text:
The purpose of this systematic evidence-based review, requested by the Agency for Healthcare Research and Quality (AHRQ) and conducted by the RTI International—University of North Carolina at Chapel Hill Evidence-based Practice Center (RTI-UNC EPC), was to review the evidence on outcomes of gestational weight gain with specific attention to five key questions:
KQ 1. What is the evidence that either total weight gain or rate of weight gain during pregnancy is associated with (1) birth outcomes, (2) infant health outcomes, and (3) maternal health outcomes? Does any evidence suggest that either total weight gain or rate of weight gain is a causal factor in infant or maternal health outcomes?
KQ 2. What are the confounders and effect modifiers for the association between gestational weight gain (overall and patterns) and birth outcomes? Based on the findings in KQ 1, do these confounders and effect modifiers themselves contribute to antepartum or postpartum complications or to longer-term maternal and fetal complications, including development of adult obesity?
KQ 3. What is the evidence that weight gains above or below thresholds defined in the 1990 IOM body mass index (BMI) guide-
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Results from the Evidence-Based Report*
on Outcomes of Maternal Weight Gain
The purpose of this systematic evidence-based review, requested by
the Agency for Healthcare Research and Quality (AHRQ) and conducted
by the RTI International—University of North Carolina at Chapel Hill
Evidence-based Practice Center (RTI-UNC EPC), was to review the evi-
dence on outcomes of gestational weight gain with specific attention to five
key questions:
• KQ 1. What is the evidence that either total weight gain or rate
of weight gain during pregnancy is associated with (1) birth out-
comes, (2) infant health outcomes, and (3) maternal health out-
comes? Does any evidence suggest that either total weight gain or
rate of weight gain is a causal factor in infant or maternal health
• KQ 2. What are the confounders and effect modifiers for the as-
sociation between gestational weight gain (overall and patterns)
and birth outcomes? Based on the findings in KQ 1, do these con-
founders and effect modifiers themselves contribute to antepartum
or postpartum complications or to longer-term maternal and fetal
complications, including development of adult obesity?
• KQ 3. What is the evidence that weight gains above or below
thresholds defined in the 1990 IOM body mass index (BMI) guide-
* Appendixes and evidence tables cited in this report are provided electronically at http://
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lines or weight loss in pregnancy contribute to antepartum or
postpartum complications or longer-term maternal and fetal com-
plications? How do these relationships vary by sociodemographic
characteristics (i.e., race and age)?
• KQ 4. What are the harms or benefits of offering the same weight
gain recommendations to all pregnant women, irrespective of age
and body weight considerations (e.g., pregravid weight, actual
body weight at a particular time point, or optimal body weight)?
• KQ 5. What are the anthropometric tools for determining adiposity
and their appropriateness for the pregnancy state? What are the
risks and benefits of measuring adiposity for (1) clinical manage-
ment of weight gain during pregnancy and (2) evaluation of the
relationship between weight gain and outcomes of pregnancy?
The review focused on screening studies from 1990 to October 2007
that were published in English, and excluded studies with low sample size
(case series < 100 and cohorts < 40) or failure to control for pregravid
weight. In total, 150 studies were systematically reviewed and each was
rated on quality and used to assess the strength of evidence for each out-
come. The report, including appendices and evidence tables, can be ac-
cessed and viewed in its entirety at http://www.ahrq.gov/clinic/tp/admattp.
htm. Literature published outside of the scope of the report (prior to 1990
and after October 2007) are reviewed in Appendix C of this report. The
methods and results and of the evidence review (Chapter 3 of the report)
are provided below.
In this chapter, we document the procedures that the RTI International-
University of North Carolina Evidence-based Practice Center (RTI-UNC
EPC) used to develop this comprehensive evidence report on outcomes
of maternal weight gain. The team was led by a senior health services
researcher (Meera Viswanathan, PhD, Study Director), a senior epidemi-
ologist (Anna Maria Siega-Riz, PhD, RD, Scientific Director), and a senior
nurse-researcher (Merry-K Moos, FNP, MPH, co-Scientific Director).
