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The Kitchen and Bath Industry Show (KBIS) announced the winners of the 2015 Best of KBIS Awards. Entries in this competition included more that 100 products and winners were announced in five categories: Best Kitchen – Gold and Silver, Best Bath – Gold and Silver and...

There is nothing better than holiday traditions made in the kitchen! All of us at Kitchen Designs wish you and your family a holiday season full of blessings and love. May your kitchens be filled with wonderful holiday traditions and lasting memories! It...

Want your turkey to come out fabulous with zero effort! Enlist the help of a steam oven. All you have to do is choose a cooking mode using steam and/or convection that's ideal for your dish, and the oven automatically adjusts everything to perfection whether...

We are pleased to announce the availability of a new cabinet color available in the Cottage Collection, Cottage Putty on Maple. This new cabinet color combines the cool Designer Color Putty with the addition of glazing, rub through, and physical...

Hardware for cabinets is like the jewelry we select to wear with our clothes. We can change our look by changing our jewelry. The same is true in the kitchen, and beautiful cabinet hardware can pull your entire kitchen together. Hardware for me is personal. You...

Many of our clients at Kitchen Designs are choosing cluster lighting in the kitchen to add an artistic element and focal point over their kitchen island or dining table. Have a look at the way these cluster lights utilize varying heights, shapes, finishes, and...

Ken and I would like to thank the Manhasset Women's Coalition Against Breast Cancer for its dedication, compassion, and tireless work helping many women in our community in need. It is a cause close to our hearts, and this year the Coalition celebrated...

Wolf Appliance, Inc., a leader in high-end cooking equipment, introduced a new Wolf Gourmet line of luxury countertop kitchen appliances and kitchen tools including blenders, toasters, and toaster ovens now available in the United States. These new countertop...

It has been a few weeks since I posted a Wacky Wednesday unique find, and I love that some of you called me on it. We have been swamped over here before the holidays. I will always welcome your feedback, but as some of you know, I had to turn off...

Northport, Long Island kitchen designed by Ken Kelly, CKD, CBD, CR of Kitchen Designs by Ken Kelly, Inc.; Interior design by Judith Deutsch Designs... Imagine returning to your dock just a few steps from your Northport home after an exhilarating morning boat...

If you're seeking a nostalgic, retro kitchen vibe, there are many options available in kitchen appliances, furniture, and accessories that can help you create the look. All the cabinetry including the entertainment center in this studio loft is Brookhaven by...

The cosmetics industry has the right idea by offering colors for every season and reason. Having renovated many interiors in my career and having seen clients pack up drawers and bins full of wonderfully colored cosmetics, I often wondered why they look...

After my recent visit to the Sub-Zero / Wolf factory, I am anxiously awaiting the arrival of the NEW “M” Series ovens. I already love their “L & E” series ovens but the new “M” series ovens have so much more to offer. Two vertical style convection fans which give...

A Kalamazoo Outdoor Kitchen Experience Awaits There is a lot of BUZZ about our Kalamazoo outdoor kitchen line. It is nice to see so many others that share in the excitement for outdoor kitchen grills, pizza ovens, and weather proof outdoor cabinetry. Here are...

We have been on the road photographing some kitchen renovations we recently completed on Long Island for our photo gallery. We also have several new, exciting developments happening at Kitchen Designs plus all new showroom renovations going on. It sure has been a...

Did you know you can now bring bring exquisite Bentley luxury car interiors into your home? One of the nice things about having a press pass for Milan's Design Week was being granted the privilege of photographing the Bentley Luxury Home booth for our Kitchen Designs...

Recently we attended a kitchen design seminar in NY and learned more about "The Galley Sink". This sink design would actually make me want to do the dishes especially when it is so easy to add a few helpers. Here's what Jen had to say... As a big fan of the Food...

Happy 4th of July! I love this holiday because it connects all Americans with each other in a flash of tremendous gratitude. We are ready for another fourth of July party, are you? This is the perfect time of year to spend with family and friends enjoying delicious...

How cute is this new mini fridge with retro style from Smeg? It is the perfect size for college dorm rooms, offices, or even home mini bars. Mini Fridge: The Italian appliance brand Smeg is known for its iconic 50's...

The tea and coffee cup chandelier with drop crystals is from Troy Lighting's Barista Collection. This is a unique way to light up your breakfast room. It comes in various sizes and is shown here in the 12 light version with vintage bronze finish. You...

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"Every room uniquely tells the story of its owners who live and find comfort in the environments we create."

With 35+ years of established relationships in the kitchen and bath industry, Kitchen Designs fully discloses we are affiliated with the manufacturers and vendors whose products we sell, discuss, and link to on this site. This design blog is written by Grace Kelly in collaboration with our Kitchen Designs team.


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Of the 23 trials they identified, 12 were methodologically sound enough to include in their analysis. The analysis revealed that some statistically significant weight loss occurred, but the magnitude of the effect is small and the clinical relevance is uncertain.

They also found that gastrointestinal adverse events were twice as likely in the hydroxycitric acid group as in the placebo group. When you are considering the potential benefits of products look for meta-analysis studies that take in all the sound research available.

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Topographically guided two-step LASIK and standard LASIK in the correction of refractive errors after penetrating keratoplasty.
To evaluate in a long-term period the effectiveness and safety of topographically guided two-step laser in situ keratomileusis (LASIK) and standard LASIK technique in the correction of refractive errors after successful penetrating keratoplasty (PKP) for keratoconus. At least 2 years after PKP and 6 months after removal of all sutures, 15 eyes of 15 patients (Group 1; mean manifest refraction spherical equivalent (MRSE) -7.23 D -/+ 3.42 SD) were submitted to standard LASIK and 15 eyes of 15 patients (Group 2; mean MRSE -4.37 D -/+ 1.97 SD) to a topographically guided two-step LASIK procedure (first the flap and at least 2 weeks later the laser ablation). In all cases, a superior hinged corneal flap(160 microm/9.5 mm) was created. After a follow-up of 36 months, in Group 1 the mean uncorrected visual acuity (UCVA) was 0.51 logarithm of the minimum angle of resolution (logMAR) -/+ 0.41 SD and the mean best-corrected visual acuity (BCVA) was 0.03 logMAR -/+ 0.05 SD, with a mean MRSE of -1.57 D -/+ 2.65 SD. In Group 2, the mean UCVA was 0.28 logMAR -/+ 0.24 SD and the mean BCVA was 0.01 logMAR -/+ 0.03 SD, with a mean MRSE of -0.07 D -/+ 1.00 SD. In both groups, no complications were observed. After a long follow-up period, both topographically guided two-step LASIK and standard LASIK could be considered effective and safe tools in the correction of refractive errors after successful PKP for keratoconus.


S4C considers moving HQ from Cardiff to Carmarthen or Gwynedd

The Welsh language television channel said it could relocated its head office to either Carmarthen or Gwynedd but it would carry out the second part of a study before deciding.

S4C's HQ has been in Cardiff since the channel launched 31 years ago.

It is hoped the study will be completed by the first half of 2014. The channel stressed it would maintain a "presence" in the capital.

The first phase of the study which began last year asked organisations to suggest relocation ideas for the channel.

The second phase will look at moving the channel's HQ and it will work with two groups, one led by the University of Wales Trinity Saint David in Carmarthen and another led by Gwynedd council.

Ian Jones, the channel's chief executive, said: "Moving forward with step two of our feasibility study shows that we're giving full consideration to how much more S4C can do to ensure that the whole of Wales benefits as much as possible from our existence as a national channel.

"I'm really looking forward to seeing the outcomes of the additional work that will be done now in conjunction with our potential partners in Carmarthen and Gwynedd."

Gwynedd Council welcomed the announcement.

Gwynedd Council leader Dyfed Edwards said: "It is very encouraging that Gwynedd has been identified as one of two possible areas being considered by S4C for their headquarters.

"It would certainly be a tremendous boost to our local economy and the Welsh language if this goes ahead."


Q:

How can I submit form data to other website in Angular4?

I have a form on my Angular component. What I need to do is post form data to another site and open the page in new window.
Basically, I want it to be like
<form action="http://othersite.com/otherpage" target="_blank" method="POST">
   <input name="test">
   <button type="submit">Submit</button>
</form>

For some reason Angular blocks the form processing. Is there any way to send form data to the page on another website?

A:

The NgForm directive is applied to form elements, but its selector allows adding the ngNoForm attribute to avoid applying it:
selector: 'form:not([ngNoForm]):not([formGroup]),ngForm,[ngForm]',

So you can use
<form ngNoForm ... >

to have a plain old form.


Q:

Write CSV file from scraped data with Beautiful Soup

This is how I scraped the data using Beautifulsoup.
comments =[]
users_list = []
users = driver.find_elements_by_class_name('_6lAjh')

for user in users:
    users_list.append(user.text)

i = 0
texts_list = []
texts = driver.find_elements_by_class_name('C4VMK')

for txt in texts:
    texts_list.append(txt.text.split(users_list[i])[1].replace("\r"," ").replace("\n"," "))
    i += 1
    comments_count = len(users_list)

for i in range(1, comments_count):
    user = users_list[i]
    text = texts_list[i]
    print("User ",user)
    print("Text ",text)
    print()
    comments.append(users_list[i])
    comments.append(texts_list[i])
    idxs = [m.start() for m in re.finditer('@', text)]
    for idx in idxs:
        handle = text[idx:].split(" ")[0]

print(handle)

This is the text data I have which are username, comments, and number of likes from instagram.
' heyyy 3w1 likeReply' -> 'heyyy' is comment in here, 3w means the comment was written 3weeks ago, 1 like is number of likes
print(comments)

['User1',
 '  3w1 likeReply',
 'User2',
 '  3w1 likeReply',
 'User3',
 ' Looking good! Collab, DM "bruteimpact.fashion 3wReply',
 'User4',
 ' heyyy 3w5 likeReply']

I want to save this into CSV file that looks like this(three columns- ID, Comments, likes_count):
ID  Comments  likes_count
User1        0
User2        1
User3 Looking good! Collab, DM "bruteimpact.fashion  0
User4 heyyy    5

so far this is the code I wrote but is far from the result I want to get and I do not know how to get to the final destination at all. Plus, I have no idea how to make separate 'likes_count' by detaching the number of likes from the comment data I have. However, I would be satisfied with CSV file with just "ID" and "Text" column without "likes_count". Please help me!
fields = ["User", "Text"]
rows = [comments]
filename = "insta_records.csv"
with open(filename, 'w', encoding='utf-8') as csvfile:
    csvwriter = csv.writer(csvfile)
    csvwriter.writerow(fields)
    csvwriter.writerows(rows)

A:

