text:
Peak Risk
Article by John Serrapere
Investment Analyst & Strategist
Foster Holdings, Inc.
Are we missing a link or a file here?
Jim Nickerson
Shadow Fed, Contrary Old Fart
For two reasons Mr. Serepere's commentary is highly disturbing to me.
The first is because EJ prefaced it with, This is likely the most important analysis that iTulip.com has published in its seven year history.
The second reason it disturbs me is that I do not comprehend most of it.
Example: The wide credit spreads depicted in Figure 1 were warning investors to underweight or hedge assets with high correlations to the S&P 500 and high correlations to credit risk, while Figure 2 indicates the contrary.
As I understand the article, the credit spreads at the end of April 2006 were narrow (169 bps) as they were at the end of January 2000 (165 bps). In contrast to the Serepere's quote above, it seems that the narrow credit spreads existing a few days ago are warning investors to underweight or hedge assets with high correlations to the S&P 500 and high correlations to credit risk. Would that not be easier to understand if I am understanding it?
What assets have high correlations to credit risks?
Jim 69 y/o
"...Texans...the lowest form of white man there is." Robert Duvall, as Al Sieber, in "Geronimo." (see "Location" for examples.)
Dedicated to the idea that all people deserve a chance for a healthy productive life. B&M Gates Fdn.
Good judgement comes from experience; experience comes from bad judgement. Unknown.
Where can one find the yields on Baa Corporate Bonds?
From time to time I have come across someone describing one technical indicator or another. Many of these have seemed useful, but the initial problem for me was not having the data in order to be able to follow the indicator without relying upon someone else. Because no one answered my question above, thus saving me a lot of time searching, I had to search myself.
One can find the daily yield on TNX in numerous places, but I have not seen BBB (BBBdesignates the same grade bonds as Baa) corporate bond yield data anywhere I could get it for free. I found http://www.bondsonline.com/Todays_Market/.
If anyone wishes to follow the yield spreads between the 10 year BBB and TNX as described by John Serrapere, you can access that site. You must scroll down to find a blue graph on the left which charts the AAA and BBB yields. If you point to the chart you should get a pop up window that shows the yield for the grade of bonds at the various maturities. Getting the yields pop up might take pointing to it several times, and I could only get it to work using IE 6.0. It would not work with Mozilla/Firefox 5.0.
Serrapere said [Startquote]The 10-year T-note minus Baa Yield spread was 169 bps at the end of April 2006.[/QUOTE] Actually if you do it that way the spread is a minus number. Yesterday, 4/26, the TNX was 5.052% and at the above site the BBB 10 year yield was 6.49%, so the spread would be a minus 1.44%. The BBB 10 year bond was yielding 144 basis points more than the 10 year Treasury note, so this is even a tighter spead that Serrapere noted in his article on iTulip--this assumes I have not screwed up anywhere.
This indicator strikes me as one I wish to follow.
Serrapere said
The 10-year T-note minus Baa Yield spread was 169 bps at the end of April 2006.
Actually if you do it that way the spread is a minus number. Yesterday, 4/26, the TNX was 5.052% and at the above site the BBB 10 year yield was 6.49%, so the spread would be a minus 1.44%. The BBB 10 year bond was yielding 144 basis points more than the 10 year Treasury note, so this is even a tighter spead that Serrapere noted in his article on iTulip--this assumes I have not screwed up anywhere.
Sorry, I messed up the above post.
zeebie
Where can one find the yields on Baa Corporate Bonds? Jim
Daily Data from 1986: http://research.stlouisfed.org/fred2/series/DBAA/119
Weekly Data from 1962: http://research.stlouisfed.org/fred2/series/WBAA/119
Monthly Data from 1919: http://research.stlouisfed.org/fred2/series/BAA/119
zeebie,
GOOD MAN, I presume you are a man. If you are, and were I with you, I would probably hug you. If you are a woman, I would definitely hug you.
What you pointed out is a great data source.
The quotes below are taken from:Guest Commentary - May 26, 2006
Peak Risk by John Serrapere
Recent credit spreads are the narrowest since 1984. The spread from Treasuries to the lowest grade corporate bonds was recently 345 bps, while the long-term average spread has been 546 bps and the all-time widest spread was 1126 bps on October0, 2002. Under current conditions, corporations must grow free cash-flow, and that is tethered to earnings growth. The 10-year T-note minus Baa Yield spread was 169 bps at the end of April 2006, which is 40%-63% below normal, as shown in Tables 2 and 4 below, and a mere 4 bps wider than it was at the end of January 2000.
Tight spreads are odd given a flat yield curve, higher all-items inflation, rich equity valuations, and an aged business cycle. Narrow credit spreads under these conditions have been indicative of extreme risk. The stakes for high credit risk in this cycle are especially serious because of severe consumer indebtedness and structural financial imbalances resulting from U.S. domestic trade and federal deficits. The wide credit spreads that happened between February 2000 and October 2002 depicted in Figure 1 were warning investors to underweight or hedge assets with high correlations to the S&P 500 and high correlations to credit risk. Narrow credit spreads that happened between October 2002 and December 2005 as shown in Figure 2 indicate the contrary.
Based on my data on the TNX which has been downloaded initially from Worden.com, and updated daily for a long time using the closing quotes of TNX from schwab.com, and Baa data jsut downloaded from http://research.stlouisfed.org/fred2/series/DBAA/119, I find some discrepancies in what Mr. Serrapere said in his commentary above and my data.
The spread from Treasuries to the lowest grade corporate bonds was recently 345 bps,
My data show the last time the Baa-TNX was 345 bps or more was on 12/31/02 when it was 349 bps. That long ago, over 4 years ago, does not strike me as recent.
the all-time widest spread was 1126 bps on October0, 2002.
There is something significantly wrong with the above quote besides the typo that obscures the intended day of the month.
My data show the highest Baa-TNX spread since 12/30/99 was 395 bps on 10/14/02.
The 10-year T-note minus Baa Yield spread was 169 bps at the end of April 2006, which is 40%-63% below normal, as shown in Tables 2 and 4 below, and a mere 4 bps wider than it was at the end of January 2000.
My data show the Baa-TNS spread on 1/27/2000 was 154.5 bps. The lowest spread in April 2006 was 165.5 bps on 4/25, thus 11 bps wider than it was at the end of January 2000.
My interpretation of these spread data is likely infantile in perspective compared to Mr. Serrapere's; however, it strikes me that a point he was making is that these low spreads are (may be) precursors to future periods where the spreads will again widen and according to his Figure 1. during such periods of widening spreads one thing that may not do well is the SPX.
My data show that the Baa-TNX spread was 150.40 on 3/14/05. That is 4 bps lower than in January 2000, and 15 bps lower than in April 2006. Twenty-six market days after 3/14/05, the SPX bottomed on 4/20/05 at intraday 1136.15, and went on to hit 1326.70 intraday on 5/8/06. So with the Baa-TNX spread at what may be (if my data are correct) its lowest level since January 2000--that is, 150.40 on 3/14/05--the SPX subsequently rose 16.77%, which to me is not a bad gain in a few days less than 14 months.
Likely, I am missing something important here, but I do not know what it is.
If one takes the times of the two lowest spreads on the Baa-TNS spread since the beginning of 2000, following the first there was a collapse of the market to its October 2002 lows--a loss of 49% over 30.5 months. Following the second low spread of 150 bps 14 months ago, the SPX has risen almost 17%.
Had Mr. Serrapere published these same comments at the end of March 2005, they would have appeared to me to be more ominous, at least with regard to the Baa-TNS spreads data, than they are now, but after that the market measured by the SPX had a nice run up. Now, I do not know really what to make of his comments.
Where am I wrong?
Good job seeking to validate the author's research!
I can confirm a few things from what he said:
The 10-year T-note minus Baa Yield spread was 169 bps at the end of April 2006,
I show 167.
which is 40%-63% below normal, as shown in Tables 2 and 4 below,
I'm not sure where he gets this from. I show it is only 20% below average.
and a mere 4 bps wider than it was at the end of January 2000.
I show 167 now and 168 on the last day of January 2000.
The spread from Treasuries to the lowest grade corporate bonds was recently 345 bps
I believe he made a mistake here since as I just said, I can confirm his value at the end of April.
The spread from Treasuries to the lowest grade corporate bonds was recently 345 bps, while the long-term average spread has been 546 bps and the all-time widest spread was 1126 bps on October0, 2002.
I don't have a clue where he is getting these numbers. I checked this back to 1953 and I cannot confirm these values.
I found the returns going forward 1-Mth, 3-Mths, and 12-Mths on the S&P 500 for the various spread values. In order to simplify the evaluation, I broke the spreads into groups of 10% each -- decile baskets. Here is what I found for the 12 month forward return:
Lowest 5%: 116-148 -- 25.15%
Next 5%: 148-152 -- 27.39%
Lowest 10%: 116-152 -- 26.23%
Next 10%: 152-164 -- 20.40%
Next 10%: 183-198 -- 4.07%
Next 10%: 98-213 -- 5.85%
Next 10%: 253-285 -- -1.23%
Top 10%: 285-390 -- 3.52%
Based on the above, I would say that the author's comment that:
Narrow credit spreads under these conditions have been indicative of extreme risk.
Yes and no. Our present value is 168 bps. At this value the historical forward one month return for the S&P 500 is 2.04%, 3.52% for three months forward and 12.71% for one year forward. But the narrow the credit spread, the more likely that the market will bounce back as evidenced by the data compiled above.
I'll probably add this data to my own blog so if you are interested drop me an email and I'll give you temporary access to view the data and download the spreadsheet I put together for this study.
John Serrapere
Emerging Market securities and equities rated B or lower by S&P for earnings and dividnd quality are two expamles of asset with high correlations to credit spreads.
Readers should know that this paper was written as an internal white paper for my firm. The paper was addressing hedge fund styles with the advice to underweight styles with high correlations to credit risk. This paper was completed on Apr-20-2006 and revised on May 25, 2006 for itulip.com. Funds that employ the aforementioned securites and high yield bonds and various arb styles (if their bias tends to be too long) also have high correlations to credit risk. Shorts need liquidity more than longs so hedge funds are hurt badly when credit spreads widen.
I have a patent pending on a metric, Relative Value at Risk that measures systematic trend risk to the above. Since the fall of 2005 it has been warning of a 1997-1998 like risk for most hedge fund styles.
Made clarifications to John's piece. They are here:
http://www.itulip.com/peakriskmay2006.htm#update
Please also note John's comment that this work was written originally in late March and early April 2006.
I appreciate Mr. Serrapere's corrections and the value of his paper in general.
It is above my understanding as to why he chose to interject data on the Treauries versus the Credit Swiss High-Yield Index spreads, when eveything else of which he wrote concerned the 10 yearTreasury Baa spreads.