We first describe our strategy for identifying articles relevant to our five
key questions (KQs), our inclusion and exclusion criteria, and the process
we used to abstract relevant information from the eligible articles and
generate our evidence tables. We also discuss our criteria for grading the
quality of individual articles and for rating the strength of the evidence as
a whole. Finally, we explain the peer-review process.
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TABLE 1. Inclusion/exclusion Criteria for Gestational Weight Gain
Category Criteria
Study population Women of any age with singleton pregnancies
Study settings KQ 1, KQ 2, KQ 4: Developed nations: United States, Canada, Western
and geography Europe, Japan, Australia, New Zealand
KQ 3: United States
KQ 5: All countries
Time period January 1990 through October 2007
Publication English only
Admissible Admissible designs
Controlled trials (n ≥ 40), nonrandomized controlled trials (n ≥ 40),
evidence (study
design and other systematic reviews, meta-analyses, prospective trials with historical
controls (n ≥ 40), prospective or retrospective observational cohort
studies (n ≥ 40), and medium to large case series (n ≥ 100)
Other criteria
Original research studies must provide sufficient detail regarding
methods and results to enable use and adjustment of the data and
Relevant outcomes must be abstractable from data presented in the
Sample sizes must be appropriate for the study question addressed in
the paper; single case reports or small case series (fewer than 100
subjects) are excluded.
For KQ 1, 2, 3, and 4: prepregnancy body mass index (BMI) or weight
must be accounted for in the relationship between maternal weight
gain and outcome.
Studies limited to women with preexisting health conditions only are
Literature Review Methods
Inclusion and Exclusion Criteria
Our inclusion and exclusion criteria are documented in Table 1. As
noted in Chapter 1, this systematic review focuses on outcomes of maternal
weight gain with respect to the 1990 recommendations from the Institute
of Medicine (IOM). Largely for that reason, we limited our searches to
articles published in 1990 and thereafter. We also restricted our searches
to developed countries so that we could have data generally relevant for
maternal weight gain and health outcomes in the United States.
We excluded studies that (1) were published in languages other than
English (given the available time and resources); (2) did not report informa-
tion pertinent to the key clinical questions; (3) had fewer than 40 subjects
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for randomized controlled trials (RCTs) or nonrandomized cohorts with
comparisons or fewer than 100 subjects for case series; and (4) were not
original studies.
For KQ 1, 2, 3, and 4, we required that the reported association be-
tween maternal weight gain and health outcomes accounted for prepreg-
nancy body mass index (BMI) or weight, either through stratified univariate
analysis or multivariate analysis.
Literature Search and Retrieal Process
Databases We used multifaceted search strategies to include current and
valid research on the KQs, which we applied to four standard electronic
databases—MEDLINE®, Cochrane Collaboration resources, Cumulative
Index to Nursing and Allied Health Literature (CINAHL), and Embase.
We also hand-searched the reference lists of relevant articles to make sure
that we did not miss any relevant studies. We consulted with our Technical
Expert Panel (TEP) about any studies or trials that are currently under way
or that may not yet be published.
Search terms. Based on the inclusion/exclusion criteria above, we gener-
ated a list of Medical Subject Heading (MeSH) search terms (Table 2 and
Appendix A*). Our TEP also reviewed these terms to ensure that we were
not missing any critical areas, and this list represents our collective deci-
sions as to the MeSH terms used for all searches.
TABLE 2. MEDLINE® Search Strategy and Unduplicated Results for
February 2007
Search Terms Search Results
#2 Search "Weight Gain"[MeSH] 13,220
#5 Search pregnancy [MeSH] 577,647
#6 Search #2 AND #5 1,808
#7 Search gestational weight gain 1,725
#8 Search #6 OR #7 3,023
#9 Search #6 OR #7 Limits: English, Humans 1,696
#15 Search ("Outcome Assessment (Health Care)"[MeSH] OR "Outcome 332,914
and Process Assessment (Health Care)"[MeSH] OR "Pregnancy
Outcome"[MeSH]) OR "Reproductive History"[MeSH] OR "birth
outcomes" OR "infant health outcomes" OR "maternal health
outcomes" Limits: English, Humans
#16 Search #9 AND #15 Limits: English, Humans 474
#19 Search ("Counseling"[MeSH] OR "Directive Counseling"[MeSH]) 23,091
#20 Search #9 AND #19 12
#25 Search "Body Weights and Measures"[MeSH] 279,399
#26 Search #9 AND #25 1,044
#29 Search "Anthropometry"[MeSH] 71,849
#30 Search #26 AND #29 359
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Our searches in MEDLINE® produced 715 unduplicated records.