You have flat list so you could use zip to group user and its comment
comments = ['User1',
 '  3w1 likeReply',
 'User2',
 '  3w1 likeReply',
 'User3',
 ' Looking good! Collab, DM "bruteimpact.fashion 3wReply',
 'User4',
 ' heyyy 3w5 likeReply']

rows = []
for user, text in zip(comments[::2], comments[1::2]):
    print(user, text)
    #rows.append([user, text])

fields = ["User", "Text"]
filename = "insta_records.csv"
with open(filename, 'w', encoding='utf-8') as csvfile:
    csvwriter = csv.writer(csvfile)
    csvwriter.writerow(fields)
    csvwriter.writerows(rows)

Result on screen
User1   3w1 likeReply
User2   3w1 likeReply
User3  Looking good! Collab, DM "bruteimpact.fashion 3wReply
User4  heyyy 3w5 likeReply

And in file
User,Text
User1,  3w1 likeReply
User2,  3w1 likeReply
User3," Looking good! Collab, DM ""bruteimpact.fashion 3wReply"
User4, heyyy 3w5 likeReply

To create other columns you would have to first edit comments - split(), replace(),
slice [start:end],  etc.
rows = []
for user, text in zip(comments[::2], comments[1::2]):
    parts = text.rsplit(' ', 2)#[:-1]
    parts.insert(0, user)
    print(parts)
    rows.append(parts)

Result on screen
['User1', ' ', '3w1', 'likeReply']
['User2', ' ', '3w1', 'likeReply']
['User3', ' Looking good! Collab, DM', '"bruteimpact.fashion', '3wReply']
['User4', ' heyyy', '3w5', 'likeReply']

but there is missing space in '3wReply' so it doesn't split it correctly and it would need more work to split it correctly.
BTW: when you have 3w5 then you can split('w') to get ['3', '5'] but in HTML can be other text instead of w so it would need more work. Maybe using more complex rules in BeautifulSoup you could better split it.


Q:

Writing SQL in Coderpad

I have an interview coming up in which I will write code in Coderpad.  What is the syntax to write SQL in Coderpad? (note Coderpad with an "r", not Codepad).
First, you select a language for Coderpad.  I am selecting Scala.
Here is a database they provide:
+--------------------+-----------+---------------+
| Table Name         | Row Count | Table Size KB |
+--------------------+-----------+---------------+
| departments        |         5 |       16.0000 |
| employees          |         6 |       32.0000 |
| employees_projects |         5 |       48.0000 |
| projects           |         3 |       16.0000 |
+--------------------+-----------+---------------+

Here is Scala code that does work:
object Solution extends App {
  for (i <- 0 until 5) println("Hello, World!")
}

I want to run a simple SQL query.
SELECT * FROM employees;

Note: I can write complex SQL in Spark with Scala.  I have written hundreds of Databricks Scala notebooks.  So, I do not need a primer on Scala or SQL.
I simply need the correct SYNTAX to write any simple SQL query in CoderPad just to get me started.  Thank you.
In other words, how do I insert a SQL statement into a Scala Object?
I tried:
object Solution extends App {
  //for (i <- 0 until 5) println("Hello, World!")
  val myTest = SQL("select * from employees").as(mapping *)
  myTest.take(1)

}

But get this error:
Solution.scala:6: error: not found: value SQL
  val myTest = SQL("select * from employees").as(mapping *)
               ^
Solution.scala:6: error: not found: value mapping
  val myTest = SQL("select * from employees").as(mapping *)

A:

I'm the guy that makes CoderPad. Currently, you can't connect to MySQL databases in other language environments. That's something we want to do eventually, though.

A:

You'll need to connecto to your database just as you would do that in Java
They should provide you the database information to connect, so you need to do the following steps (writing from memory, sorry is something is missing)
import the required classes:
import java.sql.DriverManager
import java.sql.Connection

Then define the properties to connect:
val driver = "com.mysql.jdbc.Driver"
val url = "jdbc:mysql://whateverServer/whateverDatabase"
val username = "user"
val password = "password"

Create the driver and then create the connection:
Class.forName(driver)
val connection = DriverManager.getConnection(url, username, password)

Then the statement and then run the query itself:
val statement = connection.createStatement()
val resultSet = statement.executeQuery("select * from employees")


Draggable Elements with RxJS

I’ve written previously about making DOM elements draggable using a combination of mouse and touch events. Recently I discovered a more elegant way to achieve this using RxJS and Hammer.

Tools

Hammer JS needs no introduction. It is the go to library for supporting touch gestures. Plus it provides an abstraction over the browser events allowing us to handle mouse and touch at the same time.

RxJS is a reactive programming library for JavaScript. We will use it to convert events into an observable stream and for animations.

I’ve been using RxJS for a couple of years now. Mostly for state management with Angular and with redux-observable. I love working with observables. It allows me to write succinct and declarative code.

A few months ago David Khourshid introduced me to his library RxCSS and to the idea of using observables to create reactive animations. Reactive programming makes it really easy to convert events into data and drive animations. This pushed me to learn more about observables and discover lots of new patterns. In this post I am going to share one of those patterns.

⚠ I am going to assume a basic understanding of RxJS. If you are new to RxJS then I would highly recommend reading David’s animated intro to RxJS first.

Drag Gesture

The drag gesture can be broken down into three stages: start, move & end. On start we grab the current location of the element. The move event provides the delta which we can use to move the element. Lastly, the end event provides us with a hook to do any kind of cleanup once the gesture has ended. Hammer’s Pan Recognizer provides us with panstart, panmove & panend events which work perfectly for the drag gesture.

Events to Observable

We start by creating a Hammer manager and configure it to handle pan in all directions. Rx.Observable.fromEvent allows us to convert events into an observable sequence. This one observable stream – pan$ – will allow us to subscribe to events for pan-start, pan-move and pan-end.

Composing the Drag Observable

For the drag gesture we want to create an observable stream such that it emits values from the the pan-move event once the pan-start event has been triggered and then stops emitting those values once the pan-end event is triggered.

drag$panStart$panMove$panEnd$⬇🔁🔁🔁🔁🔁🔁🔁🔁🔁⬆ Visualization of the drag observables. Generated using rxviz.com

The filter operator allows us to filter values based on a provided condition. We can use this to target specific events. For example, pan$.filter(e => e.type === 'panstart') to subscribe only to pan-start events. Then to generate the drag$ observable we then need to combine panstart$, panmove$ & panend$ in the following pattern:

Let’s break this down step by step. panstart$ is the observable that is driving the whole thing. When it emits the first value it switches to the panmove$ observable. This switching is done using the switchMap operator. The panmove$ observable then starts emitting the location values. We can tell it to stop when panend$ emits a value by chaining on the takeUntil operator. Therefore, all subscribers to drag$ only ever receive location values. You can see a simulated visualization of this setup here.

Now that we understand the basic structure we can flush out the details. The panmove event only provides delta values. To calculate the absolute position we need to start by getting the initial location. In this example I am getting that information from the element itself. To provide a cleanup hook we can subscribe to the move$ observable and handle it via the onComplete callback.

// Generates the drag$ observableconstdrag=({element,pan$})=>{constpanStart$=pan$.filter(e=>e.type==='panstart');constpanMove$=pan$.filter(e=>e.type==='panmove');constpanEnd$=pan$.filter(e=>e.type==='panend');panstart$.switchMap(()=>{// Get the starting point on pan-startconststart={x:+element.getAttribute('cx'),y:+element.getAttribute('cy'),};// Create observable to handle pan-move and stop on pan-endconstmove$=panmove$.map(pmEvent=>({x:start.x+pmEvent.deltaX,y:start.y+pmEvent.deltaY,})).takeUntil(panend$);// We can subscribe to move$ and handle cleanup in the onComplete callbackmove$.subscribe(null,null,()=>{/* Handle cleanup when pan ends */});returnmove$;});};

The pattern I shared above is based on the dragndrop example from the RxJS documentation.

Scaling to Canvas

Quite often I end up having to limit the element to a parent container. For example, a <circle> that can only be dragged within the <svg> container where the cx and cy values need to be calculated in the viewBox coordinate system.

This is essentially a global to local coordinate transform. With SVG this can get slightly tricky depending on how you want the SVG to scale. I generally prefer preserveAspectRatio="xMidYMid slice". This makes the SVG grow until it entirely covers the container – very similar to background-size: cover.

Smooth Motion

In the example above you’ll notice that the motion is somewhat rigid. The circle is stuck to the pointer and instantly stops wherever the pointer stops. We can make this better by adding smooth motion. This will also provide a bit of momentum to the circle.

For smooth motion I am using the LERP-ing technique. It is described in detail by David Khourshid in the An Animated Intro to RxJS article I mentioned earlier. The gist of it is that instead of using the drag$ observable directly we combine it with an animation timer. This allows us to smooth out the motion by using linear interpolation. However, we still have the possibility to subscribe to drag$ if we want access to the raw location.

Conclusion

You can see the power of RxJS here. We were able to convert events into observable streams. Then we composed those streams to create the drag$ observable. And finally we added the animation layer to smooth out the motion. The code is quite declarative. Each layer that we created is modular and can be easily composed to create complex scenarios – for example see the demo below and the one at the top of the page. Looking for more inspiration? Checkout CodePen for many more examples.


Introduction {#s1}
============

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) characterized by chronic and recurrent inflammation of the colon and rectum mucosa. UC patients are classified according to the inflammatory activity ([@B1]), and current treatment options seek to keep the patient in a state of remission or symptoms improvement ([@B2]). Inactive UC (iUC) correspond to those with normal mucosa, and active UC (aUC) present different degrees of mucosal inflammation classified using the Mayo endoscopic score (MS) ([@B1]). The multifactorial etiology of UC is associated with an abnormal immune response to commensal bacteria combined with individual\'s genetic factors. Hence, the following elements have been involved in the development of the altered inflammatory response in UC: dysbiosis of gut microbiota ([@B3]), the impaired intestinal epithelial barrier function ([@B4]) and a loss of tolerance to blood flow agents ([@B5]). These factors lead to the recruitment of inflammatory cells ([@B6]) causing persistent tissue damage. The UC features are associated with the increment of immunological molecules such as TNFα, IL-13, and damage-associated molecular patterns (DAMPs), or alarmins like Interleukin (IL) 33 ([@B7]--[@B9]). The inflammatory mediator IL-33 is a member of the IL-1 superfamily, interacting with the ST2L receptor and triggering a signaling pathway which induces Th2-type cytokines ([@B10]). Increased IL-33 levels in inflamed intestinal mucosa of aUC patients ([@B11]), released mainly from the intestinal colonic epithelium ([@B12]), have been proposed as an inflammation disease marker and contributing to disease severity ([@B13]).