text:
navfn algorism
navfn
I am using the navfn. The algorithm works perfectly for me, but I would like to know whether there is any documentation about how it works.
And I'd like to understand the quadratic approximation.
link: http://www.ros.org/doc/diamondback/api/navfn/html/navfn_8cpp_source.html#l00473">http://www.ros.org/doc/diamondback/api/navfn/html/navfn_8cpp_source.html#l00473
00507 // use quadratic approximation
00508 // might speed this up through table lookup, but still have to
00509 // do the divide
00510 float d = dc/hf;
00511 float v = -0.2301 * d * d + 0.5307 * d + 0.7040;
00512 pot = ta + hf * v;
DimitriProsser
11153 ●79 ●116 ●169
Navfn uses Dijkstra's algorithm to search through the available working area and find the best path. What this means is that navfn uses breadth-first search to check the costmap cells for the optimal path. It begins at the robot's origin and radiates outward, checking each non-obstacle cell in turn until the goal is reached. You can find a primer on Dijkstra's algorithm here.
Navfn's optimal path is based on a path's "potential". The potential is the relative cost of a path based on the distance from the goal and from the existing path itself. It must be noted that Navfn update's each cell's potential in the potential map, or potarr as it's called in navfn, as it checks that cell. This way, it can step back through the potential array to find the best possible path. The potential is determined by the cost of traversing a cell (traversability factor, hf) and the distance away that the next cell is from the previous cell.
The section of code that you posted occurs during the update of a given cell during traversal. The quadratic approximation is used to overcome the limitation that navfn's potential array is four-connected, i.e. it only checks it's top, right, left, and bottom neighbors and not the diagonals. For example, in the section of code that you posted, tc is defined as the cell with the lowest of either the left cell or the right cell, and ta is the lowest of the top cell or the bottom cell. It then calculates the relative cost between these two cells. Then, the algorithm checks to see if the relative cost of traversing through a cell is less than the cost of going around it. If the cost of going around a cell is less than going through it, the algorithm uses the quadratic estimation to determine an approximate cost.
Is there a name for this particular method? Like in the normal Dijkstra's algorithm (taking Euclidean distance from start & goal to be the metric), there is no need to have the potential field with the traversabilitiy factor and the lowest neighbor and all that. What's this particular method called?
2ROS0 ( 2014-11-14 13:59:33 -0600 )edit
@2ROS0 It is called Wavefront expansion algorithm https://en.wikipedia.org/wiki/Wavefro... but it essentially has the same breadth first search propogation as the conventional dijkstras algorithm, the only difference is instead of constructing a tree of neighbours based on cost traversal, it assumes initially that all cells are at high potential except the start which is at zero potential, assigns finite potential values to each cell during traversal and then uses gradient descent to trace path back from end to start
indraneel ( 2020-06-25 05:18:39 -0600 )edit
I know this is an old question, but I have had the same doubt about the quadratic approximation. Found this https://github.com/locusrobotics/robo...
There it explains where the calculation comes from. How does it relate to the ideia of going around the cell in the answer? I mean, the potential is still assigned to the expanded node n, so for me, it is not clear how the algorithm "knows" it should go around instead of trasnversing through the cell.
PLui ( 2020-09-10 07:28:32 -0600 )edit
Last updated: Oct 03 '11
Motion primitives in Trajactory_planner_ros [closed]
Best way to send a goal with move_base that is off the global costmap?
navfn and carrot planner?
Want to know Navfn working in details!
Why does the navfn plan a path through a wall
switching global planner
Global Planner Parameters in Navigation
Navfn - Potential Field Calculation
Why does move_base abort this path?
How to use the DWB local planner

redpajama_set_name: RedPajamaCommonCrawl


text:
Community housing group seeks mortgage refinancing
OBJ staff
Mar 22, 2012 8:04am EDT
Ottawa Community Housing Corp.
OCHC
"A need for significant capital repair", coupled with a lack of money to deal with it, is prompting the Ottawa Community Housing Corp. to ask the city to approve a mortgage refinancing.
Although the group has subsidies and funding from existing capital repair programs, OCHC says those are "insufficient to complete the work that is required," and warns much of its portfolio is falling into almost irreparable disrepair.
It is looking to take advantage of the low-interest rate environment to refinance its existing debt and to generate additional revenues to partially fund the work.
A staff report describing the situation will go before the community and protective services committee meeting Thursday. The city is OCHC's sole shareholder.
If the proposal goes through, the city's annual payments of $2.09 million on the eight properties under consideration would not change, but the amortization period would be extended to 30 years.
The existing amortization on these properties ranges from 33 months to 15 years.
OCHC has applied to Infrastructure Ontario to refinance the eight mortgages, all of which renew in 2012. Its long-term borrowing rates are currently between 3.75 and 4.2 per cent, according to the report.
The amount remaining on the mortgage is $18.4 million. Refinancing the mortgages will fund a loan from Infrastructure Ontario of between $35 million and $37 million. That loan will pay out the existing mortgages and about $16.6 million to $18.6 million can be used for "priority capital repair work."
"The intention of the refinancing is to leverage the equity in existing assets to generate capital that can be applied toward the repair of the housing stock," the report stated.
"This can be accomplished by extending the amortization period to 30 years for each of these projects at a fixed rate of interest for the duration of the loan. By extending the amortization period and maintaining the debt payments at the current level, it is possible to generate approximately $16.6 million to $18.6 million in capital."
The properties under consideration are Lebreton 1, Strathcona: Sentier, Fairlea Court, Rockingham, Hasenack Place, Allard Place, Harmony House and Blohm Court, according to the report.
The report also warned that there is a gap between OCHC's existing annual funding and the required repairs to the aging portfolio, and requested consideration of the need for more capital investments. The average building in its portfolio is over 35 years old.
A 2008 building condition assessment found $211.4 million in capital repair classified as "past due and immediately required", and $121 million more needed during the next five years.
"This housing had reached a point where many building systems (e.g. roofs, elevators, waste stacks) required major repair or replacement. Many communities required extensive renewal or redevelopment and it was, and still is, a challenge to maintain them adequately," the report stated.
"Without further capital grants and increased annual funding, the backlog will continue to grow. There will be a direct impact on the quality of life for tenants and the eventual loss of stock as some buildings deteriorate to a point where they can no longer be rented or occupied."
In recent months, the corporation has drawn up plans to add more townhouses to its portfolio, and put solar panels on a fifth of its houses and apartments.
The group is Ottawa's largest community housing provider and the second-largest in the province after an agency in Toronto.
Controversial Chateau Laurier expansion not good enough, McKenna says
Controversial Château Laurier expansion cleared after final attempt to revoke approval fails
Councillors' effort to block Château Laurier addition fails – but will be reconsidered Thursday


text:
News|Humanitarian Crises
UN: Largest forgotten humanitarian crisis looms in CAR
UN refugee agency sounds alarm as number of people in need of aid reaches 2.7 million amid continued fighting.
UN Security Council has approved keeping a peacekeeping force in Central African Republic for another year [File: EPA]
The humanitarian crisis in the Central African Republic is in danger of becoming the largest forgotten humanitarian crisis, the UN refugee agency has said.
Almost 900,000 people from the country have been forcibly displaced, both to neighbouring countries and internally, by ongoing fighting in the country since December 2012, the UNHCR said in a statement on Monday. An estimated 2.7 million people are in need of aid in CAR and in its neighbouring countries, it said.
CAR crisis at a glance
Total population: 4.6 million
Total people in need of humanitarian assistance: 2.7 million
Internal Aid Cost
Required: $613m
Received: $85m
Internal Aid Deficit: $528m
Regional Aid Cost
Required: $331.2m
External Aid Deficit: $302.2
Total Aid deficit: $830.2m
– Source: UNHCR
"We must prevent the Central African republic from becoming a forgotten crisis," said Claire Bourgeois, the UN's humanitarian coordinator in the CAR said.
"The current funding for the strategic humanitarian response does not allow us to ensure the protection of all these displaced persons or to provide the minimum of what is needed to meet the huge humanitarian needs."
Muslim Seleka rebels seized power in March 2013, overthrowing then president Francois Bozize who responded with reprisal attacks by Christian anti-Balaka fighters.
Lack of funding
The statement by the UN agency comes just days ahead of a forum bringing together the key stakeholders in the crisis: the armed groups, trade unions, media, displaced people, employers, political parties, platform of religious organisations and the Muslim community.
With the humanitarian crisis in the country largely underfunded, it is likely to take precedence at the forum in the country's capital, Bangui, commencing on May 4.
A total of almost $613m in relief aid is required inside the country and $331.2m outside the country. Thus far, only $85m has been received for internal aid and $29m for external aid.
The country's humanitarian aid deficit is $830.2m, according to the UNHCR.
Separately, the UN Security Council has approved keeping a peacekeeping force in the CAR for another year due to the continuing violence in the country.
The council in March approved a resolution authorising an additional 1,030 military and police personnel for the nearly 12,000-strong peacekeeping force.
A transitional government is supposed to be organising elections for August this year, but instability threatens that goal.
United Nations and French troops are currently trying to stabilise the impoverished and landlocked country.
HRW: Muslim herders held captive by militia in CAR
Human Rights Watch demands intervention as year-long kidnapping of herders continues in Central African Republic.
Former CAR leaders sign 'meaningless' peace agreement
Deal between Francois Bozize and Michel Djotodia does not involve current government, raising doubts on its legitimacy.
CAR protesters clash with UN peacekeepers turns deadly
One dead and dozens hurt as hundreds protest UN mission's failure to stop raids by ethnic Peuhl pastoralists.


iN Education, Inc. is on a mission to increase the overall Standardized Testing averages on a national level, improve upon test prep ACT and SAT awareness, teach youth the "hard & soft skills" necessary for the success in all industries prior to entering the workforce, address health and wellness for the families, provide incentives to achieve high levels of education, and emphasize the importance of continuing education.
The current iN Education website was built on WordPress and keeping the same framework in mind, I had to come up with a design for the website, that would be responsive as well.
I started off the project by understanding the requirements of the nonprofit, which involved interview with the founder. Initial interviews led to creation of sitemap, to better understand the flow of the entire website.
After the approval of the sitemap, I started off with creating initial wireframes, that helped come up with a clear direction for the website from a flow, experience and information architecture perspective.
For a non-profit, telling a story is very important, which leads to donations and volunteer engagements, hence, I made sure the wireframe reflected what's more important for the organization to tell as their story.
The brand colors were very important for the organization and hence, keeping that in mind, I created the final interface designs based off of the wireframes and the back-and-forth feedback from the key decision makers.
When Sonali joined our IT team we didn't know what a great UX designer she was! She immediately took the charge of every project she was involved in; she had done her research and came up with a creative ways on how to improve our website(s) and how to get the work done. Sonali is a great graphic designer, UX developer and we have also discovered her secret passion for writing! We love new look of our website http://zealousness.org/.Our main company website http://ineducationonline.org/ is currently undergoing new facelift thanks to Sonali as well!
Sonali, thank you for sharing your talent with us! Keep up the great work you are doing.
Founder & Executive Director, iN Education, Inc.


BEVERLY HILLS, CA--(Marketwire - October 22, 2009) - Ewire -- Salon City, Inc. (PINKSHEETS: SALN) announced today that plans for the next phase of development of its Salon City Network (SCN) of independent distributors and salons have commenced through Beauty Entertainment magazine. The magazine has begun featuring top salons in key cities in the USA, which are being submitted by several leading distributors who are representing the network in markets that they serve. New markets being featured are Chicago, New Jersey, New York City and Baltimore.
Steven Casciola, President and CEO of Salon City, Inc., said, "BE! Magazine is giving us a unique opportunity to brand salons, distributors and sponsors in our new 'Radar' section of the publication. Distributors have positively received the new magazine as well as their opportunity to brand all three segments of the industry with our publication and Salon City's Network. From here, we plan to offer the salons a membership and licensing relationship that will begin to provide added support in marketing, education, branding and retailing of Salon City's products which will also include the magazine itself."
Casciola added, "We are receiving requests from distributors to sponsor additional markets and we intend to set the stage to generate more business by branding the salons that come onboard with SCN. When distributors brand and position salons in BE!, they will eventually be licensed to sell smaller portions of their space in our publication. Each distributor is then offered the opportunity to select top salons to involve them in the SCN program. The revenue both SCN and the distributors receive will cover their initial investment, leaving room for profit. Salon profits can increase also as the media exposure starts creating more demand and the number of salons working with Salon City increases."