Searches in other databases yielded in 190 new records from CINAHL and
4 from Embase. Similar searches in Cochrane did not produce any new ci-
tations. Following an update on October 3, 2007, and additional searches
for KQ 5, we ultimately identified 1,082 unduplicated records. In addition,
peer reviews suggested 3 new citations that met our inclusion criteria.
Figure 1 presents the yield and results from our searches, which we
conducted from February through October 3, 2007. Beginning with a yield
FIGURE 1. Disposition of articles for gestational weight gain.
APP E Fig 2
CD only
entire image, including type, is bitmapped
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of 1,085 articles, we retained 150 articles that we determined were relevant
to address our KQs and met our inclusion/exclusion criteria (Table 1).
We reviewed titles and abstracts of the articles against the basic inclusion
criteria above; we retained relevant articles, all published after our search
cutoff date of January 1990, and used them as appropriate in the discus-
sion in Chapter 4.
Article selection process Once we had identified articles through the elec-
tronic database searches, review articles, and reference lists, we examined
abstracts of articles to determine whether studies met our criteria. Each
abstract was independently, dually reviewed for inclusion or exclusion, us-
ing an Abstract Review Form (Appendix B). If one reviewer concluded that
the article should be included in the review, we retained it.
Of this entire group of 1,085 articles, 479 required full review. For the
full article review, one team member read each article and decided whether
it met our inclusion criteria, using a Full Text Inclusion/Exclusion Form
(Appendix B*). Reasons for article exclusion are listed in Appendix D.
Literature Synthesis
Deelopment of Eidence Tables and Data Abstraction Process
The senior staff who conducted this systematic review jointly developed
the evidence tables. We designed the tables to provide sufficient information
to enable readers to understand the studies and to determine their quality;
we gave particular emphasis to essential information related to our KQs.
We based the format of our evidence tables on successful designs that we
have used for prior systematic reviews.
We trained abstractors by having them abstract several articles into
evidence tables and then reconvening as a group to discuss the utility of
the table design. The abstractors repeated this process through several itera-
tions until they decided that the tables included the appropriate categories
for gathering the information contained in the articles.
Three junior epidemiologists (Sunni Mumford, SM; Andrea Deierlein,
MS, MPH; and Julie K. Knaack, MPH, RD, LDN) shared the task of ini-
tially entering information into the evidence tables. Senior staff reviewed
the articles and edited all initial table entries for accuracy, completeness,
and consistency. Abstractors reconciled all disagreements concerning the
information reported in the evidence tables. The full research team met
regularly during the article abstraction period and discussed global issues
related to the data abstraction process.
The final evidence tables are presented in their entirety in Appendix C.
Studies are presented in the evidence tables alphabetically by the last name
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of the first author. A list of abbreviations and acronyms used in the tables
appears at the beginning of that appendix.
Quality Rating of Indiidual Studies
The evidence for this systematic review is based almost entirely on
observational studies. This fact presents a challenge for rating individual
studies. Quality rating forms for RCTs have been validated and in use for
several years; a similarly well-validated form for observational studies does
not exist.
Thus, as a parallel effort, we developed a form to rate observational
studies.35 This form, which can be used to rate the quality of a variety
of observational studies, was based on a review of more than 90 AHRQ
systematic reviews that included observational studies; we supplemented
this review with other key articles identifying domains and scales.36,37 We
structured the resultant form largely on the basis of the domains and sub-
domains suggested by Deeks and colleagues;36 we then adapted it for use
in this systematic review (Appendix B*).