Additionally, IL-33 induces an anti-inflammatory response mediated by regulatory T cells (Tregs) and type 2 innate lymphoid cells (ILC2) ([@B14], [@B15]), by recruiting and activating M2 macrophages ([@B16]). Functionally, this cytokine could contribute to inflammation resolution by releasing IL-10 from ILC2, initiating the restoration of the epithelial barrier. Importantly, IL-33 is associated with healing processes by enhancing intestinal epithelial cells (IEC) proliferation *in vitro*, and colonic mucosal restoration in a (DSS)-induced mice model of colitis ([@B16], [@B17]). These dual roles make IL-33 an essential molecule in IBD pathology, being especially relevant to the study of molecular mechanisms underlying its expression, and its link to the inflammation stage. Although nuclear transcription factors might control IL-33 in an inflammatory context, other regulators such as microRNAs could adjust its temporal expression at the post-transcriptional level.

MicroRNAs are small non-coding RNAs (\~22 nt) that interact through their "seed sequence" with messenger RNAs (mRNAs), promoting mRNA degradation or blocking translation ([@B18], [@B19]). Post-transcriptional regulation by microRNAs can coordinate temporally gene expression in diverse cell types ([@B20]), impacting on several biological processes such as proliferation, differentiation, and tissue homeostasis ([@B21]). In addition, microRNAs have been associated with the pathogenesis of intestinal diseases such as colon cancer ([@B22]), and are deregulated in the inflammatory environment of intestinal mucosa in UC patients ([@B23]--[@B28]). The effects of microRNAs on immunological factors have been described before ([@B23], [@B29], [@B30]), however, there is no evidence that they have an effect on IL-33 in the UC context.

In this study, we performed gene expression microarray analysis for mRNAs and microRNAs in UC patients to explore their molecular interaction and association. A wide variety of microRNAs showed altered expression, including a microRNA family (miR-378) with an IL-33−3′UTR binding site, as demonstrated by *in silico* analysis. We hypothesize that some of these microRNAs family members have an inhibitory effect on IL-33 expression in intestinal mucosa. To demonstrate this, we analyzed biopsies from UC patients and healthy controls and produced correlation studies. A microRNA (miR-378a-3p) selected from this first analysis, was evaluated for its role on IL-33 expression through gain and loss of function *in vitro* experiments. Lastly, we investigated the microRNA\'s effect on IL-33 in intestinal epithelial cell line (HT-29) under an inflammatory condition. Our results support that IL-33 is regulated by microRNAs from the miR-378 family, and offer a novel mechanism to be used in exploring new therapeutic interventions in UC patients.

Materials and Methods {#s2}
=====================

Human Samples
-------------

Colonoscopic pinch biopsies of inflamed and non-inflamed mucosa from eight active UC patients were used for microarray assays ([Table 1](#T1){ref-type="table"}, left). Colonic biopsies of 24 active UC patients (Mayo score 2 and 3), 10 inactive UC (Mayo score 0 and 1), and six healthy subjects for qPCR assays were added ([Table 1](#T1){ref-type="table"}, center). From the active UC patient cohort, 16 colonoscopic samples were included for the evaluation of IL-33 protein levels by ELISA ([Table 1](#T1){ref-type="table"}, right). Recruitment was conducted by the gastroenterology service of Clínica Las Condes.

######

Clinical characteristics of patients.

                                                      **Microarrays assays**   **qPCR assays**   **ELISA assay**
  --------------------------------------------------- ------------------------ ----------------- ----------------- --------- --------- -------- -- -------- --------
  No. of patients                                     8                        10                24                6         16
  Mayo score                                          MS = 2                   MS = 3            MS = 0            MS = 1    MS = 2    MS = 3      MS = 2   MS = 3
                                                      7                        1                 4                 6         14        10          7        9
  Female, *n* (%)                                     5 (62.5%)                5 (50%)           16 (66%)          5 (42%)   8 (50%)
  Age (y)
      Median                                          34                       46                35                52.5      31.5
      Range                                           18--44                   20--76            24--60            36--70    24--53
  Duration of IBD (y)
      Median                                          3                        10                4                 --        5.5
      Range                                           1--7                     0.6--21           0.2--21                     0.2--21
  Treatments
      5 ASA                                           2                        3                 5                 0         5
      Steroids                                        1                        0                 3                 0         3
      Steroids + 5 ASA                                1                        0                 2                 0         2
      Steroids + Immunosuppressant                    2                        0                 4                 0         4
      Steroids + Sulfasalazine                        0                        1                 2                 0         2
      Sulfasalazine                                   0                        1                 0                 0         0
      5 ASA + immunosuppressant                       1                        3                 0                 0         0
      Methotrexate + 5 ASA                            0                        1                 0                 0         0
  Biologics therapy
      Biologics therapy + 5 ASA + Sulfasalazine       0                        1                 3                 0         0
      Biologics therapy + Immunosuppressant           1                        0                 3                 0         0
      Biologics therapy + 5 ASA                       0                        0                 1                 0         0
      Biologics therapy + immunosuppressant + 5 ASA   0                        0                 1                 0         0

Ethics Statement
----------------

All participants provided informed consent. The study was approved by the Sub-direction of Research, and Local Ethics Committee from Clínica Las Condes (Act accepted the August 8, 2014) and performed according to human experimental guidelines. Clinical investigation was conducted according to Declaration of Helsinki principles with participants identified only by number.

Total RNA and microRNA Enrichment
---------------------------------

Total RNA for microarrays was obtained using Mirvana microRNA Kit (Life Technologies Carlsbad, CA), and RNA integrity was evaluated with the High Sensitivity RNA Analysis Kit (Advanced Analytical Technologies Ankeny, IA). For qPCR analysis, large mRNAs (\>200 nt) from the colonic biopsies of patients were isolated using miRNeasy Kit (Qiagen Germantown, MD), and an enriched fraction of small RNAs was obtained with the Rneasy mini elute clean up kit (Qiagen Germantown, MD).

Microarray Assays
-----------------

MicroRNA and gene expression microarrays of inflamed and non-inflamed mucosa from eight active UC patients was done by using the Affymetrix GeneChipTM Version 4 microRNA arrays following the Affymetrix hybridization protocols (ThermoFisher Scientific Santa Clara, CA). This platform has extended coverage of more than 5,000 mature microRNAs (included in the miRBase 20 release). Starting with 350 ng of total RNA, the Affymetrix FlashTagTMBiotin HSR labeling was used to label RNA according to the manufacturer\'s protocol. On average 13 μg of labeled sample were hybridized for 16 h at 48°C using the Affymetrix Eukaryotic Target Hybridization Controls protocol. Array slides were stained with streptavidin/phycoerythrin utilizing a double-antibody staining procedure and then washed for antibody amplification according to the GeneChip Hybridization, Wash, and Stain Kit was used according to the manual. Arrays were scanned in an Affymetrix Scanner 3000 and data was obtained using the GeneChip® Command Console Software (AGCC; Version 3.2). Gene expression analysis was conducted using Agilent Whole Human Genome 4×44 multiplex format oligo arrays (014850) (Agilent Technologies Santa Clara, CA) that has coverage of more than 40,000 human mRNA transcripts. Fifty nanograms (ng) of total RNA were amplified as directed in the NuGEN Ovation Pico WTA System and 5 μg of amplified cDNA were enzymatically labeled using the Agilent SureTag DNA Labeling Kit. For each sample, 3 μg of Cy3 labeled cDNA were hybridized for 17 h. Slides were washed and then scanned with an Agilent Scanner. Data were obtained using the Agilent Feature Extraction software (v12), using the 1-color defaults for all parameters. The Agilent Feature Extraction Software performed error modeling, adjusting for additive and multiplicative noise. The resulting data of microRNA and gene expression microarrays were processed using OmicSoft Array Studio (Version 9.0) software. Raw data were processed with Partek® Genomic Suite® software, version 6.6 Copyright, 2016 Partek Inc., to generate a Principal Components Analysis and to find gene probes expressed with statistical significance. Ingenuity® Pathway Analysis (IPA®) version 6.5 tool (QIAGEN Inc.) Ingenuity Systems 2 was used to identify functional pathways and top upstream regulators along with their statistical significance. The network relation between microRNA and transcripts figure was generated through the use of IPA®. Gene expression and small RNAs microarrays are linked to GEO accession [GSE133061](GSE133061).

RNA-RNA Interaction Analysis
----------------------------

The prediction of interaction between RNA molecules was using the INTA RNA 2.1.0 and Vienna RNA package 2.1.3 ([@B31]). Minimum Free Energy (MFE) analysis to predict the probability of 3′UTR RNA folding was conducted using the Vienna RNA tool ([@B32]). Identification of target sites for microRNA was conducted using TargetScan 7.2 ([@B33]).

Quantitative Real-Time PCR
--------------------------

Taqman MicroRNA Assay (ThermoFisher Scientific Carlsbad, CA) was used to analyze the expression of miR-378a-3p, miR-378c, and miR-422a and the endogenous control RNU43 at full reaction volume (20 μl) according to the manufacturer\'s instructions. To evaluate the levels of each mRNA, the total cDNA was reverse transcribed from 1 μg of RNA using 1 unit of reverse transcriptase (Agilent Technologies). Quantitative real-time PCR for IL-33, IL-8 AGO1, AGO2, PPARGC1B, and 18s rRNA genes were performed using II Brilliant SybrGreen qPCR Master Mix (Agilent Technologies). Primer sequence for IL-33 Fwd GTGACGGTGTTGATGGTAAGATGT, Rev CACTCCAGGATCAGTCTTGCAT; PPARGC1B Fwd TGTTCAGACAGAACGCCAAG, Rev AAGCCGTACTTCTCGCCTCT; IL-8 Fwd TCTGGACCCCAAGGAAAACT, Rev TTGCATCTGGCAACCCTACA; AGO1 Fwd GGTCCAGCATTTCAAGCCTCAGAT, Rev CACAATGGCTAGCCACTTGATGGA; AGO2 Fwd GGGGCAGGAATAAAGCTATTGCGA, Rev TGCGCGTATTTGCAGAAGCAC; 18s ribosomal RNA (rRNA) Fwd GTGGAGCGATTTGTCTGGTT, Rev CGCTGAGCCAGTCAGTGTAG. The 18s rRNA was used as a reference gene to normalize mRNA levels. Each sample was measured by duplicated with qPCR results analyzed by the ΔΔC~q~ method.

Western Blotting
----------------

Proteins extracted using RIPA Lysis Buffer (ThermoFisher Scientific Carlsbad, CA) supplemented with Complete mini protease inhibitors cocktail (Roche, Mannheim, Germany) and immersed in Laemmli Buffer (Sigma Aldrich Saint Louis, MO) from HT-29 experiments (HT-29: 40 μg, HT-29 transduced cell lines: 30 μg) were loaded in 10% polyacrylamide gels. Protein transference to nitrocellulose membranes was accomplished using a Trans-Blot Turbo Transfer System (Bio Rad Laboratories Inc). Membranes were incubated overnight with Monoclonal IL-33 antibody MAB3625 (R&D Minneapolis, MN) (1:250) and β-actin as load control (1:2,000) (Santa Cruz Biotechnology Dallas, TX). Chemiluminescence was evaluated using ChemistCope equipment and the bands area were quantified with the Image J Software.

