariboo-Chilcotin Beetle Action Coalition, New Pathways to Gold Society, 100 Mile Snowmobile Club, Canim Lake Truckers Association, Cariboo Regional District and District of 100 Mile House.
The Moffat Creek bridge, which opened for use in December 2015, is another important link on the Gold Rush Snowmobile Trail. Earlier this winter, the Blair Street bridge opened in Wells. Also this winter, new directional signs with trail names and maps were installed on the Green Lake Snowmobile Trail system east of 70 Mile House, allowing for safer public use.
Riders should remember to check conditions before heading out onto the trail: Be informed before use, be prepared for all types of weather and carry appropriate equipment to ensure a safe, fun riding experience. The current Gold Rush Snowmobile Trail route avoids avalanche terrain. However, conditions, maintenance and signage will vary depending on proximity to local communities and snowmobile clubs.
Snowmobiling plays a vital economic and recreational role in the Cariboo region, and promotes a safe, active lifestyle by providing groomed and well-maintained trails.
Currently, the Gold Rush Snowmobile Trail stretches approximately 259 kilometres from 70 Mile House to Horsefly.
The vision for the trail is to cover about 460 kilometres from Clinton to Wells/Barkerville, with a target completion date of 2018.
The Gold Rush Snowmobile Trail is an initiative of the British Columbia Snowmobile Federation on behalf of local Cariboo clubs, including the Green Lake Snowmobile Club, 100 Mile House Snowmobile Club, Williams Lake Powder Kings Snowmobile Club, Quesnel Snowmobile Club and Wells Snowmobile Club.
The trail is maintained by the local snowmobile clubs in cooperation with Recreation Sites and Trails BC.


I use the word "normation" to describe the process whereby one religious tradition asserts its superiority over others, particularly laying claim to being "the" orthodox tradition, while others are considered to be lesser, defective, or downright errant.
What lessons about normation might we be able to learn from the most recent declaration by the Vatican and the reinstatement of the Catholic Latin Mass?
1. What is written as normative by one religious group does not reflect the religious reality. In this case, the written declaration of the Catholic Church uses language of superiority, describing other forms of Christianity in deviant and "lesser" terms. But the fact is that other forms of Christianity do not consider themselves to be deviant or lesser, nor do all Catholics themselves think along these lines. Because one group describes another group as thus-and-so does not mean that the other group is thus-and-so.
2. Normative posturing in religion is successful because of its appeals to authority, appeals which are meaningful to certain parties, but do not reflect the fact that other parties have their own equally successful appeals. In this case, the appeals from the Vatican come in two ways: Roman successorship of the Pope (Petrine authority), and apostolic succession (our tradition is a continuation of the tradition that has been handed down from the twelve apostles).
3. Normative declarations result in confusion and offense. Need I say more?
4. There is always response to normative posturing (although in the ancient world this may not always be captured in the literature). Typical responses include outrage, anger, insult, defensiveness and questions like why would you say this about me? My religious views are just as good as yours if not better.
5. The group that is norming will then consolidate its position, sometimes adjusting its previous position, sometimes intensifying it.
"Current Events", "Gnosticism", "Historical Hermeneutics"


text:
HomeWEATHER UPDATESMeT Issued Fresh Weather Advisory, Two More Western Disturbances Reaching The Valley
MeT Issued Fresh Weather Advisory, Two More Western Disturbances Reaching The Valley
According to the new weather calendar of the Meteorological Department, two westerly winds are affecting Jammu and Kashmir
Dry and partly cloudy weather till January 18, snow and rain forecast from January 22 to 24
Srinagar, Jan 17: The Meteorological Department, while issuing a new weather calendar, said that the fresh westerly winds are affecting Jammu and Kashmir from January 22, due to which the weather conditions will change.
According to CNI, due to the dry weather conditions in Kashmir Valley and Jammu, where the cold wave is increasing day by day, the Meteorological Department has issued a weather calendar and has predicted more rains and snowfall till January 22 and 24.
Mukhtar Ahmad, the director of Meteorological Department, said that the fresh western winds will last from January 22 to 24, during which there is a possibility of rains and snowfall. He said that the weather will remain dry from January 18 to 22.
He further said that during this period, there will be chances of light to moderate snowfall in the plains and moderate to heavy snowfall in the upper reaches of the Kashmir valley. He also said that people should avoid going to the slopes and avalanche-prone areas during this period.
It should be noted that the weather conditions have improved after the snowfall in the past few days and due to good sunshine throughout the day. The cold wave has increased. He said that the weather is likely to remain mainly dry and partly cloudy till January 18.
While from January 19 to 21, the weather will be cloudy with light rain and snowfall. He added that from 22 to 24 Snowfall and rains are likely till January. (CNI) reports
NEWS WEATHER UPDATES