There are currently no listings available in Morado Cove Condos. Save this Search to be notified by email as soon as new Morado Cove Condos listings hit the market.
*Morado Cove Condos Market Stats are based on Austin MLS data as of April 20th, 2019 at 10:25am CDT.
Morado Cove Condos is in the Arboretum/Great Hills section of Northwest Austin, a high-demand area only 11 miles from Downtown Austin in Travis County's 78759 zip code. The community, dating to 2008, is at 10300 Morado Cove, west of Highway 183 at Braker Lane. For buyers wanting a gated, suburban neighborhood close to schools, employment and shopping, check out Morado Cove condos.
Buyers of Morado Cove Condos for sale enjoy hill country views from their 1 and 2-story residences in over 20 buildings set along Morado Cove. The stone and stucco elevations, hip roofline, covered entryways and 1 and 2-car attached garages make each unit feel like a home. At over 2,000 square feet in size, these houses live larger than the typical condominium. Gorgeous interiors with gas fireplace, high ceilings, rear balcony and wall of windows give a very distinctive look to these units built by Morado Cove Partners.
Where are Morado Cove Condos Austin TX?
Find out more about Morado Cove Condos for sale. To explore homes in the community, take MoPac Expressway /TX-1 Loop N to Highway 183 N. Exit toward Braker Ln/Balcones Woods Drive. Follow West Braker Lane to Morado Circle. This community is 11 from Downtown Austin. Austin-Bergstrom International Airport is 19 miles from the neighborhood.
Surrounded by trees, Morado Cove Condos for sale have the appeal of a hill country setting with the convenience of being close to many community amenities. Less than a mile from North Hills Town Center and The Arboretum at Great Hills, residents can choose among many stores and restaurants. HEB grocery store, Target, Pottery Barn, Costco Wholesale and The Cheesecake Factory are all nearby. For an evening out, Regal Cinema Gateway 16 at Gateway Shopping Center is less than 2 miles from most homes. Residents enjoy outdoor activities at Great Hills Park with walking trails that allow them to explore the beauty of Austin's hill country landscape of live oaks, wildflowers and succulent plants.
Austin ISD serves students living in Morado Cove Condos. Davis Elementary (K-5), Murchison Middle (6-8), and Anderson High (9-12) are the assigned schools for this community. Private school options include Hill Country Christian School (PK-12), St. Louis Catholic School (PK-8), and Austin International School (PK-5).
Contact a Morado Cove Condos REALTOR® today.
Interested in Buying in the Morado Cove Condos area?
Have a home to Sell in the Morado Cove Condos area?


Brandi Pine, LEED AP | WALSH Construction Co.
Brandi started her career as an assistant superintendent with Walsh in 2004 after graduating from Oregon State University with a BS in Construction Management. She spent over a decade in the field, acquiring a vast knowledge of construction systems with specific experience in constructing wood frame, multi-unit housing projects. She took the true Walsh "builder" path to Project Manager by working her way into positions of greater leadership and skill, from assistant superintendent to superintendent and as project manager, managing her first project in 2012 and just recently finishing The Union, a 189,713 SF, seven-story mixed-use apartment building.
With the company for over 13 years, she has experience in many types of projects, from mixed-use, market rate and affordable housing, to tenant improvements, and educational facilities. She has an extensive background in 5 over 1 wood framed construction projects. Other areas of construction that she has include an extensive background with preconstruction services and estimating. As a LEED AP, she will provide valuable insight and assistance with sustainability goals.


Lessons from various speakers at an annual study at our home. For additional lessons that some friends of our have been recording for years, visit their site at http://liveforit.us/ . There is a couple of seconds of lead time before a couple of the lessons. They usually begin within 60 seconds.
Justin created a handout for the first lesson. You can download the handout here.


You need support? We would be glad to help you!
With the purchase of Safexpert, you do not only receive an innovative and efficient software tool, but also first-class telephone support for technical installation and application questions.
We would be glad to support you!


text:
Analysts: Intel's Price-Slashing Stemming Market Loss to AMD
SAN FRANCISCO – Intel Corp.'s (INTC) attempt to stanch the loss of market share to Advanced Micro Devices Inc. (AMD), its smaller rival in the computer microprocessor business, appears to be working and may allow it to gain lost ground over the next six months, analysts said Friday.
AMD on late Thursday warned second-quarter revenue would be about $1.22 billion, or about 9 percent below the previous period.
In April, the Sunnyvale-based company had forecast revenue that would be flat or slightly below first-quarter sales of $1.33 billion. It pinned the lower estimate on declining sales of processors for desktop and notebook PCs.
The disclosure came as an abrupt reversal for AMD, which over the past year has picked up about 5 points of market share, mostly at the expense of Intel, according to Mercury Research.
With AMD's share hovering around 21 percent, company executives last month said they were preparing to supply 30 percent of the market's needs by 2008.
Steep price cuts from Intel, the world's biggest chip maker, appear to be throwing a fork in those plans, analysts said.
Over the past few months, Intel, head quartered in Santa Clara, has slashed prices for its PC processors by as much as 30 percent.
Intel, whose processors have been largely outgunned by higher-performing chips from AMD, also has been talking up future price cuts that are to coincide with the release of three new products, due by midsummer, it says will put the company back in the technological lead.
Intel's product and pricing forecasts caused people to delay buying computers over the quarter, some analysts said.
"In the years that we've been covering Intel we can't recall another time that the company has been so willing to talk about price cuts, simply because that tends to damage demand for the near term," Merrill Lynch analyst Joe Osha wrote in a report. "At this point, though, pushing demand as far out as possible has made sense for Intel given Intel's own problems and planned product launches for Q3."
Bank of America analyst Sumit Dhanda agreed that Intel's cuts hurt sales of AMD's PC processors, adding that in some cases the larger company's prices were lower than comparable products offered by AMD.
AMD made cuts of its own, but they came later in the quarter. They also ranged from 8 percent to 10 percent — smaller than Intel's reductions, he said.
"Intel has been a share gainer in the desktop and notebook segments throughout the June quarter, thanks to aggressive pricing incentives," Dhanda wrote. The cuts, "although not enough to mitigate the weak PC demand, helped stimulate demand for Intel parts vs. AMD's."
He predicted the pattern would continue as Intel introduces a desktop chip code-named Conroe later this month and a notebook processor code-named Merom in August.
Spokesmen for Intel and AMD declined to comment ahead of conference calls to discuss quarterly earnings both companies have scheduled for later this month.
Analysts also attributed AMD's miss to flagging PC demand. Merrill Lynch's Osha said the two companies' combined second-quarter revenue fell 14 percent from the previous period, while units declined 10 percent. That is "a lot worse" than is typical for this time of year.
"It looks to us like Intel's attempts to freeze demand by talking up Q3 price cuts are at least partially responsible for the poor Q2 environment," Osha wrote.
Citigroup analyst Glen Young wrote in a report that the chances of Intel missing its forecast have decreased, but have not been eliminated, since the quarter ended in June.
The analyst speculated revenue, which in April Intel forecast would be from $8 billion to $8.6 billion, has been steadied by sales to Apple Computer Inc. (AAPL), which recently began using Intel processors in many of the machines it sells.
AMD shares fell 27 cents, or 1.1 percent, to close at $23.56 in afternoon trading on the New York Stock Exchange. Intel lost 29 cents, or 1.5 percent, to $18.56 on the Nasdaq Stock Market.


A friendship that began in 1998. A casual conversation amongst friends in 2014. A social enterprise born in 2015.
We are the founders of Euforia Singapore, and this is our story.
We are three individuals who not only share a longstanding friendship since our secondary school days, but also a shared interest in social causes. This led to a dinner conversation in 2014, where we shared our personal experiences and discussed the plight of the smaller Non-Profit Organisations (NPOs) in Singapore.
Receive more funding and donations that allow them to conduct more Promotional & Public Relations activities.
In such a competitive landscape, where so many NPOs are vying for the attention of individuals, there will tend to be organisations that fall by the wayside.
This results in many of the less popular and less well-known NPOs to suffer from a lack of awareness amongst the wider community.
There is a lack of understanding amongst individuals of the causes that the smaller NPOs support, and the issues that their members and their families face.
In order to garner more support for their causes, educating the community is extremely essential. Unfortunately, the smaller NPOs do not have adequate funding or professional expertise to do so.
Using the televised charity shows as an example, in order to encourage viewers to make donations, they frequently feature stories of members of the various featured NPOs. These stories tug at the heartstrings of individuals, and tell the community the issues or difficulties that the NPOs and their members face.
Many of the lesser-known NPOs have members who suffer from similar issues or worse, and more needs to be done to educate the community that there are many others out there who also require their help or assistance.
Many individuals tend to not donate to NPOs that they are not familiar with, or whose cause they are not supportive of. This has a major impact on how the NPOs can help their members.
From our experience speaking to them, many of the smaller and lesser-known NPOs face problems with funding. As a result, their hands are tied when it comes to how much they can help each individual member.
The number of activities that the NPOs can carry out for their members, is also reduced, and dependent on the amount of excess funds that they have.
There are many professionals whose services or expertise are useful skills that the smaller NPOs can benefit from.
Professionals such as Lawyers, Accountants, Branding/Marketing/Public Relations Consultants, and Graphic Designers, just to name a few.
Many of such professionals are not volunteering their services to the NPOs, especially the smaller ones. Their help can alleviate many internal structural problems that NPOs face, and assist the NPOs tremendously by freeing up valuable resources for other purposes.
A place where you can Shop. Donate. Learn. Volunteer.
Click here to learn more about the SDLV Platform™.