ELISA
-----

Protein extracts (100 μl) with RIPA Lysis Buffer (ThermoFisher Scientific Carlsbad, CA) supplemented with protease inhibitors cocktail (Roche, Mannheim, Germany) were used to measure IL-33 concentration from human tissue samples by ELISA (DuoSet, R&D Systems, Minneapolis, MN, USA) according to the manufacturer\'s instructions. Each sample was duplicated and average results were normalized to total protein concentration and expressed as pg (IL-33)/mg (total protein).

Cell Lines and Cultures
-----------------------

HT-29 was kindly provided by Dr. Julio Tapia (Cell Transformation Laboratory, Faculty of Medicine, University of Chile). HT-29 and HEK 293 cells were cultured in high glucose DMEM (Corning Inc., Tewksbury, MA) with 10% Fetal Bovine Serum (FBS, Hyclone Pittsburgh, PA), Penicillin/Streptomycin (1%). HEK 293T cells were cultured in MEM medium (Corning Inc., Tewksbury, MA) 10% SFB and Penicillin/Streptomycin (1%).

Lentivirus Preparation
----------------------

For stable over-expression of miR-378a-3p in HT-29 cells, we used the primiR-378 sequence (300 pb flanking the miR-378a stemloop:MI0000786) inserted in the SalI site of vector pGPG-Lenti-CMV-GFP-puro vector previously validated for microRNA expression ([@B34]). The cloned vector, pGPG-Lenti-CMV-PrimiR-378 plasmid, or negative vector pGPG-Lenti-CMV-GFP-puro were co-transfected with the helper plasmids (pPAX2 and pVSV-G) in HEK 293T cells. Supernatants with lentiviral particles were recovered 48 h post-transfection and the cell debris removed by centrifugation. Stable miR-378a-3p inhibition was achieved using Tud Decoy technology. LentiMiR378a-3pTuD and negative scrambled control \#1 were purchased (MISSION® Lenti microRNA Inhibitors, Sigma Aldrich, St. Louis, MO). PrimiR-378, control primir-378, MiR-378a-3p (TuD) Inhibitor or TuD Inhibitor control lentiviral particles were added to HT-29 cells previously treated with Polybrene 6 μg/mL (Sigma-Aldrich St. Louis, MO) and incubated for 72 h at 37°C with 5% CO~2~ environment on 24-well culture plates. Then, Puromycin (2 μg/mL) selection was performed for 2 weeks.

Gen Reporter Assays
-------------------

The IL-33 3′UTR wild type binding sequence (42 nt) was cloned into a β-galactosidase pmiRCHECK reporter vector into the PmeI restriction site (IL-33 WT). A control plasmid with interspersed substitutions in the seed sequence was cloned into the same vector (IL-33 MUT). A β-gal vector containing 3 canonic binding sites sequence for miR-378a-3p was used as a positive control (pmirCHECK 3′UTR XXX MiR-378a-3p BS). MicroRNA sensor vectors and positive control are tools previously validated in the Gene Therapy Center (UMASS) and published for microRNA effect evaluation in HEK 293 cells ([@B34], [@B35]). HEK293 cells (2.5 × 10^4^ cells) were seed in 24 wells plates in 500 ul of DMEM medium with SFB (10%). After 24 h the transfection with Mimics Negative control \#1 (ThermoFisher Scientific Carlsbad, CA) 10 nM, Mimic 5 nM plus Mimic negative control 5 nM, and Mimics 10 nM, and co-transfected with 200 ng of β-gal vector using Lipofectamine 2000 (ThermoFisher Scientific Carlsbad, CA) according to manufacturer instructions were accomplished. β-Gal levels (Applied Biosystems, Bedford, MA, USA) were measured 24 h post-transfection and normalized to Luciferase expression (F-Luc) (Promega Madison, WI) in four duplicate independent experiments according to manufacturer instructions.

Cell Viability Assay
--------------------

HT-29 over-expressing or inhibiting of the miR-378a-3p and their respective cell line controls were seeded (3 × 10^5^ cells) in 6-wells plates with DMEM, FBS (10%) and Penicillin/Streptomycin (1%). Afterward, cells were trypsinized at 6, 12, 24, 48, and 72 h and the number of viable cells (unstained) were counted by trypan blue stain (Thermofisher Scientific Carlsbad, CA) using a Neubauer Camera. Additionally, viable cells were determined by flow cytometry (FACSCanto Becton Dickinson Biosciences, San Jose CA, USA) using propidium iodide (PI) stain (10 μg/mL) (ThermoFisher Carlsbad, CA, USA) at 24, 48, and 72 h in four duplicate independent experiments.

Inflammatory Assay in Intestinal Epithelial Cells
-------------------------------------------------

HT-29 1 × 10^6^ cells were incubated in DMEM with 1% FBS overnight and then treated with human recombinant TNFα (R&D Systems, Minneapolis, MN USA) at 10 ng/mL for 3, 6, and 24 h for microRNA and mRNA evaluation, and 12, 24, and 48 h for protein measurement. Four duplicate independent experiments were performed.

Statistical Analysis
--------------------

Microarrays results were analyzed using two-way ANOVA to determine significant differences between genes and microRNAs probes. A cutoff of 1.5-fold change, a *P* ≤ 0.05 (microRNAs) and ≤ 0.01 (mRNAs) were used to select the gene probes for further analysis. Statistical analysis for qPCR, ELISA, chemiluminescence and luminescence assays were performed with ANOVA and 2-tailed Student test (GraphPad 7.0) unpaired or paired according to sample characteristics. Results are expressed as Mean values ± standard error (SEM). Bonferroni and Tukey post-tests were used for ANOVA analysis. For correlation analysis, we used Pearson correlation. *P* ≤ 0.05 was considered significant.

Results {#s3}
=======

Expression of microRNAs and mRNAs Associated With Inflammatory and Metabolic Pathways Is Altered in Inflamed Tissue
-------------------------------------------------------------------------------------------------------------------

To have an overview of transcripts and microRNAs involved in inflammatory pathways, particularly related to increased IL-33 levels in aUC ([@B11]), we determined their differential expression in inflamed vs. non-inflamed intestinal mucosa (from colon pinch biopsies), by microarray assays. Clinical characteristics of each patient are described in [Table 1](#T1){ref-type="table"}. To provide an overview of variance in samples given by the inflammatory mucosa context, we performed a Principal Component Analysis (PCA) of microRNAs and mRNAs arrays. This analysis indicates that inflammation condition impact on molecules expression as seen in the main component (PC \#1), explaining 10.3 and 22.2% of total variances (27.5; 45.3%), respectively, for the microRNAs and mRNAs arrays ([Figures 1A,B](#F1){ref-type="fig"}, respectively). To visualize the impact of inflammation on microRNA and mRNA expression, we performed a Heat map analysis ([Figures 1C,D](#F1){ref-type="fig"}, respectively). A total of 89 mature microRNAs and 3,854 gene expression probes were regulated by the inflammatory context (≥1.5-fold). For microRNA, there were a similar number of up-regulated ([@B36]) and down-regulated ([@B37]) probes modulated by inflammation condition. Additionally, there were slightly more up-regulated transcripts (2,120) than those down-regulated (1,734) by inflammation in gene expression microarray.

![Inflammation context impact on microarrays analysis. **(A)** Total principal component analysis (PCA) and the main component PC \#1, corresponding to variation by inflammation, performed in inflamed and non-inflamed colon biopsies from aUC patients for microRNA microarray and **(B)** gene expression microarray. **(C)** Cluster analysis for microRNA microarray and **(D)** gene expression microarray. Hierarchical clustering was performed based on the main 30 up and downregulated selected gene probes.](fimmu-10-02449-g0001){#F1}

To understand inflammation impact on differentially expressed miRNA and transcript expression and signaling pathways, we used the Ingenuity Pathway Analysis (IPA) software. Mitochondrial dysfunction, adhesion of granulocytes and diapedesis were the most commonly affected pathways by inflammation ([Table 2](#T2){ref-type="table"}). The tumor necrosis factor (TNF) was the upstream regulator molecule mostly related to altered mRNAs expressed in inflamed mucosa. Additionally, differentially expressed genes were associated with cancer, gastrointestinal, immunological diseases, and cellular processes such as cell movement, growth, and proliferation ([Table 2](#T2){ref-type="table"}).

######

Analysis of functional groups from gene expression microarray by IPA.

        **Top canonical pathways**            **Top upstream regulators**   **Top molecular and cellular functions**
  ----- ------------------------------------- ----------------------------- ------------------------------------------
  1\.   Mitochondrial dysfunction             TNF                           Cellular movement
  2\.   Granulocyte adhesion and diapedesis   LPS                           Cellular growth and proliferation
  3\.   Oxidative phosphorylation             β-estradiol                   Cellular development
  4\.   Antigen presentation pathway          TGFβ1                         Cell-to-cell signaling and interaction
  5\.   Role of tissue factor in cancer       IFNγ                          Cell Death and survival

Subsequently, we analyzed strongly deregulated transcript fold-change such as IL-33 to evaluate possible relationships with the inflammatory environment. We observed large up-regulation of MMP3 (59.5 times), CXCL8 (40.1 times) ([Table 3](#T3){ref-type="table"}), along with a high IL-33 mRNA fold-change (3.8 times). Alternatively, most down-regulated genes were HMGCS2 (−19 times) and SCL26A2 (−14.5 times). Regarding microRNA expression, we found a robust up-regulation of miRNAs related to immune homeostasis such as miR-hsa-miR-223-3p and miR-708-5p ([Table 3](#T3){ref-type="table"}), suggesting that inflammation is an important feature impacting in microRNA profile. In addition, eight members of the microRNAs miR-378 family were among the most down-regulated genes ([Table 3](#T3){ref-type="table"}). To find predicted mRNA targets for this microRNA family, we performed an interaction network using IPA software, which uses data derived from TargetScan, TarBase miRecords and Ingenuity® Knowledge Base. This analysis shows a direct relationship between the miR-378 family and the IL-33 transcript ([Supplementary Figure 1A](#SM1){ref-type="supplementary-material"}). This microRNA family shares the same seed sequence and, thus might interact with IL-33 mRNA. TargetScan software also predicted the interaction between these molecules and identified that the type of pairing between miR-378 family seed sequence within IL-33 mRNA is through an 8mer in the 3′UTR ([Supplementary Figure 1B](#SM1){ref-type="supplementary-material"}), exhibiting an effective canonical site type ([@B33]). Furthermore, we analyzed the 3′UTR IL-33 sequence based in MFE to evaluate the folding interactions (Vienna RNA software). Accordingly, the location of target sequence in 3′UTR IL-33 has a moderate probability in presenting an unpaired conformation ([Supplementary Figure 1C](#SM1){ref-type="supplementary-material"}), suggesting that the IL-33 binding site is accessible for microRNA interaction. Additionally, to predict an interaction between the miR-378 family and IL-33 3′UTR, we evaluated the binding strength of both molecules by interaction energy analysis (IntaRNA-RNA-RNA Interaction software) ([Table 4](#T4){ref-type="table"}). The lowest interaction energy was found for miR-422a (−13.6 kcal/mol) and miR-378c (−9.6 kcal/mol), energies acceptable for human microRNAs interactions ([@B38]). In conjunction, these analyses suggest that miR378 family members interact with IL-33 3′UTR. Based on these findings and background information involving these microRNAs and intestinal mucosa inflammation, we selected miR-378a-3p \[down-regulated in inflamed mucosa ([@B23])\], miR422a and miR-378c for further correlation analysis in a cohort of patients with aUC, inactive UC (iUC) and healthy controls.