The form currently includes review of nine key domains: background,
sample selection, specification of exposure, specification of outcome, sound-
ness of information, followup, analysis comparability, analysis of outcome,
and interpretation. Each of these domains was further evaluated on aspects
of quality of the study design or reporting that would influence the reader's
perception of internal validity of the journal article (Table 3). We note that
variations in reporting could result in different scores for studies drawing
from the same sample.
As described in Table 3, we combined these elements to generate overall
scores. We set the default as fair and then focused on the threshold required
for good and poor studies; the algorithm is also described in Table 3. Fair
studies, therefore, include studies that were predominantly fair (four to nine
fair ratings on domains) and could not be rated either good (fewer than
five good ratings for subdomains) or poor (fewer than three poor ratings
for subdomains). Studies with more than five good ratings for domains that
also received one or two poor ratings were downgraded to fair quality.
Key methodological concerns in this literature relate to the source of
information on weight gain and the timing of measurement of weight gain.
Studies that relied solely on self-reported pregravid and final pregnancy
weights suffer from well-documented issues of recall bias. In addition,
women tend to misreport their weight, and this bias varies by weight
status38 and ethnicity.39 The timing of weight measurement (for pregravid
weight and final weight) can vary depending on the design of the study;
when unreported, the total weight gain during pregnancy cannot be as-
sumed to be collected at similar time points for all women within the study,
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TABLE 3. Scoring Algorithm for Subdomains and Overall Quality
Rating for Individual Studies
Definition and Scoring Algorithm Rating
Score algorithm for background (presented in the context of previous research,
hypothesis clearly described)
• Both elements present Good
• Neither present Poor
• One of two elements present Fair
Score algorithm for sample definition (explicitly stated inclusion/exclusion criteria,
uniform application of criteria, clear description of recruitment strategy, clear description
of characteristics of the participants, power analysis or some other basis noted for
determining the adequacy of study sample size)
• > Three elements present Good
• < Two elements present Poor
• Two or three elements present Fair
Score algorithm for exposure (clear definition of weight gain, check for plausibility of
pregravid weight, clear explanation of actions taken on outliers)
• All three elements present or clearly defined Good
• Poor definition of weight gain Poor
• Moderate or very clear definition of weight gain, one or more other elements Fair
Score algorithm for outcome (clear description of primary outcomes)
• All essential details described Good
• Few or no essential details described Poor
• Some essential details described Fair
Score algorithm for soundness of information (quality of source of information on
exposure, confounders, and outcome)
• Good for all three Good
• Poor on source of information for exposure Poor
• Any other score Fair
Score algorithm for followup (adequate reporting of reasons for loss to followup)
• Retrospective or prospective study with clear reporting on loss to followup Good
• Prospective study, no reporting on followup Poor
• Retrospective study with no reporting on loss to followup Fair
Score algorithm for analysis comparability (comparability of cohorts through design,
reasonable choice of control variables, clear description of confounders, adequate
adjustment for confounders)
• All elements present Good
• Inadequate adjustment for confounding Poor
• Any other score Fair
Score algorithm for analysis outcome (withdrawals, lost to followup, and missing data
adequately accounted for in the analysis, and appropriate statistical methods used)
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TABLE 3. Continued
Definition and Scoring Algorithm Rating
• Both elements clearly present Good
• Neither element present Poor
• Any other score Fair
Score algorithm for interpretation (results interpreted appropriately based on study
design and statistics, clinically useful, appropriate presentation, presented in the context
of prior research, and conclusion supported by results)
• All elements clearly present Good
• Conclusions not supported by results Poor
• Any other score Fair
Score algorithm for overall quality
• 5 or more good ratings and no poor ratings on subdomains Good
• 3 or more poor ratings on subdomains Poor
• < 5 good ratings and < 3 poor ratings on subdomains; 5 or more good ratings Fair
and any poor ratings
resulting in further bias. Our rating algorithm, therefore, paid special at-
tention to the source of data on gestational weight gain and the timing of
measurement. Studies that relied solely on recalled prepregnancy and total
pregnancy weight were rated poor on that domain, but if they defined their
gestational weight variable clearly (providing details on the timing of mea-
surement for pregravid and final weight measurements) and either checked
for the biological plausibility of pregravid weight status or explained how
outliers were dealt with, they could receive an overall fair rating (assuming
that they received fewer than three poor ratings overall).