We have prepared a wide selection of buttons that you can add via shortcodes. Please note that at buttons with icons you can add any icon that you wish with a simple link to the icon within the shortcode. The recommended size of the icons is 16 x 16. This is a convenient way to create your own nifty little buttons.


text:
Q: React Native Not Responding to Touch on Android Only I am trying to update a Flatlist to present as seen in this video:
https://www.youtube.com/watch?v=6XxpUhQqpjY
My elements include touchable components such as TextInput and Buttons.
This works perfectly in iOS. However, on Android, the Flatlist scrolls using the FlingGesture, but none of the touchable components responds to touch. When I tap on a TextInput the keyboard is not invoked.
I'm using NativeBase and React Navigation if that's helpful.
<Content>
 <FlingGestureHandler key='up'
  direction={Directions.UP}
  onHandlerStateChange={ev => { if (ev.nativeEvent.state === State.END) {
      //setActiveIndex()
      if (activeIndex === data.length -1) {
        return
      }
      setActiveIndex(activeIndex + 1)
    }
  }}
  >

  <FlingGestureHandler
  key='down'
  direction={Directions.DOWN}
  onHandlerStateChange={ev => {if (ev.nativeEvent.state === State.END) {
      //setActiveIndex()
      if (activeIndex === 0) {
        return
      }
      setActiveIndex(activeIndex - 1)
    }
  }}
  >
  <FlatList
  scrollEnabled={false}
  removeClippedSubviews={false}
  refreshControl={<RefreshControl refreshing={games.loadingGames}
  onRefresh={onRefresh} />}
  contentContainerStyle={{
    flex: 5,
    justifyContent: 'flex-start',
    padding: SPACING * 2
  }}
  style={{minHeight: Dimensions.get('screen').height-240}}
  data={games.sort((a,b) => {
      return (b.status === a.status) ? new Date(a.startDateTime) - new Date(b.startDateTime) : new Date(b.startDateTime) - new Date(a.startDateTime)
    })}
  CellRendererComponent={({item, index, children, style, ...props}) => {
    // console.log(`props`, props)
    const newStyle = [
      style,
      { zIndex: games.length - index }
    ]
    return (
      <View style={newStyle} index={index} {...props}>
        {children}
      </View>
    )
  }}
  keyExtractor={(item) => item.gameId.toString()}
  renderItem={({item, index}) => {
    const inputRange = [index -1, index, index + 1]
    const translateY = scrollXAnimated.interpolate({
      inputRange,
      outputRange: [50, 0, -100]
    })
    const scale = scrollXAnimated.interpolate({
      inputRange,
      outputRange: [.8, 1, 1.3]
    })
    const opacity = scrollXAnimated.interpolate({
      inputRange,
      outputRange: [1 - 1/VISIBLE_ITEMS, 1, 0]
    })
    const game = item
    return index >= activeIndex && index < activeIndex+2 && (
      <GameItem
        style={{
          minHeight: ITEM_HEIGHT,
          minWidth: ITEM_WIDTH,
          opacity,
          transform: [
            {
              translateY,
            },
            { scale },
          ],
        }}
        onLayout={getItemDimensions}
        game={game}
        selectGame={selectGame}
        onChangeText={onChangeScore}
        onChangeStars={onChangeStars}
        onSubmit={submitPrediction} />
    )
  }}
/>
  </FlingGestureHandler>
  </FlingGestureHandler>
</Content>

I have tried a lot of different solutions but cannot seem to resolve the issue.

A: If you are using android you should import GestureHandlerRootView from react-native-gesture-handler and wrap your component that contained  FlingGestureHandler with it. Something like this :
return(<GestureHandlerRootView style={{flex:1}}>
<FlingGestureHandler key='up'
  direction={Directions.UP}
  onHandlerStateChange={ev => { if (ev.nativeEvent.state === State.END) {
      //setActiveIndex()
      if (activeIndex === data.length -1) {
        return
      }
      setActiveIndex(activeIndex + 1)
    }
  }}
....rest of your code
</GestureHandlerRootView>);