######

Top microRNAs and mRNAs deregulated in inflamed mucosa.

  **Induced microRNAs ID**   **Fold change**   **Repressed microRNAs ID**                         **Fold change**   **Induced mRNAs ID**   **Fold change**   **Repressed mRNAs ID**   **Fold change**
  -------------------------- ----------------- -------------------------------------------------- ----------------- ---------------------- ----------------- ------------------------ -----------------
  hsa-miR-223-3p             5.3               hsa-miR-147b                                       −6.6              MMP3                   59.5              HMGCS2                   −19
  hsa-miR-708-5p             4.7               hsa-miR-196b-3p                                    −6.4              CHRDL2                 50.5              SLC26A2                  −14.5
  hsa-miR-29b-1-5p           3.0               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378e      −3.9              PROK2                  50.5              UGT2A3                   −13.8
  hsa-miR-138-5p             2.9               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-422a      −3.9              SLC6A14                45.1              PITX2                    −12.5
  hsa-miR-23a-5p             2.8               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378g      −3.8              CXCL8                  40.1              SLC51A                   −12.4
  hsa-miR-486-3p             2.8               hsa-miR-196b-5p                                    −3.6              MMP7                   38.3              BMP3                     −11.8
  hsa-miR-27a-5p             2.8               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378d      −3.5              DUOX2                  35.4              B4GALNT2                 −10.9
  hsa-miR-766-3p             2.8               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378a-3p   −3.4              SLC6A14                33.3              TIGD6                    −10
  hsa-miR-155-5p             2.5               hsa-miR-378a-5p                                    −3.4              PI3                    32.3              DPP10                    −9.9
  hsa-miR-4538               2.5               hsa-miR-192-3p                                     −3.1              DUOX2                  30.9              SAG                      −9.8
  hsa-miR-503-5p             2.4               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378c      −3.1              SAA1                   27.3              CA1                      −9.7
  hsa-miR-4448               2.3               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378i      −3.1              CHI3L1                 25.0              UGT1A8                   −9.4
  hsa-miR-548ac              2.3               [^\*^](#TN1){ref-type="table-fn"}hsa-miR-378f      −3.0              CYR61                  24.4              PCK1                     −9.1
  hsa-miR-4736               2.2               hsa-miR-141-3p                                     −2.8              SERPINB5               23.0              MST1L                    −8.7
  hsa-miR-193b-5p            2.1               hsa-miR-1296-5p                                    −2.7              INHBA                  22.9              DPP10-AS1                −8.6

*miR-378 family members*.

######

Interaction energy analysis between miR-378 family and IL-33 3′UTR using INTA RNA software.

  **MicroRNA**   **Energy: kcal/mol**
  -------------- ----------------------
  miR-422a       −13.61
  miR-378c       −9.61
  miR-378i       −9.46
  miR-378f       −8.67
  miR-378d       −8.62
  miR-378a-3p    −8.47
  miR-378g       −8.34
  miR-378e       −7.14

MiR-378a-3p Correlates Inversely With IL-33 Expression in Intestinal Mucosa of UC Patients and Is Modulated by Anti-TNF Therapy
-------------------------------------------------------------------------------------------------------------------------------

To corroborate levels of miR-378a-3p, miR-378c, miR422a, and IL-33 observed by microarrays, we enrolled aUC and inactive UC (iUC) patients together with a healthy subject group for their evaluation by qPCR. Analysis showed that aUC patients had decreased miR-378a-3p levels compared to healthy subjects (HS) (*P* = 0.018) and with iUC (*P* = 0.0006) ([Figure 2A](#F2){ref-type="fig"}). When we evaluated the miR-378a-3p levels according to MS, we found lower levels of this microRNA mainly in patients with MS = 2, 3 compared to MS = 0 (*P* = 0.0078, *P* = 0.002, respectively) ([Figure 2B](#F2){ref-type="fig"}), and a negative correlation with the MS (*r* = −0.50, *P* = 0.0080) ([Figure 2C](#F2){ref-type="fig"}). IL-33 mRNA was found increased in aUC and iUC patients compared to HS (*P* = 0.023, *P* = 0.0075, respectively) ([Figure 2D](#F2){ref-type="fig"}). Also, protein IL-33 levels were increased in intestinal mucosa lysate of aUC vs. HS or iUC (*P* = 0.046, *P* = 0.0034, respectively) ([Figure 3A](#F3){ref-type="fig"}). Analysis showed the highest IL-33 protein content was in patients with MS = 2 and MS = 3 compared to MS = 1 (*P* = 0.022, *P* = 0.0048, respectively) ([Figure 3B](#F3){ref-type="fig"}) along with direct correlation between them (*r* = 0.50, *P* = 0.0083) ([Figure 3C](#F3){ref-type="fig"}). Moreover, miR-378a-3p and IL-33 (mRNA and protein) levels were found inversely correlated (*r* = −0.53, *P* = 0.0018; *r* = −0.35, *P* = 0.037, respectively) ([Figures 3D,E](#F3){ref-type="fig"}).

![MiR-378a-3p levels are decreased in intestinal mucosa from active UC patients. **(A)** Relative expression from healthy subjects (HS) ([@B6]), inactive (iUC) ([@B10]), and aUC ([@B24]) patients of miR-378a-3p by qPCR, **(B)** miR-378a-3p levels according Mayo Score (MS), and **(C)** correlation analysis between miR-378a-3p and MS, and **(D)** IL-33 mRNA by qPCR. Mann Whitney test and Pearson Correlation were performed. \**P* = \< *0.05*, \*\**P* = \< *0.01*, \*\*\**P* = \< *0.01*.](fimmu-10-02449-g0002){#F2}

![MiR-378a-3p levels are inversely correlated with IL-33 content in intestinal mucosa from UC patients and healthy subjects. **(A)** IL-33 protein levels by ELISA of HS = 6, iUC = 10 and aUC = 16, **(B)** according to MS, and **(C)** correlation analysis between IL-33 and MS. **(D)** Correlation analysis between miR-378a-3p and IL-33 mRNA, and **(E)** with IL-33 protein. Mann Whitney test and Pearson Correlation were performed. \**P* = \< *0.05*, \*\**P* = \< *0.01*.](fimmu-10-02449-g0003){#F3}

Regarding other microRNA expression in colonic biopsies, we determined a reduction of miR422a levels in aUC compared to iUC patients (*P* = 0.0077) ([Supplementary Figure 2A](#SM2){ref-type="supplementary-material"}), with no differences between UC patients and HS. For miR-378c, there were no differences between HS, iUC and UC samples ([Supplementary Figure 2B](#SM2){ref-type="supplementary-material"}). Levels of miR-422a correlated inversely with IL-33 protein (*r* = −0.36, *P* = 0.037) ([Supplementary Figure 3A](#SM3){ref-type="supplementary-material"}), but not with IL-33 mRNA levels ([Supplementary Figure 3B](#SM3){ref-type="supplementary-material"}), and miR-378c were no correlated with IL-33 expression either ([Supplementary Figures 3C,D](#SM3){ref-type="supplementary-material"}). These results suggest that miR-378a-3p and miR-422a might be potential regulators of IL-33 expression.

TNFα is a pro-inflammatory molecule that is increased in inflamed UC intestinal mucosa patients ([@B39]), regulating different microRNAs ([@B40]). Thus, the possible effect of TNFα on expression of the three microRNAs included in this study was determined in inflamed mucosa of patients (MS = 2--3) receiving anti-TNFα therapy (*n* = 8) compared with aUC with other treatments (*n* = 16). We found increased levels of miR-378a-3p and miR-378c (*P* = 0.036, *P* = 0.01, respectively) ([Supplementary Figures 4A,B](#SM4){ref-type="supplementary-material"}, respectively), along with decreased IL-33 mRNA levels (*P* = 0.031) ([Supplementary Figure 4C](#SM4){ref-type="supplementary-material"}) in inflamed mucosa of patients with anti-TNFα therapy. MiR-422a levels in mucosa patients with this treatment were not altered ([Supplementary Figure 4D](#SM4){ref-type="supplementary-material"}). These findings suggest an inhibitory effect of TNFα on miR-378a-3p and miR-378c levels.

We show that miR-378a-3p expression is inversely correlated with IL-33 mRNA and protein; IL-33 mRNA is a predicted target of miR-378a-3p and this microRNA is potentially regulated by TNFα. Given these reasons we selected miR-378a-3p to validate its effect on IL-33 through an *in vitro* approach and to further study their modulation by TNFα.

IL-33 Target Sequence Is Inhibited by miR-378a-3p
-------------------------------------------------

To determine the effect of miR-378a-3p on IL-33 expression, we used a β-Galactosidase (β-Gal) gene sensor vector containing the binding site (BS) for miR-378a-3p in the wild type IL-33 3′UTR (WT IL-33), or a BS mutant vector (MUT IL-33). The annealing between the WT and MUT BS sequences with miR-378a-3p is shown in a diagram in [Figure 4A](#F4){ref-type="fig"}. A positive control that contains 3 consecutive canonic target sequences for miR-378a-3p was used (pmirCHECK 3′UTR XXX MiR-378a-3p BS). The β-Gal activity was reduced in HEK-293 cells transfected with WT IL-33 sensor vector and Mimic 5 or 10 nM compared to Mimic 0 nM (*P* \< 0.0001). This reduction was dependent on the miR-378a-3p mimic concentration used ([Figure 4B](#F4){ref-type="fig"}) (*P* \< 0.05). β-Gal activity decreased in cells transfected with the positive control as well (*P* \< 0.0001), while the mimic molecule had no effect on β-Gal activity of MUT IL-33 vector. This outcome suggests that miR-378a-3p exerts an inhibitory effect on the target sequence present in the 3′UTR of IL-33. Also, we generated stable HT-29 cell lines that over-express (PrimiR-378 cells) or inhibit the miR-378a-3p (Inhibitor cells) along with their respective control cell lines (CTR Primir-378, CTR Inhibitor). The basal levels of miR-378a-3p were evaluated to determine the effectiveness of the transduction. Thus, miR-378a-3p levels increased on average 75-fold in PrimiR-378 cells and decreased 1.3-fold (30% repression) in the Inhibitor cells, relative to each control cell line ([Figure 5A](#F5){ref-type="fig"}) (*P* = 0.011, *P* = 0.0037, respectively). The levels of IL-33 mRNA decreased 2.1-fold in HT-29 PrimiR-378 cells and was induced 2-fold in HT-29 Inhibitor cells ([Figure 5B](#F5){ref-type="fig"}) (*P* = 0.045, *P* = 0.048, respectively. These results strongly suggest that miR-378-3p regulates IL-33 mRNA post-transcriptionally, possibly by promoting its degradation. Furthermore, IL-33 protein levels decreased in Pri-378 cells and increased in inhibitor cells compared with their respective controls ([Figures 5C,D](#F5){ref-type="fig"}) (*P* = 0.0033, *P* = 0.0004, respectively).