Strength of Aailable Eidence
Our scheme follows the criteria applied in an earlier RTI-UNC EPC
systematic review of systems for rating the strength of a body of evidence.40
That system has three domains: quality of the research (as evaluated by the
quality rating algorithm described above), quantity of studies (including
number of studies and adequacy of the sample size), and consistency of
findings. Two senior staff members assigned grades by consensus.
We graded the body of literature for each KQ and present those ratings
as part of the discussion in Chapter 4. The possible grades in our scheme
are as follows:
I. Strong: The evidence is from studies of sound design (good quality);
results are both clinically important and consistent with minor exceptions
at most; results are free from serious doubts about generalizability, bias, or
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flaws in research design. Studies with negative results have sufficiently large
samples to have adequate statistical power.
II. Moderate: The evidence is from studies of sound design (good qual-
ity), but some uncertainty remains because of inconsistencies or concern
about generalizability, bias, research design flaws, or adequate sample size.
Alternatively, the evidence is consistent but derives from studies of weaker
design (fair quality).
III. Weak: The evidence is from a limited number of studies of weaker
design (fair or poor quality). Studies with strong design (good quality) ei-
ther have not been done or are inconclusive.
IV. No evidence: No published literature.
External Peer Review
As is customary for all evidence reports and systematic reviews done
for AHRQ, the RTI-UNC EPC requested review of this report from a
wide array of individual outside experts in the field, including our TEP,
and from relevant professional societies and public organizations. AHRQ
also requested review from its own staff. We sent 20 invitations for peer
review: 6 TEP members, 6 relevant organizations, and 8 individual experts.
Reviewers included clinicians (e.g., obstetrics and gynecology, women's
health/general health), representatives of federal agencies, advocacy groups,
and potential users of the report.
We charged peer reviewers with commenting on the content, structure,
and format of the evidence report, providing additional relevant citations,
and pointing out issues related to how we had conceptualized and defined
the topic and KQs. We also asked them to complete a peer review checklist.
We received comments from 11 of the invited peer reviewers in addition
to comments from AHRQ staff. The individuals listed in Appendix E**
gave us permission to acknowledge their review of the draft. We compiled
all comments and addressed each one individually, revising the text as
This chapter presents the results of our evidence review for the follow-
ing four key questions (KQs): KQ 1, outcomes of gestational weight gain;
KQ 3, outcomes of gestational weight gain within or outside the recom-
mendations of the Institute of Medicine (IOM); and KQ 5, anthropometrics
of gestational weight gain.
We note that KQ 2, on modifiers of outcomes, is derivative of KQ 1.
KQ 4, on recommendations for weight gain, is derivative of KQ 3. Because
we framed KQ 2 and KQ4 as synthesis questions, we cover them in Chap-
ter 4.
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Appendix C provides the detailed evidence tables for KQs 1, 3, and 5.
Our summary tables below feature groups of studies addressing each out-
come; we present these text tables only when we have three or more studies
pertaining to that particular outcome. These tables are organized by quality
(good, then fair, then poor), and then alphabetically.
The summary tables generally provide information to identify the study
(author and date), sample size, study quality, definition of gestational weight
gain, definition of outcome, results, and confounders and effect modifiers.
Unless otherwise noted, we use the metrics (e.g., grams, kilograms, pounds)
that each study article used; we did not recalculate measures into the same
KQ 1: Outcomes of Gestational Weight Gain
We present outcomes in the physiological order, beginning with mater-
nal antepartum and intrapartum outcomes, then birth outcomes (neonatal
outcomes at the time of birth), infant outcomes (< 1 year), child outcomes
(≥ 1 year), and finally maternal short- and long-term outcomes. Evidence
Tables 1-35 (Appendix C) include studies relevant for KQ 1, listed alpha-
betically by author. For each outcome, we describe study characteristics
and then report an overview of results, followed by detailed results. When
meaningful, we present results separately for varied measures of gestational
weight gain (categorical measures of weight gain, rate of weight gain, total
weight gain, and other). For some bodies of evidence, variations in the
definition of the outcome and inconsistencies in the direction of effect may
suggest that an overall assessment of the effect is more meaningful than
separate assessments of outcomes associated with each measure of gesta-
tional weight gain. Summary tables and text include information on the
confounders and effect modifiers accounted for in each study.