I remember being young and writing out my Christmas wish list, filled with toys or games, and other things I definitely didn't need, but desperately wanted. And while it's still undeniably fun to open up mysterious, beautifully wrapped packages from loved ones, gift giving means something totally different to me as a legitimate grown-up. For the family and friends on my list this year, more thought goes into each gift than simply what's at the top of a magazine's must-have list. I'm finding things with a personal connection to each individual to show not only my appreciation for who they are in my life, but to try and make their life just a teeny bit better.
One gift I'm super excited about this year is HP's Spectre x360 laptop, which I'll be giving to my little sister, Elaine. Since she's six years my junior and we were latchkey kids (raised by a single, working mother) I was often responsible for taking care of her, and I always kind of resented that. But when Elaine was 18, something happened that would change our lives forever. She got pregnant. And it didn't play out like it does in rom-coms. Our whole family was devastated and depressed. In fact, my sister was very close to giving her baby up for adoption, but ultimately my mom convinced Elaine to keep her — and now none of us could ever imagine our worlds without my niece Kaley.
Kaley forced our family to come together, since we all had to help raise her. She also made Elaine grow up fast — for better or worse. She never finished high school, and instead went straight to work. And now that Kaley is older, Elaine is finally able to focus more on who she is and what she wants to do with her life. I'm giving her this awesome Spectre x360 laptop and a workspace in the hopes that it will help her discover and pursue her interest. I'm giving it to her with the encouragement to get her GED, look into college, and figure out what she wants to do with her life. And because the laptop is so easy to use, lightweight, and portable, I think it will make both her and Kaley's lives a little easier. In case you forgot what my mom's home looked like before, here's the before.
Thinking about more thoughtful gift giving is actually what HP's #ReinventGiving promotion is all about (in fact, watch this sentimental ad that explains the campaign — and yes, I cried). And now, you have the opportunity to win a Spectre x360 laptop to give someone important as well — and you don't have to purchase a thing to enter. Actually, all you have to do to enter is comment #ReinventGivingSweepstakes on my Instagram post [here] and you're in the running to win one of six laptops that HP is awarding. The contest ends December 14th and you can read all the pertinent details here.


text:
Sarmatia lysippusalis är en fjärilsart som beskrevs av Walker 1858. Sarmatia lysippusalis ingår i släktet Sarmatia och familjen nattflyn. Inga underarter finns listade.

Källor

Nattflyn
lysippusalis

redpajama_set_name: RedPajamaWikipedia


DAU file extension | How can I open or convert this file?
Many people share .dau files without attaching instructions on how to use it. Yet it isn't evident for everyone which program a .dau file can be edited, converted or printed with. On this page, we try to provide assistance for handling .dau files.
The DAU data files are related to SPSS. DAU file is a SPSS Overflow Data. SPSS is a comprehensive statistical package that combines data manipulation and statistical analysis. The .dau file holds responses to questions that need to be transcribed, coded, or checked.
Naturally, other applications may also use the .dau file extension. Even harmful programs can create .dau files. Be especially cautious with .dau files coming from an unknown source!
Can't open a .dau file?
The .dau file extension is often given incorrectly!
If you have useful information about the .dau file format, then write to us!