![Identification of putative miR-378a-3p binding site within the IL-33 3′UTR. **(A)** Diagram of 3′UTR IL-33 target sequence into Lac Z reporter gene to evaluate microRNA effect, **(B)** miR-378a-3p over-expression reduces β-Gal activity of a reporter vector harboring IL-33 wild-type target sequence in HEK 293T cells. Mimic 0 nM (mimic negative control 10 nM), Mimic miR-378a-3p 5nM + Mimic negative control 5 nM, or Mimic 10 nM were co-transfected with sensor vectors. β-Gal F-Luc ratios of Mimic miR-378a-3p treatments were normalized to Mimic 0 nM of each sensor vectors. Four experiments by duplicated were analyzed using Two-way ANOVA with Tukey\'s multiple comparisons test. \**P* = \< *0.05*, \*\*\*\**P* = \< *0.0001*.](fimmu-10-02449-g0004){#F4}

![Over-expression and inhibition of miR-378a-3p modulate IL-33 expression. Stable expression of miR-378a-3p (Primir-378) or inhibition of miR-378a-3p (Inhibitor), and their respective controls (CTR PrimiR-378a, CTR Inhibitor) were obtained with Lentiviral vectors in HT-29 cells. **(A)** MiR-378a-3p Log~2~ fold change, and **(B)** IL-33 mRNA fold change relative to CTR cell lines by qPCR, **(C)** IL-33 protein and β-actin by Western Blotting (WB) and bands quantification by densitometry analysis (Fiji Software) of Control Primir-378 and Primir-378 cell lines, and **(D)** Control Inhibitor and Inhibitor cell lines. Four experiments by duplicated were performed. Each cell line was compared with their respective control using Paired *t*-test. \**P* = \< *0.05*, \*\**P* = \< *0.01*, \*\*\**P* = \< *0.001*.](fimmu-10-02449-g0005){#F5}

High IL-33 expression has been associated with increased viability ([@B41]), thus we evaluated viable PrimiR 378 and Inhibitor stable cells by the trypan blue exclusion test. Cells over-expressing miR-378a-3p (presenting low IL-33 expression) diminish the number of viable cells (*P* = \< 0.01; *P* = \< 0.001) ([Figure 6A](#F6){ref-type="fig"}) compared to control cells, and conversely miR-378a-3p inhibition increased it (*P* = \< 0.05; *P* = \< 0.001) ([Figure 6B](#F6){ref-type="fig"}) at 48 and 72 h. Additionally, we found decreased viability in cells over-expressing miR-378a-3p (*P* = \< 0.0001) ([Figure 6C](#F6){ref-type="fig"}), with an increment of viability in miR-378a-3p Inhibitor cells (*P* = \< 0.05) ([Figure 6D](#F6){ref-type="fig"}) at 24 h according to propidium iodide stain. In conjunction, these results show the inhibitory effect of miR-378a-3p on IL-33 expression on cell viability.

![Over-expression and inhibition of miR-378a-3p levels alter viability of colonocytes cell line. **(A)** IEC cells over-expressing the primiR-378, and **(B)** inhibiting the miR-378a-3p and their respective control cell lines (CTR PrimiR-378, CTR Inhibitor) were cultured by 6, 12, 24, 48, and 72 h. The number of viable cells were counted using trypan blue stain. The % of viability was achieved with PI stain by flow cytometry in **(C)** IEC cells over-expressing the primiR-378 and **(D)** inhibiting the miR-378a-3p cultured by 24, 48, and 72 h. Four experiments by duplicated were analyzed using Two-way ANOVA with Bonferroni multiple comparisons test were performed. \**P* = \< *0.05*, \*\**P* = \< *0.01*. \*\*\**P* = \< *0.001*, \*\*\*\**P* = \< *0.0001*.](fimmu-10-02449-g0006){#F6}

TNFα Reduces the miR-378a-3p Levels in HT-29 Cells
--------------------------------------------------

Due to higher miR-378a-3p levels in inflamed aUC mucosa patients receiving anti-TNFα therapy, we conducted experiments replicating the inflamed condition in a colonocyte *in vitro* model (HT-29 cells) exposed to TNFα. Levels of miR-378a-3p decreased with TNFα stimulation at 3 h ([Figure 7A](#F7){ref-type="fig"}) whilst simultaneously IL-33 mRNA levels increased ([Figure 7B](#F7){ref-type="fig"}) (*P* = \< 0.05). Additionally, IL-33 protein increased at 24 h post-stimulus ([Figures 7C,D](#F7){ref-type="fig"}) (*P* = \< 0.05). These results showed an inverse correlation between miR-378a-3p and IL-33 levels (*Pearson* correlation *r* = −0.67, *P* = 0.047). Furthermore, we measured the levels of the miR-378a-3p hosted gene, the PPARGC1B-mRNA, and found it decreased at 3 and 6 h after TNFα stimulus ([Figure 7E](#F7){ref-type="fig"}) (*P* = \< 0.05, *P* = \< 0.001, respectively). The miR-378a-3p expression correlated directly with PPARGC1B mRNA levels (*Pearson* correlation *r* = 0.7, *P* = 0.04). Increased IL-8 mRNA levels confirmed the effect of TNFα on the cells, which was observed after 3 h ([Figure 7F](#F7){ref-type="fig"}) (*P* = \< 0.05). The mRNA levels of genes involved in microRNAs biogenesis, AGO1 and AGO2, were not affected by TNFα, suggesting that microRNAs expression changes are mainly related to inflammation ([Figures 7G,H](#F7){ref-type="fig"}). This implies that TNFα is a regulator of miR-378a-3p expression through its host gene (PPARGC1B) in IEC.

![TNFα decreases miR-378a-3p and increases IL-33 expression in colonocytes. HT-29 cell line was stimulated with 10 ng/mL human recombinant TNFα (hr-TNFα) for 3, 6, and 24 h. Fold change relative to non-stimulated control of **(A)** MiR-378a-3p and **(B)** IL-33 mRNA. **(C)** IL-33 protein was measured in HT-29 cells stimulated with hr-TNFα 10 ng/mL 12, 24, and 48 h by WB, **(D)** Band quantification of IL-33 protein normalized to β-actin. **(E)** Fold change relative to non-stimulated control of PPARGC1B mRNA and **(F)** IL-8 mRNA levels (measured as control of TNFα stimulus). **(G)** AGO1 and **(H)** AGO2 mRNA levels were assessed as control of miRNA-biogenesis machinery. Four experiments by duplicated were analyzed using Two-way ANOVA with Bonferroni post-test. \**P* \< *0.05*, \*\**P* = \< *0.01*.](fimmu-10-02449-g0007){#F7}

Discussion {#s4}
==========

In the last decade, the role of microRNAs in the intestinal homeostasis and IBD pathophysiology has been related mainly with the impairment of the epithelium barrier and inflammatory response ([@B36]). Accordingly, our data shows an altered microRNA profile expression related to the inflammatory context. In this work, we show deregulation of a set of microRNAs (miR-223-3p and miR-147b) ([Table 3](#T3){ref-type="table"}), whose have been founded increased in intestinal mucosa of IBD patients and were associated with macrophage polarization to an anti-inflammatory profile in a murine model ([@B42], [@B43]). Accordingly, a set of genes in our gene expression microarray were associated with pathways, molecular and cellular functions reflecting the UC inflammatory process. Delving into the microRNA profile, we found eight microRNAs from the miR-378 family, whose levels were decreased in inflamed vs. non-inflamed mucosa. Interestingly, these microRNAs, sharing the same target sequence, are hosted in genes that are located in different coding and non-coding genome regions, and this microRNAs redundancy might ensure effective regulation of their target genes. Hence, the down-regulation of the whole miR-378 family could represent a more efficient mechanism for IL-33 control, which signifies a possible additive effect. Moreover, each microRNA from this family is coded in different genome regions that could implicate distinctive regulation pathways for each one. This verifies the complex microRNA networking that might impact on IL-33 expression in a temporal way during inflammation. For our study, we selected three members of the miR-378 family (miR-378a-3p, miR-422a, and miR-378c) to evaluate their expression in biopsies samples. In particular, we observed decreased levels of miR-422a, and miR-378a-3p in inflamed biopsies compared to samples from inactive patients. Diminished levels of both microRNAs have been measured in gastric and colorectal tumor tissue, together with their deregulating involvement in metabolic pathways related to lipid metabolism ([@B44]--[@B46]). Thus, microRNA levels might be reflecting the metabolic shift that occurs in inflamed intestinal mucosa, described previously in ulcerative colitis, as associated mainly to microbiota deregulation with upper lipid metabolism and lower glucose uptake ([@B47]).

Our studies focused on the miR-378a-3p, whose target genes have been examined in processes of differentiation and proliferation ([@B48], [@B49]). Our results showed an inverse correlation of miR-378a-3p with IL-33 levels in mucosa of UC patients and healthy subjects that could evidence a mechanistic relationship between these molecules. Also, the levels of miR-378a-3p and IL-33 determined in this research confirm previous reports in UC ([@B11], [@B23]). At present, other examples of microRNAs regulating IL-33 include miR-487b, described as a negative regulator in murine macrophages, which decreases co-stimulatory molecule production and therefore the inflammatory response ([@B37]). Due to the cell sample complexity, IL-33 production by macrophages was not possible to observe, although this does not rule out that it can be regulated by miR-487b. Recently, another example was miR-200b and miR-200c which were described as post-transcriptional regulators of IL-33 in allergic airway inflammation disease ([@B50]), and were confirmed by our microarray data analysis showing decreased levels of both microRNAs in inflamed mucosa (−1.29 and −1.35, respectively) and we cannot dismiss their effect on IL-33 in the intestinal mucosa of UC patients. In regard to the indirect regulation of IL-33 by microRNA, miR-29a has also been described as a direct negative regulator of sST2 mRNA in a murine model of tendinopathy ([@B51]), therefore, miR-29a inhibits sST2 production affecting the activation of IL-33/ST2 axis. All these antecedents and results show the diverse microRNAs networks that might disturb IL-33/ST2 axis signaling.