redpajama_set_name: RedPajamaStackExchange


text:
Probiotic Alleviate Fluoride-Induced Memory Impairment by Reconstructing Gut Microbiota in Mice
Jinge Xin, Hesong Wang, Dong Zeng, Ning Sun, Lianxin Li, Ye Sun, and 6 more
published 01 Jun, 2021
Read the published version in Ecotoxicology and Environmental Safety →
Fluoride which is widespread in our environment and food due to geological origin and industrial pollution has been identified as developmental neurotoxicants. Gut-brain axis provide new sight to the brain-derived injury. We hypothesized that fluoride-induced memory impairment was associated with gut dysbiosis, which could be prevented by improving the gut microbiota.
Mice were given fluoridated drinking water (sodium fluoride, 100 mg/L) for 70 days and administered with PBS or a probiotic strain, Lactobacillus johnsonii BS15 for 28 days prior to and throughout a 70 day exposure to sodium fluoride.
Results showed that fluoride reduces the exploration ratio in Novel object recognition (NOR) test and the spontaneous exploration during the T-maze test in mice following an hour water avoidance stress (WAS), which were significantly improved by the probiotic. 16S rRNA sequencing showed a significant seperation in ileal microbiota between the fluoride-treated mice and control mice. Lactobacillus was the mainly targeting bacteria and significantly reduced in fluoride-treated mice. BS15 reconstructed the fluoride-post microbiota and increased the relative abundance of Lactobacillus. D-lactate contant and diamine oxidase (DAO) activity, two biomarkers of the gut permeability were reduced in the serum of probiotic-inocluated mice. ZO-1, an intestinal tight junction protein, which was reduced by fluoride in mRNA and protein levels were increased by the probiotic treatment. Moreover, in the hippocampus which is essential to learning and memory, the probiotic increased the down-regulated mRNA levels of myelinassociated glycoprotein (MAG) level, Bcl-xl and decreaed up-regulated mRNA levels of Bad in fluoride-treated mice. The probiotic applied in this study also increased down-regulated mRNA and protein levels of brain-derived neurotrophic factor (BDNF) and cAMP response element-binding protein (CREB), and balanced the inflammatory cytokines in mRNA and protein levels in hippocampus of fluoride-treated mice.
These results suggested that there may be some correlations between the fluoride-induced memory dysfunction and alteration of gut microbiota, and reconstruction of gut microbiota is a potential method to prevent the memory dysfunction.
Applied & Industrial Microbiology
Lactobacillus johnsonii BS15
memory dysfunction
gut–brain axis
Fluoride is a widespread environmental pollution, and ground water is the major source of exposure in which the fluoride concentration can be as high as 35 mg/L (Petrone, et al. 2013). Fluorosis induced by geological origin is a serious public health concern in 28 nations particularly in India and China (Rafique, et al. 015). In India, 230 districts of 20 states are at risk of high level of fluoride in drinking water (Srivastava, et al. 2020). In China, almost all the provinces have reported fluorosis except for Shanghai. Moreover, social modernization results in fluoride pollution because of industrial production, the mechanical processing of food, and the use of fluorine-containing crop protection. Based on previous reports, fluoride concentration in canned meat and brick tea is under 1 to more than 8.6 mg/kg (Fein, et al. 2001) and 600–2800 mg/kg (Fung, et al. 1999), respectively. Fluoride accumulation in our body can damage both bone (Petrone, et al. 2013) and non-bone tissues (Yan, et al. 2019; Qian, et al. 2013), such as the liver, kidney, spleen, and brain. The neurotoxic effects of fluorine must not be ignored because such effects can affect brain health in rodents at levels below those that induce dental lesions (Grandjean, et al. 2019). To date, fluoride has been identified as developmental neurotoxicants (Grandjean, et al. 2014).
Recently, evidence on fluoride-induced brain damage is increasing and focused on learning and memory dysfunction. An epidemiological study from Hulunbuir, Inner Mongolia of China based on 331 children aged 7 to 14 from four schools with the same teaching quality demonstrated that fluoride exposure even in low levels had negative effects on children's memory (Ding, et al. 2011). Similar studies were also found in other countries (Green, et al. 2020; Bashash, et al. 2017). Moreover, Liu et al. (2010) found that a rat exposed to fluoride (50 mg NaF/L) for 6 months showed prolonged escape latency in the Morris water maze test. Animal experiments also demonstrated that fluoride exposure could cause microtubule lesions; thickened postsynaptic density; pathologic, indistinct, and short synaptic cleft; and myelin damage (Niu, et al. 2018). Furthermore, brain-derived neurotrophic factor (BDNF) and cAMP/Ca2+-responsive element-binding protein (CREB), which have been identified to be involved in hippocampal plasticity and hippocampus-dependent memory based on considerable evidence, were decreased in mice exposed to fluoride (100 mg NaF/L) for 60 days (Niu, et al. 2018).
Recently, increasing evidence has demonstrated that the gut microbiota is associated with mood and memory disturbances, and improving the gut microbiota is a potential method to treat such diseases. For example, patients with colitis characterized by disordered gut microbiota have a high risk for anxiety (21%) and depression (15%) (Neuendorf, et al. 2016). Different colitis models represent the human behavioral phenotype. Zhao et al. (2020) found that the depression and anxiety-like behavior in dextran sulfate sodium-induced colitis model could be improved by lycopene through increasing the relative abundance of Bifidobacterium and Lactobacillus. Similarly, Jang et al. (2018) inoculated Lactobacillus johnsonii to 2,4,6-trinitrobenzenesulfonic acid-induced colitis model, which improved memory impairment by restoring the disturbed gut microbiota composition. Neuroactive metabolites and gut integrity are the main mechanisms underlying the communication between the gut and brain. Recently, Mao et al. (2020) observed increased levels of lactate in the fecal and brains of mice inoculated with Lactobacillus, and consequently, the mice had an improved memory. High levels of GABA are linked to novel object recognition and improved working memory and are consumed and produced by the gut microbiota, which influence circulating GABA levels (Strandwitz, et al. 2018). Damage of gut integrity can cause the bacteria and harmful metabolites to enter into the brain. Recently, Emery et al. (2017) found evidence for microbiological incursion into the brain. Zhan et al. (2016) found increased levels of Escherichia coli K99 and lipopolysaccharide (LPS) in Alzheimer's disease (AD) brain and suggested that Gram-negative bacteria-derived LPS induced AD neuropathology in an ischemia–hypoxia rat model. Collectively, these studies indicate a link between the gut microbiota and memory potential.
In addition, Luo et al. (2016) found that Lactobacillus spp. remarkably decreased and E. coli and Enterococcus spp. increased in fluoride-treated broiler. Therefore, we hypothesized that fluoride-associated memory impairment might be associated with gut microbiota changes. The present study aimed to determine the fluoride-exposed gut microbiome feature and assess whether adjusting the gut microbiota could alleviate the fluoride-induced memory dysfunction. Groups of mice were exposed to 100 ppm fluoride on the basis of (i) documented human exposures (The range of fluoride dose in adult is 0.84-27.1 mg per day, which convert to ppm is 0.19-6.02ppm [based on a 55 kg person drinking 4.5 L of water per day]; Supplementary Note 1 and Table S1), (ii) a dose equivalent equation adjusting for surface area differences between mice and humans (Coryell, et al. 2018) (Supplementary Note 1), (iii) the use of similar exposures in studies researching fluoride-associated brain lesion in mice (Table S2), and (iv) high dose for the potential damage in a shortened test period. We selected L. johnsonii BS15 (CCTTCC M2013663) as a potential strategy to regulate the gut microbiota. Bifidobacterium and Lactobacillus strains are commonly used to improve the gut microbiota. L.johnsonii BS15 (CCTTCC M2013663), which has been screened and separated by our team, showed a steady effect on adjusting the gut environment and lowering the intestinal permeability of mice with high-fat diet, thereby preventing non-alcoholic fatty liver disease (Xin, et al. 2014). We recently found that L. johnsonii BS15 improved memory dysfunction in mice induced by a 7 day water-avoidance stress (WAS) by enhancing the gut integrity, which could be a potential "psychobiotic" (Wang, et al. 2020). We used 16S rRNA gene sequencing to detect the feature of the gut microbiota in fluoride-infected mice and BS15-treated mice. We assessed the difference in memory ability between untreated and treated individuals by T-maze test and novel object recognition (NOR) test under psychological stress. Given the importance of the hippocampus on memory function, hippocampal inflammation and memory-associated protein were detected in this study. This study may provide new insight to the fluoride-induced memory impairment and novel method to prevent these impairment.
Culture and Treatment with BS15
L. johnsonii BS15 was grown under anaerobic condition in de Man–Rogosa–Sharpe broth (Qingdao Rishui Bio-technologies Co., Ltd., Qingdao, China) at 37 °C for 24 h. The quantity of bacterial cells was assessed by heterotrophic plate counts. L. johnsonii BS15 cells were then centrifuged (10,000×g, 10 min at 4 °C), washed three times by phosphate-buffered saline (PBS), and re-suspended in PBS (pH 7.0) at a density of 1×109 cfu cells/mL (daily consumption dose: 0.2 mL/mice).
Water avoidance stress (WAS)
WAS, a well-established model of psychological stress in mice, was used in our study as a psychological stressor. Mice were exposed to WAS, as Gareau et al. (2011) described with minor modifications. In brief, mice were placed on a small platform surrounded by room-temperature water (1 cm below the platform) in the middle of the home cage for 1 h. All the WAS and behavioral tests were carried out at 7:00 am–11:30 am.
Behavioural tests
NOR test: The NOR test was used to assess the ability of rodents to recognize a novel object in the environment. It is a widely used method for the detection of working memory alterations based on nature propensity for novel objects displayed by rodents. The task procedure included three phases (Antunes and Biala, 2012): habituation, familiarization, and test phase. In brief, in the habituation phase, each mouse was placed into the empty open-field arena (l×b×h=40 cm×40 cm×45 cm) for 1 h for habituation. The mouse was then removed from the arena and placed in its home cage. During the familiarization phase, one mouse, following 1 hour WAS, was placed in the arena containing two different objects (#A+#B) for 5 min. These two objects were placed in opposite corners of the cage. Then, the mouse was removed from the arena and returned to its cage for a 20 min rest. During the test phase, the mouse was returned to the arena and confronted with object B and a novel object (object #C, distinguishable from object #A). Exploration ratio (F#C/(F#C + F#B) × 100, F#C = frequency of exploring the object #C, F#B = frequency of exploring the object #B), which was used to assess the memory, was calculated.
The tendency of mice to explore novelty indicated that the presentation of the familiar object existed in their memory. The objects used included a green bottle cap (#A), orange bottle cap (#B), and a small smooth stone (#C).
T-Maze test: Enclosed T-maze, an apparatus with 10 cm-wide floor and 20 cm-high walls in the form of a "T" placed horizontally, was used. The stem of the two goal arms and a start arm was all 30 cm long. A central partition was placed in the middle of two goal arms extending into the start arm (7 cm). Every arm had a guillotine door. The apparatus and operating steps were consistent with Deacon and Rawlins(2006). First, the central partition was placed in the T-maze with all the doors open. Then, mouse, directly from its home cage or flowing exposure to WAS, was placed in the start area and allowed to select the left or right arm. The mouse was kept in the chosen arm by quietly sliding the door down. After 30 s, the mouse and central partition were removed, and the mouse was returned to its holding cage. After a retention interval of 1 min, the mouse was placed in the start area for a second trail with all the doors open. Each mouse was given 10 trials over 5 days and allowed to explore the maze before sated. If the mouse selected the other goal arm in consecutive trials, then this trial was marked as "correct." Each exploration should take no more than 2 min.
Establishment of an animal model and study design
Male ICR mice (3 weeks old, Chengdu Dashuo Biological Institute, Chengdu, China) were given 1 week to adapt to the new environment. After the adaptation period, mice were randomly divided into three groups and administered with either PBS (control group, F group) or L. johnsonii BS15 (prob group; 0.2 mL/day) for 28 days prior to and throughout a 70 day exposure to sodium fluoride. Mice were provided fluoridated drinking water (concentration: 100 mg NaF/L) from 28 days to 98 days, except for the control group. Mice were housed in a constant-temperature (20 °C–22 °C) room with a 12 h light/dark cycle (lights on from 06:00 to 18:00) and given free access to water and normal chow diet (Chengdu Dashuo Biological Institute). Each cage housed six mice.
On day 98 of the experiment, subsets of mouse in each group were sacrificed by cervical dislocation for sampling following exposure to 1 h WAS. Another 10 mice of each group were used for behavioral testing after exposure to 1 h WAS. Subsets of mouse in each group without acute stress were sacrificed for sampling baseline gut microbiota.