Maternal Antepartum Outcomes
Maternal discomforts of pregnancy
Study characteristics Five studies (Evidence Table 1) investigated the
relationship between weight gain and diverse maternal discomforts of preg-
nancy: a composite of pregnancy discomforts,41 physical energy and fa-
tigue,42 stretch marks,43,44 and heartburn.45
Oeriew of results Two fair41,42 and three poor studies43-45 found
no differences for women who gained an excessive amount of weight
compared to those who did not, irrespective of body mass index (BMI)
group,42 a higher frequency of symptoms from midpregnancy through the
36th week of gestation,46 no association between gestational weight gain
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and B Hervias-Vivancos. Ultrasound evaluation of visceral fat and metabolic risk factors
during early pregnancy Obesity (Silver Spring) 2007. Sep. 15: (9) 2233-9. (PubMed)
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Chris Antonetti, the Cleveland Indians' VP and GM, announced the Indians have promoted top second-base prospect Jason Kipnis from Triple-A Columbus of the International League. Kipnis, 24, was originally drafted by the Padres in the fourth round of the 2008 June amateur draft but did not sign. He was the Pacific-10 player of the year at Arizona State the following year and was drafted the next season by the Indians in the second round of the 2009 draft, ultimately signing for $575,000. He was moved from the outfield to second base that fall during the Indians' Instructional League program.
Kipnis hits the ball hard to all fields with surprising power for his 5-foot-11 frame. With his strong forearms, hands and wrists, along with a strong mid-section, he projects to being a 15-18 home run hitter. The bat will be an immediate upgrade for the Tribe at second base.


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Localizing your app is extremely important for any developer but it's especially important for BlackBerry devs. RIM is selling devices all over the world with hotbeds in places like Indonesia. If your app is only in English, you aren't capitalizing on those BlackBerry users that only want to download an app with support for their language. Tethras aims to help make that process easy. Click through for more details.
Continue reading 'Developers: Translate and Localize Your Apps With Tethras'


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In today's Q&A, Chuck Finder answers a question from a fan upset about last June's Nate McLouth trade. I understand why this trade incensed many fans. McLouth was a quality player and a fan favorite. He was one of my favorites, too. But once we get past the emotional reaction, we see that the trade of McLouth, along with the subsequent acquisition of Lastings Milledge, did not exactly hurt the Pirates. In 2009, McLouth was only marginally more valuable for Atlanta than Charlie Morton was for the Pirates. When we consider Andrew McCutchen and Garrett Jones were more productive outfielders, it is clear that the McLouth deal did not affect the Pirates last season.
Let's look forward to 2010, primarily at the difference between an outfield duo of McLouth/Nyjer Morgan and McCutchen/Milledge. I converted CHONE's projected wOBA into runs using the formula (wOBA – .330)/1.15 * 600. This gives us offensive runs above or below average, based on 600 plate appearances. Combining Erik Manning's UZR/150 projections with a positional adjustment gives us a total defensive value.
2010 Age | Offense | Defense | Overall | |
Nate McLouth | 28 | 13.0 | -1.5 | 11.5 |
Nyjer Morgan | 29 | -4.7 | 3.5 | -1.2 |
Andrew McCutchen | 23 | 14.1 | 3.5 | 17.6 |
Lastings Milledge | 25 | 4.2 | -2.5 | 1.7 |
The Pirates have upgraded for 2010 in both left and center field, while becoming significantly younger in the process. McLouth is likely experiencing his peak, while Morgan will never replicate his 2009 production. McCutchen, on the other hand, is ready to burst into stardom, while Milledge is just approaching his prime years. Both of these players will improve, while McLouth and Morgan are more likely to decline. McLouth is a better option in right than Garrett Jones, but Charlie Morton provides a similar boost to the starting rotation. Besides, Jose Tabata is knocking on the door to take over right field.