MiR-378a-3p is induced in human primary adipocytes stimulated with TNFα or IL-6, however, there is no relating evidence between inflammatory mediators and miR-378a-3p in intestinal mucosa cells. Also, it still remains unclear in UC how IL-33 production is regulated by pro-inflammatory soluble factors such as TNFα, although it is understood that infliximab (anti-TNFα) decreases circulating IL-33 levels in UC patients ([@B52]), suggesting that its modulation involves TNFα signaling. We found increased miR-378a-3p levels in patients receiving anti-TNFα therapy, with diminished levels in IEC cells under TNFα ([@B52]). Our results suggest that modulation of miR-378a-3p by TNFα operates as an intermediary of IL-33 induction. A model of IL-33 regulation by miR-378a-3p in an inflammatory or healthy environment is represented in [Figure 8](#F8){ref-type="fig"}. Our observation in IEC cells does not dismiss that this mechanism occurs in other IL-33 sources such as endothelial cells, where miR-378a-3p has been described as being one of the most expressed microRNAs ([@B53]) and is a potential IL-33 regulator in those cells. In addition, we found that miR-378c is reduced in mucosa of UC patients by microarrays and increased in patients under anti-TNFα therapy. MiR-378c down-regulation has been associated with diverse cancer, including colorectal and gastric ([@B54]--[@B56]), and related to a predictive role in cervical squamous cell carcinoma survival ([@B57]). As with miR-378a-3p, miR-378c might also be implicated in UC pathophysiology with TNFα related to its regulation; however, complementary studies are essential to gain insight into the biology participation of miR-378c in those diseases.

![Model of IL-33 regulation by MiR-378a-3p in an inflammatory or healthy environment. **(A)** miR-378a-3p hosted in the intron 1 of PPARGC1B in the cytoplasm of epithelial cells interacts with IL-33 3′UTR mRNA controlling its production. **(B)** Inflammation condition represented by TNFα, decreases miR-378a-3p levels in epithelial cells promoting IL-33 transcription and translation, together with increased cell viability. When cells undergo necrosis, IL-33 release occurs and binds to ST2L, causing activation of lamina propria cells \[neutrophils, mast cells, macrophages (pro-inflammatory phenotype) and T lymphocytes\], perpetuating a pro-inflammatory environment in the intestinal mucosa.](fimmu-10-02449-g0008){#F8}

Remarkably, while miR-378a-3p is highly conserved between species ([@B45]) its target sequence in IL-33 is not ([@B58]), which is a common miRNA-target feature between distantly related animals ([@B59]). This highlights the importance of studying the interaction of miR-378a-3p and IL-33 in UC pathogenesis in human sample patients.

Our results showed high IEC cell viability when the content of miR-378a-3p is repressed and IL-33 increased. Decreased levels of miR-378a-3p have been related to colorectal cancer progression which targets cell cycle genes thus, promoting cell growth ([@B60]). Moreover, increased expression of IL-33 has been associated with cellular growth and proliferation in cancer cells ([@B41]). In inflamed intestinal mucosa, the effect of miR-378a-3p might be related to the re-epithelialization process, however, further studies are necessary to prove this hypothesis. Alternatively, the risk of colorectal cancer is elevated in UC patients and increases with disease extension and duration ([@B61]). Inflammatory molecules have been implicated in tumor microenvironment ([@B62]), and in line with our data, miR-378 family members were found decreased in stage II tumor colon cancer ([@B63]). This new knowledge emphasizes the relevance of inflammatory molecules involved in UC cancer progression; however, more studies are necessary to understand the implications of miR-378 and IL-33 in colon cancer risk for UC patients.

The miR-378a-3p is located in intron 1 of the PPARGC1B gene (PPARG coactivator 1 beta, 5q32), with levels found deregulated in intestinal mucosa of UC patients ([@B23]). We showed a direct correlation between both molecules in IEC suggesting that the microRNA might depend on the *PPARGC1B* transcriptional activity (see proposed mechanism, [Figure 8](#F8){ref-type="fig"}). PPARGC1B protein is involved in the control of genes associated with mitogenesis and mitochondrial metabolism ([@B64]), energy production and biogenesis ([@B65]), and highly expressed in intestinal epithelium of the crypts and villus axis ([@B66]). Furthermore, *Ppargc1b* enterocyte knockout mice present a decreased expression of metabolic pathways ([@B66]). Our gene expression microarray results showed diminished levels of *PPARGC1B* (−2.1 FC) in inflamed mucosa and altered content of mRNAs associated with mitochondrial dysfunction (IPA analysis). In relation to UC pathogenesis, a decreased colonic activity of mitochondrial complex II, III, and IV from aUC patients possibly indicates impaired mitochondrial function ([@B67]). Additionally, miR-378a-3p and its host gene, have been associated with regulation of metabolic pathways as well ([@B45]). In our data, decreased levels of miR-378a-3p might reflect a metabolic shift in inflamed mucosa, possibly associated with an increment of energy expenditure and ROS overproduction in aUC patients ([@B67]). Thus, miR-378a-3p might converge a metabolic regulation with cytokine control role in the intestinal mucosa.

Conclusion {#s5}
==========

In conclusion, this study addressed a novel mechanism of IL-33 regulation by miR-378a-3p in colonic epithelium cells under inflammatory conditions. Thus, inhibition of miR-378a-3p by inflammation enhanced IL-33 protein levels in IEC, highlighting genes and microRNAs associated with metabolic shifts in ulcerative colitis, possibly impacting on soluble inflammatory factors ([Figure 8](#F8){ref-type="fig"}). This research contributed to an in-depth analysis of a microRNA controlling IL-33 levels in an inflammatory environment and hopefully represents the basis of new biomarkers or a therapeutic target grounded on microRNA regulation for UC.

Data Availability Statement {#s6}
===========================

The datasets generated for this study can be found in the GSE133061, <https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE133061>.

Ethics Statement {#s7}
================

The studies involving human participants were reviewed and approved by Sub-direction of Research, Local Ethics Committee from Clínica Las Condes, Santiago, Chile. The patients/participants provided their written informed consent to participate in this study.

Author Contributions {#s8}
====================

KD-C performed most of the experiments and analysis, designing, and drafting of the manuscript. DD-J, MD, and GL contributed to design and achieve IL-33 detection in biopsies samples and HT-29 experiments. MO-M accomplished IPA and microarray analysis. RQ contributed to study design and sample acquisition. DS and MM enrolled UC and healthy individuals. JAC and XX performed microarray bioinformatics analysis. GG and JX designed and developed the microRNA sensor vector tools. JC developed the pri-miR lentiviral tool. RS-R supported the designing and results analysis of sensor vector experiments. M-JG prarticipated in the analysis and discussion of results. AC contributed with RNA: microRNA interaction analysis. MH contributed to study design, supervised work. All the authors contributed to the drafting and discussion of the manuscript.

Conflict of Interest
--------------------

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

We wish to thank Gene Therapy Center UMASS (MA, USA); the NIEHS transduction laboratory (NC, USA); the Center for Genomics and Bioinformatics, Universidad Mayor (Santiago, Chile); Cell Transformation Laboratory and Cancer Genomic Laboratory, Universidad de Chile (Santiago, Chile) and Laboratory of Immunogastroenterology, Hospital Clínico Universidad de Chile (Santiago, Chile) for their support to this research. The figures were produced using Servier Medical Art from [www.servier.com](http://www.servier.com). We would also like to thank David Cox for his editing contribution.

**Funding.** Clínica Las Condes Academic Project PI2013-B002 (RQ), National Fund for Scientific and Technological Development No. 1170648 (MH); National Commission for Scientific and Technological Research Scholarship No. 21150264 (DD-J), No. 21120682 (MO-M); and MECESUP Scholarship No. UCH 0714 (KD-C).

Supplementary Material {#s10}
======================

The Supplementary Material for this article can be found online at: <https://www.frontiersin.org/articles/10.3389/fimmu.2019.02449/full#supplementary-material>

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Click here for additional data file.

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Click here for additional data file.

[^1]: Edited by: Jose Carlos Alves-Filho, University of São Paulo, Brazil

[^2]: Reviewed by: Angela Bonura, Italian National Research Council (CNR), Italy; Geraldo Aleixo Passos, University of São Paulo, Brazil

[^3]: This article was submitted to Cytokines and Soluble Mediators in Immunity, a section of the journal Frontiers in Immunology


//
// Copyright (C) 2006 Andras Babos and Andras Varga
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with this program; if not, see <http://www.gnu.org/licenses/>.
//

#ifndef __INET_IMESSAGEHANDLER_H
#define __INET_IMESSAGEHANDLER_H

#include "inet/common/INETDefs.h"
#include "inet/common/packet/Packet.h"
#include "inet/routing/ospfv2/Ospfv2Packet_m.h"

namespace inet {

namespace ospfv2 {

class Router;
class Ospfv2Interface;
class Neighbor;

class INET_API IMessageHandler
{
  protected:
    Router *router;

  public:
    IMessageHandler(Router *containingRouter) { router = containingRouter; }
    virtual ~IMessageHandler() {}

    virtual void processPacket(Packet *, Ospfv2Interface *intf, Neighbor *neighbor) = 0;
};

} // namespace ospfv2

} // namespace inet

#endif // ifndef __INET_IMESSAGEHANDLER_H


        IN THE COURT OF CRIMINAL APPEALS OF TENNESSEE
                         AT KNOXVILLE
                                  August 15, 2006 Session

                 STATE OF TENNESSEE v. ROBERT L. MYERS

                 Direct Appeal from the Criminal Court for Sullivan County
                          No. S49,260    Phyllis H. Miller, Judge

                   No. E2005-02576-CCA-R3-CD - Filed October 2, 2006

The defendant, Robert L. Myers, pled guilty to two counts of attempted aggravated sexual battery,
a Class C felony, and was sentenced as a Range I, standard offender to six years on each count, to
be served concurrently. On appeal, he argues that the trial court erred in denying probation or
alternative sentencing. Following our review, we conclude that the trial court properly sentenced
the defendant and affirm the judgments of conviction.

    Tenn. R. App. P. 3 Appeal as of Right; Judgments of the Criminal Court Affirmed

ALAN E. GLENN , J., delivered the opinion of the court, in which JOHN EVERETT WILLIAMS, J., joined.
GARY R. WADE, P.J., not participating.

Richard A. Spivey and Timothy R. Wilkerson, Kingsport, Tennessee, for the appellant, Robert L.
Myers.

Paul G. Summers, Attorney General and Reporter; Cameron L. Hyder, Assistant Attorney General;
H. Greeley Wells, Jr., District Attorney General; and Kent L. Chitwood, Jr. and William B. Harper,
Assistant District Attorneys General, for the appellee, State of Tennessee.