Blood was sampled from the mice orbit, and serum was separated by incubation at 4 °C for 30 min, followed by centrifugation at 2,000×g for 20 min, and stored at −30 °C. The left hippocampus and partial ileal tissue were removed and washed with ice-cold sterilized saline without RNA enzyme (RNase) and then immediately frozen in liquid nitrogen for gene expression analysis. The right hippocampus and partial ileal tissue were obtained and stored at −80 °C for further biochemical detection. Luminal sample was collected from the ileum and stored at −80 °C for analysis of lumen-associated microbiome based on 16S rRNA gene sequencing. The ileal content was collected and stored at −80 °C for 16S rRNA gene sequencing.
Biochemical evaluation
The ileal tissue and right hippocampus were ground (pH 7.4) into 10% or 5% homogenate with PBS, respectively, and then centrifuged (12,000×g for 5 min at 4 °C). The obtained liquid supernatant was used for biochemical detection. The D-lactate and diamine oxidase (DAO) activity, contents of corticosterone (CORT) in the serum, the inflammatory cytokines in the liquid supernatant of the ileum and hippocampal homogenate, and apoptosis-regulated proteins in the liquid supernatant of hippocampal homogenate were measured by the commercial enzyme-linked immunosorbent assay (ELISA) kit for mice according to the manufacturer's instructions. The inflammatory cytokines included tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), IL-6, interferon-gamma (IFN-γ), and IL-10 (only detects ileal tissue). All the commercial ELISA reagent kits were obtained from Enzyme-linked Biotechnology Company (Shanghai Enzyme-linked Biotechnology Co., Ltd., China).
Real-time quantitative polymerase chain reaction (qPCR) analysis of gene expression
Total hippocampal RNA and ileal RNA were isolated using E.Z.N.A.® Total RNA Kit (OMEGA Bio-Tek) according to the manufacturer's instructions. Isolated RNA was assessed from the ratio of absorbance at 260 and 280 nm and agarose gel electrophoresis for quantitative and qualitative analyses. The isolated RNA was transcribed into first-strand complementary DNA with PrimeScript RT reagent kit with gDNA Eraser (Thermo Scientific, Waltham, Massachusetts, USA) according to the manufacturer's instructions. qPCR was performed with SYBR green and primers (details previously published) (Xin, et al. 2014). The PCR conditions were as follows: 1 cycle at 95 °C for 5 min, followed by 40 cycles at 95 °C (10 s) and optimum temperature (30 s), and then a final melting curve analysis to monitor the purity of the PCR product. The optimum temperature of each gene was shown in Table S3. β-Actin was used as reference genes to normalize the relative mRNA expression levels of target genes with values presented as 2−ΔΔCq. Primer sequences and optimum annealing temperatures were shown in Table S3. The relative expression levels of neurogenesis-related factors (BDNF, CREB, SCF, and NCAM), molecular myelin structure (MOG, PLP, MBP, and MAG), apoptosis-related proteins (Bax, Bad, Bcl-2, Bcl-xl, casepase9, and casepase3), cytokines (IFN-γ, TNF-α, IL-1β, IL-6, and IL-10) in the hippocampus, and tight junction (TJ) proteins (ZO-1, claudin-1, and occludin) in ileal tissue were detected.
A subset of mice in each group was sacrificed, and their brain was removed, fixed in 4% paraformaldehyde solution, and stored in 4 °C for immunohistochemical assay. The brain tissues were embedded by paraffin and cut by a microtome. Slices were submerged in citrate antigen retrieval solution and heated at medium heat until boiling using a microwave oven (model: P70D20TL-P4; Galanz, Guangdong, China). The temperature was ceased, and the tissues were kept warm for 8 min. Then, the tissues were heated at medium–low heat for 7 min. After free cooling, the slices were placed into PBS (pH 7.4) and shaken for 5 min for decoloration, which was repeated three times. Afterward, the sections were incubated in 3% oxydol for 25 min at room temperature and away from the light to block endogenous peroxidase. The slices were washed three times in PBS by shaking for 5 min, then sealed for 30 min by 3% bull serum albumin, and incubated with monoclonal rabbit anti-Occludin, anti-Claudin-1, or anti-ZO-1 (1:200) antibodies at 4 °C overnight. Species-specific biotinylated anti-rabbit immunoglobulin (horseradish peroxidase labeled) was used for immuno-detection. Following the second antibody incubation, the 3,3′-diaminobenzidine staining kit was used to complete the reaction according to the manufacturer's instructions. Hematoxylin staining was performed to re-stain the nucleus.
16S rRNA gene sequencing
Bacterial genomic DNA was extracted using the E.Z.N.A.TM stool DNA isolation kit (Omega Bio-Tek, Doraville, CA). The final elution volume was 100 µL, and the integrity, purity, fragment size, and concentration were determined by electrophoresis with 1% agarose gel. The 16S V3-V4 was amplified by PCR using the primer 515F/806R of the 16SrRNA gene. Then, the purified PCR products were formed into a library with Ion Plus Fragment Library Kit 48 rxns (Thermofisher, USA) and sequenced in the Ion S5™XL platform (Thermofisher, USA) using the single-end sequencing. The primer contained adapter sequences and single-end barcodes, allowing pooling and direct sequencing of PCR products. Cutadapt (V1.9.1, http://cutadapt.readthedocs.io/en/stable/) was applied to the resulting high-quality 16SrRNA gene reads. The 16S rRNA gene read pairs were demultiplexed on the basis of the unique molecular barcodes, and reads were merged using VSEARCH (Rognes, et al. 2016). Sequences were clustered into operational taxonomic units (OTUs) at a similarity cutoff value of 97%. Then, OTU representative sequences were produced using the Uparse v7.0.1001. Species annotation analysis was performed on the OTU representative sequences through the SILVA Database. Homogenized data of each sample were constructed using the sample with the least amount of data as the standard. This sample was used for downstream analyses of alpha-diversity, beta-diversity, phylogenetic trends, and functional prediction.
The 16S rRNA sequencing data were analyzed by T-test, Wilcoxon rank-sum test, or Tukey test to detect significant differences among the different groups. All other results were reported by mean ± standard deviation. Groups were compared using Student t-test and one-way analysis of variance (ANOVA) with Duncan's multiple range test for significant difference test. Differences of p<0.05 were considered as statistically significant.
As shown in Figs. 1A and 1B, the spontaneous exploration in the T-maze test and the exploration ratio in the NOR test were significantly reduced in the F group compared with the control and prob groups. No significant difference was observed in the abovementioned indexes between the control and prob groups. Fig. 1C shows that the F group exhibited a remarkably higher serum CORT level than the other two groups, but no significant difference was found between the other two groups.
Figs. 2A and 2B show a sharp decrease in mRNA expression levels of BDNF and CREB in the F group compared with the other two groups. The mRNA level of BDNF in the control group was higher than that in the prob group (Fig. 2A). No difference was observed in the CREB mRNA level between the control and prob groups (Fig. 2B). Moreover, no significant difference was found among the three groups (Fig. 2C). Compared with the control group, the SCF mRNA level was remarkably reduced in the F group and slightly decreased in the prob group (Fig. 2D). By contrast, the prob group presented a slightly higher SCF mRNA level than the F group (Fig. 2D). As shown in Figs. 2E–2J, the protein expression levels of BDNF and CREB were significantly reduced in the F group compared with that in the other two groups.
As shown in Figs. 3A and 3D, TNF-α and IFN-γ protein levels were significantly increased in the F group compared with that in the control and prob groups. However, the mRNA level of the abovementioned indexes in the F group was significantly higher than the control group. This difference was slight compared with the prob group. Similarly, the mRNA level of the abovementioned indexes in the prob group was slightly higher than that in the control group. However, the prob group presented significantly higher TNF-α and IFN-γ protein levels than the control group. No significant difference in IL-1β among the three groups was found in the mRNA and protein levels (Fig. 3B). As shown in Fig. 3C, the F and prob groups showed a lower IL-6 than the control group both in the mRNA and protein levels. Compared with the prob group, the significant increase of IL-6 in the F group was observed in the protein level but not in the mRNA level.
Figs. 4A and 4B show that the mRNA expression levels of PLP and MOG in the F and prob groups were sharply decreased compared with that in the control group. The PLP in the prob group was slightly higher than that in the F group. No significant difference in the MOG was observed between the F and prob groups. No changes in the MBP mRNA expression level were observed among the three groups (Fig. 4C). As shown in Fig. 4D, the F group presented a significantly lower MAG mRNA level than the other two groups. Compared with the control group, MAG was remarkably reduced in the prob group (Fig. 4D).
No significant difference in the Bcl-2 mRNA level was found among the three groups, whereas the prob group showed the highest among the three groups (Fig. 5A). In Fig. 5B, the F group presented a lower Bcl-xl mRNA level than the other two groups, but no difference was observed in the other two groups. As shown in Fig. 5C, the Bax mRNA level in the F group was slightly increased compared with that in the other two groups, but no significant difference was observed among the three groups. Fig. 5D shows a remarkably increased Bad mRNA level in the F group compared with the other two groups, whereas no difference was observed in the other two groups. As shown in Figs. 5E and 5F, no significant difference in the casepase3 and casepase9 mRNA level was observed among the three groups, but casepase3 in the control group and casepase9 in the F group were the lowest and highest, respectively, among the three groups.
The gut microbiota with or without stress were observed in each group to determine the influence of fluoride and acute stress on the gut microbiota. Through 16s rRNA gene sequencing, we did not find significant alterations in the gut microbiota of mice exposed to WAS versus non-stressed animals (Fig. S1, supplementary materials). Thus, the data with or without WAS were combined in each group.
As shown in Figs. 6A and 6B, principal coordinate analysis based on unweighted UniFrac distances and principal component analysis showed a clear separation between the ileal microbiota of mice in the F group and those in the other groups, whereas no significant separation was observed between the other two groups. Moreover, the observed species (Fig. 6C) and Shannon index (Fig. 6D) in the ileal lumen microbiome of mice in the F group were significantly increased compared with that in the control group, whereas significant increases were not observed in the prob group. The ileal microbial communities among the three groups were dominated by Firmicutes in the phylum level (Fig. 6E). As shown in Fig. 3F, relative abundance of Firmicutes in the F group was significantly reduced compared with that in the control and prob groups. On the contrary, the relative abundances of Actinobacteria (Fig. 6G), Bacteroidetes (Fig. 6H), and Cyanobacteria (Fig. 6I) increased markedly in the F group compared with the control and prob groups. The alteration of these common phyla induced by fluoride was significantly inhibited by L. johnsonii BS15. At the genus level (Fig. 6J), Lactobacillus was the important bacterium in the control, F, and prob groups, and the relative abundance of the nine main genera found in the three groups was different. As shown in Fig. 6K–S, the F group presented a sharply reduced relative abundance of Lactobacillus and Candidatus_Arthromitus and a significantly increased relative abundance of Streptococcus, Romboutsia, Allobaculum, unidentified_Clostridiales, Dubosiella, Bifidobacterium, and unidentified_Lachnospiraceae compared with the control group. However, L. johnsonii BS15 suppressed these alterations except for Streptococcus, unidentified_Clostridiales, Bifidobacterium, and Candidatus_Arthromitus. Compared with the control group, more genera bloomed or diminished in the ileal lumen of the F group than those in the prob group (Fig. 6T).
As shown in Figs. 7A and 7D, the F group showed a sharp increase in the mRNA and protein levels of TNF-α and IFN-γ compared with the other two groups, but no significant difference was observed between the other two groups except for the TNF-α mRNA level. Fig. 7B shows that the control group presented a lower IL-1β mRNA and protein levels than the other two groups, but no marked difference was found between the other two groups. No difference was observed in the IL-6 mRNA and protein levels among the three groups (Fig. 7C). Fig. 7E shows a sharp decrease in the IL-10 mRNA and protein levels in the F group than the other two groups, but no difference was found between the other two groups.
As shown in Fig. 8A, the F group shows a markedly lower ZO-1 mRNA level than the other two groups, but significant difference was not observed in the other two groups. Compared with the control group, the mRNA expression levels of claudin-1 and occludin were sharply decreased in the F and prob groups. No significant difference was observed in claudin-1 mRNA level between the control and prob groups. The occludin mRNA level in the prob group was slightly higher than that in the F group. The protein expressions of TJs were also detected by immunohistochemistry, and the results showed the same trend (Fig. 8C).