2010 Age | Offense | Defense | Overall | ||
Nate McLouth | 28 | 13.0 | -1.5 | 11.5 | |
2010 Age | FIP | Runs * | |||
Charlie Morton | 26 | 4.16 | 11.8 | ||
* based on 180 innings |
McLouth was an asset in the outfield, a position of relative team depth. The Pirates exchanged him for Morton, a similarly valued asset on the mound, where the team was weak. The Bucs also received two of their current top 15 prospects in the process. I know it is not easy to accept as a fan, but the trade improved the Pirates' future, without sacrificing much of the present.


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text: Lie to Me Series 3 - 5. The Canary's Song Facebook Google Tumblr Pinterest Blogger Reddit VKontakt Print Email About this programme 5/13. Lightman investigates a coal mine explosion that claimed the lives of six miners, and suspecting foul play, puts his own life on the line to ascertain the real cause of their deaths. Meanwhile, Foster and Torres offer to work voluntarily when the FBI asks the team for help with a difficult case. Cast and crew Cast Dr Cal Lightman Tim Roth Dr Gillian Foster Kelli Williams Eli Loker Brendan Hines Ria Torres Monica Raymund Emily Lightman Hayley McFarland Det Sharon Wallowski Monique Gabriela Curnen Crew Director Seith Mann Categories Drama Like this? Share it. Facebook Google Tumblr Pinterest Blogger Reddit VKontakt Print Email


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$8.99As recommended on epinions and pet lovers sites everywhere! We now have, in stock, the Gonzo Revolutionary Pet Hair Lifter! This amazing dry sponge works great on upholstery, clothing, drapes, bedding, wallpaper, woodwork, painted walls, carpets, pet ar Learn More -
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The Ten Best Events at Florida Supercon 2014
Christina Mendenhall Break out your best cosplay. Supercon is back.
Geeks unite! This weekend marks our yearly pilgrimage to Florida Supercon, a four-day festival highlighting comics, video games, anime, sci-fi, and all other manner of geekdom. We had a chance to pore over the jam-packed schedule (we're talking almost 1,000 events according to the FAQ) and picked out ten of the events you will NOT want to miss.
See also: Florida Supercon: "Florida's Biggest Geek Party" Moves to Miami Beach
10. Heroes of Cosplay Panel
If the Heroes of Cosplay episode at Animate! Miami left you hungry for more, you're in luck. Show star Miggy Jagger and local cosplay folks are going to let you in on some of the behind-the-scenes chisme from that episode's production. (Friday, 4:15pm, PANEL ROOM A)
9. Keeping It Local: Game Development in Miami
We chronicled the burgeoning Miami game development scene before--now's your chance to dive deeper. Local developers take the stage to talk about why Miami may just become the new hottest city in game development, and how you can be a part of it! (Sunday, 7:00pm, ROOM C227/C228)
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8 Stocks Rising on Monster Volume
Linear Technology
Linear Technology (LLTC - Get Report) designs, manufactures and markets a line of linear analog integrated circuits for companies worldwide. This stock is trading up 2.3% at $32.25 in recent trading.
Today's Volume: 1.95 million
Average Volume: 2.4 million Volume % Change: 62% Shares of LLTC are advancing modestly today after Piper Jaffray & Co. reiterated its overweight rating and $39 price target on the stock. Piper said, "We believe the company is seeing strength from the automotive, industrial, and server and networking end markets as well as its recent acquisition of Dust Networks." From a technical perspective, LLTC is bouncing slightly higher today right near some previous support at $31.44 with decent volume. This stock is currently trading right between its 200-day moving average of $30.61 and its 50-day moving average of $33.31. Traders should now look for long-biased trades once LLTC takes out some near-term overhead resistance at $32.50 with high-volume. Look for a sustained move and close over $32.50 with volume that's near or above 2,398,270 shares. If we get that action soon, look for LLTC to make a run at its 50-day or higher in the near future. Linear Technology shows up on a recent list of 6 Tech Stocks That Rate Better Than Apple.Check Out Our Best Services for Investors
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