                                           OPINION

        On June 9, 2004, a grand jury indicted the sixty-five-year-old defendant on two counts of
aggravated sexual battery, and he subsequently pled guilty to the lesser-included offenses of
attempted aggravated sexual battery. At the submission hearing, the State summarized the evidence
it was prepared to present had the matter gone to trial:

       [O]n September 9th, 2003, Deputy Sherrie Ramsey of the Sullivan County Sheriff’s
       Department received a referral of child sexual abuse from the Department of
       Children’s Services. It was originated by a Kimberly Neece. She stated that at the
       time Ms. Neece lived with the defendant, Mr. Robert Myers, and her five year-old
       daughter, Emily; her daughter’s birthday, December 5th, 1997, and they lived at 750
       VI Ranch Road in Bristol, Tennessee. She stated that on September 6th, 2003 she’d
       gotten off of work early and got home somewhere between 10:30 and 11 p.m., and
       home is the address that I just mention[ed] . . . in Sullivan County. [Ms. Neece] went
       into the house and was going to sneak up on the defendant and Emily and let them
       know that she was home early. She stated that she walked up the stairs, could hear
       them talking and laughing. The defendant’s bedroom door was half cracked and she
       could clearly see inside the bedroom. She stated that she saw the defendant, who was
       lying on the bed with his underwear pulled down, and he was holding his penis in his
       hand. The five year-old, [Ms. Neece’s] five-year-old daughter was sitting on the bed
       in front of him and she was also naked and she was leaning back on her knees and
       she was laughing as if they were playing a game. [Ms. Neece] went into the room,
       confronted them, took [the victim] to her own bedroom and then confronted the
       defendant again with regard to what had happened. The defendant came in, gave a
       statement to the Sullivan County Sheriff’s Department and stated that prior to Ms.
       Neece . . . arriving home, that . . . [the victim] . . ., five years of age, had touched his
       penis on two occasions. According to his statement the second time he did not make
       her stop. Also, it would be the State’s contention that the [victim] made a statement,
       and would make the statement had this case gone to trial, that they had been playing
       a game and also and not at the same time in which she had touched his penis but on
       the same night he had placed his mouth on both of her breasts and on her vagina with
       regard to this game that they had played, and that would be the State’s proof in this
       case.

        At the subsequent sentencing hearing, the defendant offered no proof and said that he was
relying, in part, on the presentence report and sex offender risk assessment from Counseling and
Consultation Services, which are in the record on appeal. The risk assessment stated that the
defendant posed a “moderate risk to re-offend” and that he provided differing versions of the
incident:

               The willingness or ability to honestly discuss their sexual offending behavior
       is the single most important factor associated with successful treatment. [The
       defendant] provided different versions of the “truth” during the course of the
       assessment. His statements were also significantly different than the victim[’]s. [The
       defendant’s] self-report is considered unreliable and his lack of full disclosure is
       associated with a poor treatment outcome.

        The trial court denied alternative sentencing, stating that the defendant’s sentence had
“already been mitigated enough by letting him plead to attempt.” Additionally, the court noted that
the victim, being five years old, had no choice about where to live and that the defendant blamed her
for the sexual contact:

       [T]his little girl couldn’t leave. She couldn’t go out and find her another home, and
       it was her home, the only place she had unfortunately to halfway, supposed to be safe

                                                   -2-
       in this world, was where she lives with her mother, and in that house is a man who
       would abuse her the way this report reads.

               Now, . . . who does he blame? Does he take responsibility for it? No, he
       blames the five-year-old. That’s what the Counseling and Consultation Services
       report states. It states, number one, he’s a moderate range of risk. The next is he is
       able to acknowledge some of the incident offense, however places the responsibility
       for the sexual contact on the five year-old victim.

         The trial court applied enhancement factor (16), see Tenn. Code Ann. § 40-35-114(16) (Supp.
2005), finding that the defendant had “abused a position of private trust on more than one occasion,”
which the court gave great weight. As for mitigating factors, the court concluded that the
defendant’s lack of a criminal record was relevant but entitled to “very, very little weight in a crime
of this nature.” The trial court noted that the defendant had an excellent work history. However, in
summation, the trial court decided that incarceration was appropriate:

       [C]ommunity corrections is out of the question. I don’t find that that would benefit
       him or the community. He has no drug problem. There’s nothing that caused this
       except his desire for sexual excitement and the five year-old was there to provide it.
       So I’m denying alternative sentencing, [finding] that the enhancement factors that
       I’ve found far outweigh any of the good work history and the no criminal record. So
       he’s ordered to serve his sentence of six years [as a] Range I standard offender in the
       Tennessee Department of Corrections.

                                             ANALYSIS

         On appeal, the defendant argues that the trial court erred in denying probation or alternative
sentencing, saying the court “fail[ed] to properly weigh and balance established mitigating factors
with the single enhancement factor applicable to [the defendant], a presumptively favorable
candidate for probation or other alternative sentencing.” The State argues that the record supports
the trial court’s imposition of a sentence of confinement.

        When reviewing the denial of probation, this court conducts a de novo review on the record,
“with a presumption that the determinations made by the court from which the appeal is taken are
correct.” Tenn. Code Ann. § 40-35-401(d) (2003) (amended 2005). The presumption of correctness
is “conditioned upon the affirmative showing in the record that the trial court considered the
sentencing principles and all relevant facts and circumstances.” State v. Ashby, 823 S.W.2d 166,
169 (Tenn. 1991). If appellate

       review “reflects that the trial court followed the statutory sentencing procedure,
       imposed a lawful sentence after having given due consideration and proper weight
       to the factors and principles set out under the sentencing law, and that the trial court’s

                                                  -3-
         findings are adequately supported by the record, then we may not modify the
         sentence even if we would have preferred a different result.”

 State v. Hooper, 29 S.W.3d 1, 5 (Tenn. 2000) (quoting State v. Fletcher, 805 S.W.2d 785, 789
(Tenn. Crim. App. 1991)).

        A defendant shall be eligible for probation, subject to certain exceptions, if the sentence
imposed upon the defendant is eight years or less. Tenn. Code Ann. § 40-35-303(a) (2003)
(amended 2005).1 Even if eligible, however, the defendant is not automatically entitled to probation
as a matter of law. See Tenn. Code Ann. § 40-35-303(b). The burden is on the appellant to show
the denial of probation was improper. See State v. Summers,159 S.W.3d 586, 599-600 (Tenn. Crim.
App. 2004) (citing Ashby, 823 S.W.2d at 169); see also State v. Baker, 966 S.W.2d 429, 434 (Tenn.
Crim. App. 1997) (stating that “[a] criminal defendant seeking full probation bears the burden on
appeal of showing the sentence actually imposed is improper, and that full probation will be in both
the best interest of the defendant and the public”).

        There is no bright line rule for determining when a defendant should be granted probation.
State v. Bingham, 910 S.W.2d 448, 456 (Tenn. Crim. App. 1995), overruled on other grounds by
State v. Hooper, 29 S.W.3d 1 (Tenn. 2000). Every sentencing decision necessarily requires a case-
by-case analysis. Id. Factors to be considered include the circumstances surrounding the offense,
the defendant’s criminal record, the defendant’s social history and present condition, the need for
deterrence, and the best interest of the defendant and the public. State v. Goode, 956 S.W.2d 521,
527 (Tenn. Crim. App. 1997). Another appropriate factor for a trial court to consider in determining
whether to grant probation is a defendant’s credibility or lack thereof, as this reflects on the
defendant’s potential for rehabilitation. Id.

         In this matter, it is clear that, in denying probation, the trial court considered the relevant
facts, circumstances, and sentencing principles; and, thus, its findings as to the sentence are entitled
to a presumption of correctness. In denying probation, the court found that the defendant had not
been candid as to the facts of the incident but had, in fact, “place[d] the responsibility for the sexual
contact on the five year-old victim.” As we have set out, a defendant’s lack of candor reflects on his
potential for rehabilitation. Further, according to the report from Counseling and Consultation
Services, the defendant’s “lack of full disclosure is associated with a poor treatment outcome.” In
essence, the defendant simply disagrees with the weight which the trial court afforded the

         1
          W e cite to the 2003 version of the Code because it is the law properly applied to the defendant. See 2005
Tenn. Pub. Acts ch. 353, § 18. The defendant could have elected to be sentenced under the 2005 Act because his crimes
were committed prior to June 7, 2005, and he was sentenced after that date. See id. As the defendant did not so elect,
the 2003 probation provision applies in this case. However, we note that substantial changes came with the 2005
amendment, including increasing the maximum sentence length a defendant can receive and still be eligible for probation
from eight to ten years. Tenn. Code Ann. § 40-35-303(a) (2005).

                                                         -4-
enhancement and mitigating factors. However, it is within the discretion of the trial court as to the
weight to be afforded the factors. State v. Boggs, 932 S.W.2d 467, 475 (Tenn. Crim. App. 1996).
We conclude that the record easily supports the trial court’s determination that the defendant did not
establish that he was a favorable candidate for probation.

                                          CONCLUSION

       For the foregoing reasons, we affirm the trial court’s denial of alternative sentencing.

                                                       ___________________________________
                                                       ALAN E. GLENN, JUDGE

                                                 -5-


Of African origin, Gelasius was born in Rome, and, prior to his election to the papacy, he was charged by his predecessor, Felix II, to compose ecclesiastical documents. As pope, Gelasius dealt firmly with threats to the Church of Rome from schismatics such as the adherents of Acacius. Gelasius proved unyielding in any attempts to compromise the papacy and the Church, and wrote, “There are two powers by which chiefly this world is ruled: the sacred authority of the priesthood and the authority of kings. And of these the authority of the peists is so much the weightier, as they must render before the tribunal of God an account even for the kings of men” (Catholic Encyclopedia).

Gelasius is credited with allowing for the reception of the Eucharist in both forms, although the purpose of this edict was as a way of detecting a group of subversives masquerading as Catholics – they believed wine to be sinful and would not partake, therefore giving themselves away. He also instituted the division of revenues into four parts: one for the poor, one to support the churches, one for the bishop, and the last for minor clergy.

Thought to have composed the Canon of the Scriptures, Gelasius also composed hymns, collects, and a Missal. He held a spirit of prayer, penance and study, and was called “a true father to the poor, dying empty-handed as a result of his lavish charity” (Catholic Encyclopedia).

Gelasius was the most prolific writer of the early Roman bishops. A great mass of correspondence of Gelasius has survived: forty-two letters according to the Catholic Encyclopedia, thirty-seven according to Father Bagan and fragments of forty-nine others, carefully archived in the Vatican, expounding to Eastern bishops the primacy of the see of Rome.

He was Pope from 1 March 492 – 21 November 496 (4 years, 265 days).

Catholic Encyclopedia. 2016.