text:
Meet Hideout, the 'Rookies' Reaching for the Stars
Monday, November 17, 2014 at 5:00 AM
Think of bicoastal indie rock outfit Hideout as the Intergalactic Postal Service. Like Ben Gibbard and Jimmy Tamborello before them, Gabe Rodriguez and Cory Stier pieced together their debut album in separate states. But unlike the earthbound romances of the Postal Service, Hideout relish in stories about alien abductions, and worship at the altars of Ziggy Stardust and Explosions in the Sky.
Brought together in their youth and through a slew of nascent musical projects around San Diego, Rodriguez and Stier charged forth with Hideout's Rookie (Thrill Me) while both were on tour as backing instrumentalists for Cults.
As Rodriguez huffs and puffs his way down a chilly Canal Street near his Chinatown, New York apartment, he says: "Being in a band, it's like having another girlfriend or something. You're always on tour; you're practicing, arguing about what you should do. Where this is a very— our relationship is great because when we see each other, we're usually happy just to hang out, and then getting to create something we're both passionate about. So it works well."
Rodriguez (guitar and vocals) notes that the Internet has made such an exchange of ideas much easier and less pressurized. He and Stier (drums) work on material when they feel like it, and that easygoing attitude has birthed about three albums' worth of songs. The 11 tracks on Rookie jut between M. Ward sunshine ("It Ends") and cascading epics ("Stubborn Child"). Every tune has Hideout's stamp of exploration and intrigue.
This zeal for the revelatory is best embodied in "New Music," a crisp ditty – written while on the road with Cults – that would make Conor Oberst envious.
"Sometimes when you go on tour, you get in the routine of just playing the same thing over and over again. It becomes more of a muscle memory versus an expression," Rodriguez says. "It was just the mid-tour blues. I think a lot of people get it. … I wanted that feeling of new music, something that I was excited about that I hadn't had in a little bit."
And it had been awhile since the musical community heard a good song about beings from other planets. (Katy Perry's "E.T." notwithstanding.) The trilogy of "Skylights," "Battle Lights" and "Stronger" tells of a boy's abduction, extraterrestrial proselytizing and wrecking of his family unit. Rodriguez praises the sci-fi masters for inspiring him and having the intuition to see beyond our galaxy.
"I have, since I was a little kid, fully loved sci-fi books, even fantasy. All of it!" he exclaims. "Isaac Asimov and Jules Verne and all these people have predicted things that people at the time were saying, oh, that's crazy! And they actually happened. So, I don't know. I love that." And yes, for the record, Rodriguez believes in aliens.
He's also a big believer in creating. He speaks with an awestruck tone when talking about his favorite hideout – his apartment, and specifically his desk – where he hunkers down to make art. In addition to being a musician, he dabbles in woodworking and has ambitions to pick up welding. It isn't farfetched— Rodriguez's dexterity when it comes to song structure could easily translate to the manipulation of metals. Think of him as a pop alchemist.
Or a pyromaniac.
"I think wearing the big mask and having the blowtorch sounds great," he says with a laugh.
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text:
'BNP trying to make polls controversial to foreigners'
Published: January 31, 2019 17:28:56 | Updated: February 01, 2019 17:53:59
Road Transport and Bridges Minister Obaidul Quader on Thursday said BNP is now lobbying with European Union (EU) and the United States for making the recently held general election controversial, after being rejected by the countrymen.
"The democratic world was not confused by BNP's propaganda. So, the world community recognized the new government," he told the reporters after attending a meeting of Dhaka Transport Coordination Authority (DTCA) at Nagar Bhaban in the city.
Quader, also the general secretary of Awami League, said the foreigners have no allegation against the polls held on December 30 as well as the countrymen have no reaction to this end.
Terming the BNP's demand of holding fresh polls as ridicules, the minister said they (BNP) need to go to parliament for the survival of their existence. "I hope that they will join parliament shunning negative politics and will make constructive criticisms," he added.
The ruling party leader said the behaviour of the leaders of Jatiya Oikyafront has proved that the unity will not be exist for long though they are saying that their unity remains intact, reports BSS.
Urging the elected lawmakers of BNP and Gano Forum to join parliament, Quader said the Gano Forum lawmakers are in pressure to join in the House. They will take oath after getting pressure from their voters, he added.
He said the upcoming local government elections will be held in a free, fair and transparent manner. He urged BNP to take part in the polls.
The meeting decided not to allow holding any rally in the capital except on holidays. Besides, the minister asked the authority concerned to take necessary steps to stop horning by in front of schools and hospitals.


text:
A Nyíregyházi repülőtér Magyarország jelentős repülőtereinek az egyike. Nem nemzetközi, de határnyitási joggal rendelkező repülőtér. Egy aszfaltozott és egy füves pályája van. A helyszínen van lehetőség tandemugrásra, motoros és vitorlázórepülésre, sárkányrepülőzésre. A Tréner Kft. üzemelteti a repülőteret. Nagy repülőgépek landolására nem alkalmas.

Története
1948 és 1963 között a repülőtér részt vett a belföldi légiforgalomban; a Maszovlet és utóda, a Malév üzemeltette ide járatait a Budapest–Miskolc–Nyíregyháza–Budapest útvonalon, később Debrecen érintésével is. Az 1990-es évek elején történt rövid életű kísérlet a belföldi légiforgalom újraindítására, az első járat Nyíregyházáról indult a budaörsi repülőtérre, azóta azonban a repülőtér menetrend szerinti forgalommal nem rendelkezik.

Utasforgalom

Balesetek
A Malév elődjének, a Maszovletnek a két katasztrófája közül az egyik itt történt. 1952. október 2-án a HA-LIL lajstromjelű Li–2 gép a Budapest–Miskolc–Nyíregyháza–Budapest vonalon repült. A rossz időjárás miatt többször is meg kellett kísérelniük a leszállást Miskolcon és Nyíregyházán is, utóbbinál a síkos füvön megcsúszó gép épületnek ütközött. A személyzet három tagja, köztük a két pilóta, életüket vesztették, a személyzet két további tagja és a három utas megsérült.

Jegyzetek

Források

Magyarország repülőterei
Nyíregyháza