As shown in Fig. 8B, compared with the control group, the serum DAO content was significantly and slightly increased in the F and prob groups, respectively. The control group showed a remarkably lower serum D-lactate activity than the other two groups. By contrast, the D-lactate activity in the F group was significantly higher than that in the prob group.
The results of this study provided strong evidence that reconstructing the gut microbiota could protect the brain from fluoride-induced damage and dysfunction under acute stress. Several lines of evidence supported the conclusion. First, fluoridated drinking water altered the gut microbiota structure and resulted in a reduced hippocampal BDNF and poor performance in memory-associated behavioral tests under psychological stress. Second, these alterations were reversible upon reconstruction of the microbiota by gavage with L. johnsonii BS15.
A 70 day exposure to sodium fluoride combined with 1 h exposure to WAS lowered memory potential in this experiment, indicated by the low spontaneous exploration in T-maze test and low exploration ratio in NOR test. In our previous study, different exploration ratios in NOR test were not observed between the F and control groups in the absence of WAS (data not shown). WAS is a commonly used psychological stress. Studies found that an hour of WAS exposure could not induced behavioral changes in the T-maze and NOR tests but could cause compounding effect on behavior when combined with other harmful materials (e.g., endotoxin exposure and bacterial infection) by enhancing the HPA axis responsiveness (Gareau, et al. 2011; Walker, et al. 2008). Thus, an hour of WAS exposure was added to make the potential memory impairment more evident in this experiment. Consequently, fluoride exposure resulted in HPA hyper-responsiveness to stress, indicated by abnormal elevated serum CORT in fluoride-treated mice compared with the control mice. This result was consistent with predecessors' research (Gareau, et al. 2011). Apart from the behavioral phenotypes, memory-associated gene expressions were assessed in the RNA and/or protein levels. Neuronal plasticity is the basic of learning and memory and occurs by neurogenesis, synaptic-dependent activity, cellular apoptosis, and reorganization of neuronal networks. The hippocampus, a highly plastic region, is critical for learning and memory. BDNF is one of the important modulators of neuroplasticity because of its multiple effects, such as increasing hippocampal neurogenesis, dendritic branching, cell proliferation, and promoting hippocampal long-term potentiation (Pang, et al. 2004; Cassilhas, et al. 2016). Blocking the hippocampal BDNF expression caused an impairment of spatial and reference memory (Mizuno, et al. 2000). CREB, the transcriptional regulator of BDNF, has been considered as the central to AD pathology by similar genomic network analysis (Jeong, et al. 2001). In addition, many studies using genetically modified mice revealed that a growing number of genes, such as CREB, BDNF, NCAM, and SCF, were involved in the regulation of neurogenesis. In the present study, fluoride showed adverse effects on neuroplasticity as indicated by the remarkable decrease in the expressions of BDNF, CREB, and SCF on the mRNA and/or protein levels, which was consistent with the observations of Niu et al. (2018). Buffington et al. (2016) reported that the behavioral deficits and disordered gut microbiota in maternal high-fat diet offspring could be recovered by co-housing the offspring of mothers on a regular diet. Kumar et al. (2017) suggested that L. johnsonii could increase the concentrations of acetate and butyrate in feces. Butyrate, a short-chain fatty acid, could decrease BDNF methylation and consequently cause an overexpression of BDNF by decreasing 10 to 11 translocation methylcytosine dioxygenase 1, which was the enzyme responsible for catalyzing the conversion of DNA methylation to hydroxymethylation (Wei, et al. 2014). Moreover, Luo et al. (2016) found that Lactobacillus spp. was significantly reduced in fluoride-treated broiler. Thus, L. johnsonii BS15 was supplemented to fluoride-treated mice to investigate whether L. johnsonii BS15 could reconstruct the gut microbiota and alleviate memory impairment. Memory was assessed using the same T-maze and NOR tests in the L. johnsonii BS15-inoculated mice and compared with that of control and F-treated mice. Based on our data, the L. johnsonii BS15-inoculated mice showed a significant improvement in memory compared with fluoride-treated mice. Furthermore, the negative effects of fluoride treatment on the HPA response, BDNF, and CREB have been reversed by L. johnsonii BS15. Fluoride treatment showed significantly adverse effects on the SCF expressions, which were not improved by administering L. johnsonii BS15. Thus, L. johnsonii BS15 prevented memory impairment in fluoride-infected mice, mediated the upregulations in BDNF and CREB, and attenuated the HPA response to an acute psychological stress to a certain extent.
Chronic neuroinflammation attracts public attention for its role in mental health and diseases. However, considerable evidence proved that fluoride accumulation could activate microglia, a resident macrophage in the CNS, and lead to the production of proinflammatory cytokines. Prior studies have noted the importance of aberrant intestinal microbiota, altered intestinal immune response, and impaired intestinal barrier on the neuroinflammation (Salehipour, et al. 2017). A possible mechanism underlying L. johnsonii BS15, which protected mice from fluoride-induced memory impairment, could be the inhibition of neuroinflammation. We quantified inflammatory cytokines in both mRNA and protein levels in the hippocampus to test this possibility. Inconsistent with previous studies (Guo, et al. 2017), we found that fluoride increased the TNF-α mRNA level in the hippocampus. In addition, hippocampal IFN-γ was increased in fluoride-infected mice under acute stress. Nevertheless, the effect of chronic fluorosis on the level of IL-6 was controversial. Yan et al. (2016) reported that the protein expression level of IL-6 was increased in microglial cells of rats exposed to fluoride. Moreover, evidence has shown that fluorosis inhibited the activity of immune cells resulting in the reduction and secretion of IL-6 (Guo, et al. 2017), which was consistent with our results that excessive fluoride intake could reduce IL-6. Early studies showed that high level of TNF-α could reduce synaptic density in the hippocampus (Salucci, eta al. 2014). Considerable evidence has suggested that IL-6 has a modulatory effect on TNFα-induced hippocampal injury (Harry, et al. 2003), and high level of TNF-α and low level of IL-6 might mediate the altered hippocampal volume and verbal memory difficulties (Kesler, et al. 2013). Supplement with L. johnsonii BS15 ameliorated neuroinflammation in the stressed and fluoride-infected mice by reducing the hippocampal TNF-α and IFN-γ and increasing IL-10. This finding was consistent with that of Salehipour et al., who reported that probiotic was a potential therapy to attenuate chronic CNS inflammation (Salehipour, et al. 2017). Sun et al. also demonstrated that reversing gut microbial dysbiosis could reduce the activation of the TLR4/TNF-a signaling pathway in microglia and astrocytes of Parkinson's disease (PD) mice and recover motor dysfunction of PD mice (Sun, et al. 2018). On the basis of the abovementioned results, we could hypothesize that the reduced neuroinflammation in BS15-inoculated mice was associated with the alleviated memory impairment.
We observed the mRNA expression of myelin-associated protein to assess the effect of L. johnsonii BS15 on hippocampal impairment induced by fluoride. Previous studies have demonstrated that fluoride could induce demyelination (Niu, et al. 2018). Notably, myelin sheath constituted by MOG, PLP, MBP, and MAG was important for axonal protection and interneuronal communication (Nguyen, et al. 2009). In accordance with the previous studies, the present results showed that fluoride significantly reduced the PLP and MAG in the hippocampus (Niu, et al. 2018). In addition, in this study, hippocampal PLP was significantly reduced, which might be due to the longer time of fluoride exposure or the acute stress exposure. MAG located in the innermost lamellae of myelin sheaths, as an inhibitor of mature axonal regeneration, could also promote stability and survival of myelinated axons (Nguyen, et al. 2009). A local downregulation of MAG is the critical signal for CNS injury (Nguyen, et al. 2009). Treatment with L. johnsonii BS15 effectively inhibited the reduction of MAG in fluoride-infected and stressed mice. Moreover, L. johnsonii BS15 upregulated the mRNA expression of Bcl-xl (anti-apoptotic) and downregulated the mRNA expression of Bad (pro-apoptotic) in the hippocampus of fluoride-infected and stressed mice, indicating that hippocampal apoptosis was linked to fluoride-induced memory impairment, whereas L. johnsonii BS15 improved hippocampal apoptosis.
The gut microbiota is a key modulator of the bidirectional signaling pathways between the gut and brain. We conducted 16S rRNA gene sequencing on the ileal contents of mice to identify whether the reconstruction of gut microbiota was a potential mechanism underlying the hypothesis that BS15 protected mice from memory impairment induced by fluoride. An hour of WAS exposure did not significantly change the gut microbiota structure (Fig. S1 and Table S4). We substantiated the composition differences of the gut microbiota in fluoride-treated mice through Adonis testing (Table S5) and unweighted analyses of UniFrac distances, and the administration of L. johnsonii BS15 reversed those differences. Firmicutes, which accounted for up to 90% of the total sequences, was the dominant phylum in each group. Disordered gut microbiota in fluoride-exposed mice was primarily manifested by the relative abundance decrease of Firmicutes in the phylum level and Lactobacillus in the genus level. Lactobacillus is an important genus in Firmicutes. The relative abundance of Lactobacillus in the control, F, and prob groups was 87.7%, 38.1%, and 72.7%, respectively. The reduction of Lactobacillus induced by fluoride was consistent with the results of Luo et al. (2016) Spearman correlation analysis in the genus level of the control group showed that Lactobacillus was negatively associated with most of the bacteria (66.7%; Fig. S2A). In addition to the reduction of Lactobacillus, the abovementioned negative association between Lactobacillus and most bacteria was weakened and shifted to positive association in the F group (Fig. S2B), indicating that the inhibiting effect of Lactobacillus on other bacteria was weakened, which explained the increases in community diversity (Shannon index) and richness indices (number of observed features) in fluoride-infected mice. The administration of L. johnsonii BS15 reversed these changes (Fig. S2C). This finding was in accordance with that of previous studies, which have suggested that Lactobacillus could suppress the growth of other bacteria, particularly harmful bacteria, because of its enzymatic, fibrinolytic, and broad-spectrum antimicrobial activity (Eom, et al. 2015). New evidence by 16S rRNA gene sequencing of the gut microbial community in the genetically defined collaborative cross mouse cohort with different memory potentials showed that higher relative abundances of Lactobacillus indicated higher memory potential (Mao, et al. 2020). This result was in accordance with that of Gareau et al., who showed that BDNF could reduce the risk of disorder and increase the stability of the gut microbiota (Gareau, et al. 2011). The alteration of microbiota composition indicated that the reconstruction of the gut microbiota might be an important potential mechanism underlying the improvement of memory in BS15-inoculated mice.
On the basis of recent reports, which associated bacteria and their products with memory in human (Emery, et al. 2017; Zhan, et al. 2016) (e.g., E coli K99, LPS), we focused on understanding the alterations of gut inflammation and intestinal integrity underlying the improvement of memory in gut microbiota-reconstructed mice. We observed increased pro-inflammatory cytokines (TNF-α, IL-1β, and IFN-γ) and decreased anti-inflammatory cytokine (IL-10) and TJ proteins (ZO-1, claudin-1, and occludin) in the mRNA and/or protein levels in the ileum of the F group, indicating an enhanced gut inflammation and damaged intestinal epithelial integrity. The increased serum DAO content and D-lactate activity in the F group also indicated that fluoride increased gut permeability. Serum DAO activity and D-lactate content, indicators of mucosal integrity, would be increased when the intestinal mucosal integrity was destroyed (Luk, et al. 1980; Ewaschuk, et al. 2005). Gut microbiota reconstruction improved gut inflammation and gut permeability. These findings were consistent with the previous findings that specific probiotic administration could improve gut inflammation and intestinal mucosa integrity (Mujagic, et al. 2017). Damaged intestinal mucosal integrity and some pro-inflammatory factors not only caused peripheral immune activation but also crossed the blood–brain barrier to aggravate neuroinflammation in the CNS under pathological conditions. Ait-Belgnaoui et al. also found that probiotic treatment could prevent leaky gut, thereby attenuating HPA response to an acute psychological stress in rats (Ait-Belgnaoui, et al. 2012). Hence, these results indicated that gut inflammation and intestinal mucosa integrity might be involved in the pathogenesis of neurotoxic effects of fluoride and might be the primary reason that reversed gut microbiota improved memory deficit in fluoride-infected mice under acute stress.
This study showed that fluoride-exposed and stressed mice displayed impaired memory, damaged myelin, and a hyperactive HPA axis, coupled with a disordered gut microbiota structure particularly reduced relative abundance of Lactobacillus. Reconstruction of the gut microbiota by inoculating L. johnsonii BS15 could recover gut physiology, reverse memory deficit, alleviate myelin damage, and reduce the hyperactivity of the HPA axis. Collectively, our findings first indicated an importanat role of gut dysbiosis in improving memory impairment in fluoride-infected and stressed mice. Adjustment of the gut microbiota might be a potential treatment strategy to prevent food-borne memory damage.
CNS, central nervous system; HPA, hypothalamic-pituitary-adrenal; CORT, corticosterone; NOR, object recognize; WAS, water avoidance stress; PBS, phosphate buffered saline; ELISA, enzyme-linked immunosorbent assay; OTUs, operational taxonomic units; BDNF, brain-derived neurotrophic factor; CREB, cAMP/Ca2+ responsive element-binding protein; SCF, stem cell factor; NCAM, neuronal cell adhesion molecule; MOG, myelin oligodendrocyte glycoprotein; PLP, proteolipid protein; MBP, myelin basic protein; MAG, myelin-associated glycoprotein; Bcl-2, B-cell lymphoma-2; Bcl-xl, B-cell lymphoma-extra large; Bax, Bcl2-associated X protein; Bad, Bcl-xL/Bcl-2 asociated death promoter; TNF-α, tumor necrosis factor-α; IL-β, interleukin-β; IL-6, interleukin-6; IFN-γ, interferon-γ; IL-10, interleukin-10; ZO-1, zonula occludens protein 1; DAO, diamine oxidase.
All data generated or analysed during this study are included in this published article [and its Additional file 9].
16S rRNA sequencing reads have uploaded to NCBI. The accession code of 16S rRNA sequencing reads in the National Center for Biotechnology Information (NCBI) BioProject database : PRJNA660154.
All animal experiments were performed according to the guidelines for the care and use of laboratory animals approved by the Institutional Animal Care and Use Committee of Sichuan Agricultural University (approval number: SYXKchuan2019-187).
'Not applicable' for that section
The authors declare that they have no competing interests
The present study was supported by National Natural Science Foundation of China (31970503) and Sichuan Science and Technology Program (2019YFH0060).
JX, HW, DZ, YB, and XN designed the experiment, such as Performing literature reviews, selecting search engines and search terms, and defining inclusion/exclusion criteria qualifies. JX, NS, LL, and AK performed the animal experiments and sample collection, and drafted the manuscript. YS, YZ, and KP helped to draft the manuscript. BJ and XN supervised the study.
The authors gratefully acknowledge the help from Ms. Peng Xueji and Mr. Zhang Shuai for all the hard working during the behavioral tests. Also, we really appreciate the supports provided by all other undergraduates during the animal feeding and sampling.
Authors' email addresses
JX: [email protected]; HW: [email protected]; DZ: [email protected], NS: [email protected]; LL: [email protected]; YS: [email protected]; AK: [email protected]; YZ: [email protected]; KP: [email protected]; BJ: [email protected]; YB: [email protected]; XN: [email protected].
Ait-Belgnaoui, A.; Durand, H.; Cartier, C.; Chaumaz, G.; Eutamene, H.; Ferrier, L.; Houdeau, E.; Fioramonti, J.; Bueno, L.; Theodorou, V. Prevention of gut leakiness by a probiotic treatment leads to attenuated HPA response to an acute psychological stress in rats. Psychoneuroendocrinology. 2012, 37, 1885-95.
Antunes, M.; Biala, G. The novel object recognition memory: neurobiology, test procedure, and its modifications. Cogn Process. 2012, 13, 93-110.
Bashash, M.; Thomas, D.; Hu H.; Martinez-Mier, E. A.; Sanchez, B. N.; Basu, N.; Peterson, K. E.; Ettinger, A. S.; Wright, R.; Zhang, Z.; Liu, Y.; Schnaas, L.; Mercado-García, A.; Téllez-Rojo, M. M.; Hernández-Avila, M. Prenatal fluoride exposure and cognitive outcomes in children at 4 and 6-12 years of age in Mexico. Environ Health Perspect. 2017, 125, 097017.
Buffington, S. A.; Prisco, G. V.; Auchtung, T. A.; Ajami, N. J.; Petrosino J. F.; Costa-Mattioli M. Microbial reconstitution reverses maternal diet-induced social and synaptic deficits in offspring. Cell. 2016, 165, 1762-1775.
Cassilhas, R. C.; Tufik, S.; Mello, M. T. Physical exercise, neuroplasticity, spatial learning and memory. Cell Mol Life Sci. 2016, 73, 975-83.
Coryell, M.; McAlpine, M.; Pinkham, N. V.; McDermott, T. R.; Walk, S. T. The gut microbiome is required for full protection against acute arsenic toxicity in mouse models. Nature communications. 2018, 9.
Deacon, R. M. J.; Rawlins, J. N. P. T-maze alternation in the rodent. Nat Protoc. 2006, 1, 7-12.
Ding, Y.; Gao, Y.; Sun, H.; Han, H.; Wang, W.; Ji, X.; Liu, X.; Sun, D. The relationships between low levels of urine fluoride on children's intelligence, dental fluorosis in endemic fluorosis areas in Hulunbuir, Inner Mongolia, China. J Hazard Mater. 2011, 186, 1942-6.
Emery, D. C.; Shoemark, D. K.; Batstone, T. E.; Waterfall, C. M.; Coghill, J. A., Cerajewska T. L.; Davies, M.; West, N. X.; Allen, S. J. 16S rRNA next generation sequencing analysis shows bacteria in Alzheimer's post-mortem brain. Front Aging Neurosci. 2017, 9, 195.
Eom, J. S.; Song, J.; Choi, H. S. Protective Effects of a novel probiotic strain of Lactobacillus plantarum JSA22 from traditional fermented soybean food against infection by salmonella enterica serovar typhimurium. J Microbiol Biotechnol. 2015, 25, 479-91.
Ewaschuk, J. B.; Naylor, J. M.; Zello, G. A. D-lactate in human and ruminant metabolism. J Nutr. 2005, 135, 1619-25.
Fein, N.J.; Cerklewski, F. L. Fluoride content of foods made with mechanically separated chicken. J Agr Food Chem. 2001, 49, 4284-4286.
Fung, K. F.; Zhang, Z. Q.; Wong, J. W. C.; Wong, M. H. Fluoride contents in tea and soil from tea plantations and the release of fluoride into tea liquor during infusion. Environ Pollut. 1999, 104, 0-205.
Grandjean, P. Developmental fluoride neurotoxicity: An updated review. Environ Health. 2019, 18, 110.
Gareau M. G.; Wine, E.; Rodrigues, D. M.; Cho, J. H.; Whary, M. T.; Philpott, D. J.; Macqueen, G.; Sherman, P. M. Bacterial infection causes stress-induced memory dysfunction in mice. Gut. 2011, 60, 307-17.
Grandjean, P.; Landrigan, P. J. Neurobehavioural effects of developmental toxicity. Lancet Neurol. 2014, 13, 330-8.
Green, R., Lanphear, B., Hornung, R., Flora, D., Martinez-Mier, A., Neufeld, R., Ayotte, P.,Muckle, G., Till, C. Fluoride exposure during fetal development and intellectual abilities in a Canadian birth cohort. Environ Int. 2020, 134, 105315.
Guo, H.; Kuang P.; Luo, Q.; Cui, H.; Deng, H.; Liu, H.; Lu, Y.; Fang, J.; Zuo, Z.; Deng, J.; Li, Y.; Wang, X.; Zhao, L. Effects of sodium fluoride on blood cellular and humoral immunity in mice. Oncotarget. 2017, 8, 85504-85515.
Harry, G. J.; Bruccoleri, A.; d'Hellencourt C. L. Differential modulation of hippocampal chemical-induced injury response by ebselen, pentoxifylline, and TNFα-, IL-1α-, and IL-6-neutralizing antibodies. J Neurosci Res. 2003, 73, 526-36.
Jang, S. E.; Lim, S. M.; Jeong, J. J.; Jang, H. M.; Lee, H. J.; Han, M. J.; Kim D. H. Gastrointestinal inflammation by gut microbiota disturbance induces memory impairment in mice. Mucosal Immunol. 2018, 11, 369-379.
Jeong, H.; Mason, S. P.; Barabási, A. L.; Oltvai, Z. N. Lethality and centrality in protein networks. Nature. 2001, 411, 41-2.
Kesler, S.; Janelsins M.; Koovakkattu D.; Palesh O.; Mustian K.; Morrow Gary.; Dhabhar F. S. Reduced hippocampal volume and verbal memory performance associated with interleukin-6 and tumor necrosis factor-alpha levels in chemotherapy-treated breast cancer survivors. Brain Behav Immun. 2013, 30, S109-16.
Kumar, S.; Pattanaik, A. K.; Sharma, S.; Jadhav, S. E.; Dutta, N.; Avneesh Kumar. Probiotic potential of a Lactobacillus bacterium of canine Faecal-Origin and its impact on ielect gut health indices and immune response of dogs. Probiotics Antimicrob Proteins. 2017, 9, 262-277.
Liu, Y. J.; Gao, Q.; Wu, C. X.; Guan Z. Z. Alterations of nAChRs and ERK1/2 in the brains of rats with chronic fluorosis and their connections with the decreased capacity of learning and memory. Toxicol Lett. 2010, 192, 324-9.
Luo, Q.; Cui, H.; Peng X.; Fang, J.; Zuo, Z.; Deng, J.; Liu, J.; Deng, Y. Dietary high fluorine alters intestinal microbiota in broiler chickens. Biol Trace Elem Res. 2016, 173, 483-91.
Luk, G. D.; Bayless, T. M.; Baylin, S. B. Diamine oxidase (histaminase). A circulating marker for rat intestinal mucosal maturation and integrity. J Clin Invest. 1980, 66, 66-70.
Mao, J. H.; Kim, Y. M.; Zhou, Y. X.; Hu, D.; Zhong, C.; Chang, H.; Brislawn, C. J.; Fansler, S.; Langley, S.; Wang, Y.; Peisl, B. Y. L.; Celniker, S. E.; Threadgill, D. W.; Wilmes, P.; Orr, G.; Metz, T. O.; Jansson, J. K.; Snijders, A. M. Genetic and metabolic links between the murine microbiome and memory. Microbiome. 2020, 8, 53.
Mujagic, Z.; Vos P.; Boekschoten, M. V.; Govers, C.; Pieters, H. J.; Wit, N. J. W.; Bron, P. A.; Masclee, A. A. M.; Troos, F. J. The effects of Lactobacillus plantarum on small intestinal barrier function and mucosal gene transcription; a randomized double-blind placebo controlled trial. Sci Rep. 2017, 7, 40128.
Mizuno, M.; Yamada, K.; Olariu, A.; Nawa, H.; Nabeshima, T. Involvement of brain-derived neurotrophic factor in spatial memory formation and maintenance in a radial arm maze test in rats. J Neurosci. 2000, 20, 7116-21.
Neuendorf, R.; Harding, A.; Stello, N.; Hanes, D.; Wahbeh, H. Depression and anxiety in patients with Inflammatory Bowel Disease: A systematic review. J Psychosom Res. 2016, 87, 70-80.
Niu, R.; Chen, H.; Manthari, Ram Kumar 1, Zilong Sun 1, Jinming Wang 1, Jianhai Zhang 1, Jundong Wang. Effects of fluoride on synapse morphology and myelin damage in mouse hippocampus. Chemosphere. 2018, 194, 628-633.
Nguyen, T.; Mehta, N. R.; Conant, K.; Kim, K. J.; Jones, M.; Calabresi, P. A.; Melli, G.; Hoke, A.; Schnaar, R. L.; Ming, G. L.; Song, H.; Keswani, S. C.; Griffin, J. W. Axonal protective effects of the myelin-associated glycoprotein. J Neurosci. 2009, 29, 630-7.
Pang, P.T.; Lu, B. Regulation of late-phase LTP and long-term memory in normal and aging hippocampus: role of secreted proteins tPA and BDNF. Ageing Res Rev. 2004, 3, 407-30.
Petrone, P.; Guarinob, F. M.; Giustino, S.; Gombos, F. Ancient and recent evidence of endemic fluorosis in the Naples Area. J Geochem Explor. 2013, 131, 14-27.
Qian, W.; Miao, K.; Li, T.; Zhang, Z. Effect of selenium on fluoride-induced changes in synaptic plasticity in rat hippocampus. Biol Trace Elem Res. 2013, 155, 253-60.
Rafique, T.; Naseem, S.; Ozsvath, D., Hussain, R.; Bhanger, M. I.; Usmani, T. H. Geochemical controls of high fluoride groundwater in Umarkot Sub-District, Thar Desert, Pakistan. Sci Total Environ. 2015, 530-531, 271-278.
Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahé, F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016, 4, e2584.
Salehipour, Z.; Haghmorad, D.; Sankian, M.; Rastin, M.; Nosratabadi, R.; Dallal, M. M. S.; Tabasi, N.; Khazaee, M.; Nasiraii, L. R.; Mahmoudi, M. Bifidobacterium animalis in combination with human origin of Lactobacillus plantarum ameliorate neuroinflammation in experimental model of multiple sclerosis by altering CD4+ T cell subset balance. Biomed Pharmacother. 2017, 95, 1535-1548.
Salucci, S.; Ambrogini, P.; Lattanzi, D,; Betti, M.; Gobbi, P.; Galati, C.; Galli, F.; Cuppini, R.; Minelli A. Maternal dietary loads of alpha-tocopherol increase synapse density and glial synaptic coverage in the hippocampus of adult offspring. Eur J Histochem. 2014, 58, 2355.
Srivastava, S.; Flora, S. J. S. Fluoride in drinking water and skeletal fluorosis: a review of the global impact. Curr Environ Health Rep. 2020, 7, 140-146.
Strandwitz, P. Neurotransmitter modulation by the gut microbiota. Brain Res. 2018, 1693, 128-133.
Sun M. F.; Zhu Y. L.; Zhou Z. L.; Jia X. B.; Xu Y. D.; Yang Q.; Cui C.; Shen Y. Q. Neuroprotective effects of fecal microbiota transplantation on MPTP-induced Parkinson's disease mice: Gut microbiota, glial reaction and TLRLI/TNF-alpha signaling pathway. Brain Behav Immun. 2018, 70, 48-60.
Wang, H.; Sun, Y.; Xin, J.; Zhang, T.; Bai, Y. Lactobacillus johnsonii BS15 Prevents psychological stress–induced memory dysfunction in mice by modulating the gut–brain axis. Probiotics Antimicrob Proteins. 2020, doi: 10.1007/s12602-020-09644-9. (Online ahead of print)
Walker, F. R.; Knott, B.; Hodgson, D. M. Neonatal endotoxin exposure modifies the acoustic startle response and circulating levels of corticosterone in the adult rat but only following acute stress. J Psychiatr Res. 2008, 42, 1094-103.
Wei, Y.; Melas, P. A.; Wegener, G.; Mathé, A. A.; Lavebratt, C. Antidepressant-like effect of sodium butyrate is associated with an increase in TET1 and in 5-Hydroxymethylation levels in the Bdnf Gene. Int J Neuropsychopharmacol. 2014, 18, pyu032.
Xin, J.; Zeng, D.; Wang, H.; Ni, X.; Yi, D. Kangcheng Pan, Bo Jing. Preventing non-alcoholic fatty liver disease through Lactobacillus johnsonii BS15 by attenuating inflammation and mitochondrial injury and improving gut environment in obese mice. Appl Microbiol Biotechnol. 2014, 98, 6817-29.
Yan, X.; Dong, N.; Hao, X.; Xing Y.; Tian, X.; Feng, J.; Xie, J.; Lv, Y.; Wei, C.; Gao, Y.; Qiu, Y.; Wang, T. Comparative transcriptomics reveals the role of the toll-like receptor signaling pathway in fluoride-induced cardiotoxicity. J Agr Food Chem. 2019, 67, 5033-5042.
Yan, N.; Liu, Y.; Liu, S.; Cao, S.; Wang, F.; Wang, Z.; Xi, S. Fluoride-induced neuron apoptosis and expressions of inflammatory factors by activating microglia in rat brain. Mol Neurobiol. 2016, 53, 4449-60.
Zhao, B.; Wu, J.; Li, J.; Bai, Y.; Luo, Y.; Ji, B.; Xia, B.; Liu, Z.; Tan, X.; Lv, J.; Liu X. Lycopene alleviates DSS-induced colitis and behavioral disorders via mediating microbes-gut-brain axis balance. J Agric Food Chem. 2020, 68, 3963-3975.
Zhan, X.; Stamova, B.; Jin, L. W.; DeCarli, C.; Phinney, B.; Sharp, F. R. Gram-negative bacterial molecules associate with Alzheimer disease pathology. Neurology. 2016, 87, 2324-2332.
Additionalfile9.xlsx
Additionalfile8.pdf
Additionalfile6.docx