text:
The neural circuits that govern behaviors vital to mammals, such as locomotion and respiration, rely on the ability of motor neurons (MNs) within the spinal cord to establish selective connections with dedicated sets of peripheral and central synaptic targets. Signaling pathways acting along the dorsoventral axis of the neural tube have been shown to determine the early identity of MNs and distinguish this class from other neuronal types within the spinal cord. The subsequent diversification of MNs depends on the actions of approximately 20 Hox transcription factors, which appear to be required at distinct phases of MN differentiation. While Hox genes are essential for MN fate specification, the targets of their activities are not known, nor is it understood how they achieve MN-specificity, given their relatively broad roles in patterning along the rostrocaudal axis. Moreover the factors that determine the expression patterns of Hox proteins in MNs are poorly defined.
In aim1 we will characterize the direct targets of Hox proteins, assess how they are regulated in motor columns, and determine if and how they intersect with MN-specific gene programs.
In aim2 we will dissect the mechanisms of Hox protein specificity in controlling facets of MN identity, focusing on the Hoxc9 protein, a central determinant of MN columnar organization.
In aim3 we will test the hypothesis that the organization of Hox-dependent MN subtype relies on graded activities of Polycomb proteins that ensure proper postmitotic Hox expression patterns. These studies will provide basic insights into the mechanisms through which Hox proteins influence MN differentiation, and should allow for the design of strategies to generate MN subtypes from undifferentiated cells.
One of the major challenges in the neural sciences is to understand how the specificity of connections between neurons and their synaptic targets are established during development. The overall goal of this proposal is to elucidate the developmental programs that define the ability of motor neurons in the spinal cord to make very selective connections with muscle targets. Understanding the steps that determine the intrinsic properties of motor neurons may be essential in designing strategies for generating subtypes of neurons from undifferentiated cells, a critical aspect of modeling motor neuron disease states in vitro.
|Jung, Heekyung; Mazzoni, Esteban O; Soshnikova, Natalia et al. (2014) Evolving Hox activity profiles govern diversity in locomotor systems. Dev Cell 29:171-87
|Lacombe, Julie; Hanley, Olivia; Jung, Heekyung et al. (2013) Genetic and functional modularity of Hox activities in the specification of limb-innervating motor neurons. PLoS Genet 9:e1003184
|Boucherat, Olivier; Montaron, Severine; Berube-Simard, Felix-Antoine et al. (2013) Partial functional redundancy between Hoxa5 and Hoxb5 paralog genes during lung morphogenesis. Am J Physiol Lung Cell Mol Physiol 304:L817-30
|Philippidou, Polyxeni; Dasen, Jeremy S (2013) Hox genes: choreographers in neural development, architects of circuit organization. Neuron 80:12-34
|Jung, Heekyung; Lacombe, Julie; Mazzoni, Esteban O et al. (2010) Global control of motor neuron topography mediated by the repressive actions of a single hox gene. Neuron 67:781-96


text:
Poached Cod With Garlic Mayonnaise
|For garlic mayonnaise
|1⁄2 Cup (8 tbs)
|Snipped fresh parsley
|1 Teaspoon
|Onion powder
|1⁄4 Teaspoon
|Minced fresh garlic
|1⁄8 Teaspoon
|Onion slices
|2 , separated into rings
|Chopped celery
|1⁄4 Cup (4 tbs)
|Cod fillets
|1 Pound, cut into 4 serving size pieces (1/2 Inch Thick)
In small mixing bowl, combine all Garlic Mayonnaise ingredients.
Mix well.
In 9-inch square baking dish, combine onion and celery.
Top with cod fillets.
Pour milk over fillets.
Sprinkle with parsley and caraway.
Cover with plastic wrap.
Let stand o
Recipe Summary
Rate It
Nutrition Rank
Nutrition Facts
Serving size: Complete recipe
Calories 1175 Calories from Fat 806
% Daily Value*
Total Fat 90 g137.8%
Saturated Fat 8.5 g42.4%
Trans Fat 0 g
Cholesterol 273.6 mg91.2%
Sodium 783.9 mg32.7%
Total Carbohydrates 4 g1.3%
Dietary Fiber 0.98 g3.9%
Sugars 1.7 g
Protein 81 g163%
Vitamin A 14.8% Vitamin C 22.6%
Calcium 10.1% Iron 12%
*Based on a 2000 Calorie diet

subset: commoncrawl


text:
RIP Jonathan Winters thanks for all the laughs
April 12, 2013 at 10:29 am in News, Obituaries, People
Jonathan Winters passed away in quietly in his
Encino *home overnight. He was one of my favorite comedians. He excelled at improv, but he also was a scene stealer on TV and movies. His Web Site HERE, Wiki and IMBD. That should give you plenty to read, laugh and enjoy. A few more vids after the jump.
*PS Times issued a correction after the post went up that he died in his Montecito home, not the one in Encino.


text:
Seriously, we need to vote our fingers off for Eric O'Flaherty. As often as possible, with as many different email addresses as necessary, we need to ensure his win. He is wonderful and deserves ~all~ the awards.
Well, except the ones the other Braves are up for too. Like, how could you not vote for Meds? Simba? Freddie? JHey's gold glove performance?


text:
Quick Mackerel Pate
|Skinless smoked mackerel fillet
|9 Ounce (250 Gram)
|Plain low-fat yogurt
|2⁄3 Cup (10.67 tbs) (A Generous Amount)
|Chopped fresh parsley
|1 Tablespoon
|Lemon juice
|1 Tablespoon
|Finely grated lemon rind
|1⁄2 Teaspoon (From 1/2 Lemon)
|Freshly ground black pepper
|To Taste
|Lemon wedges
|4 (To Garnish)
|Fresh parsley sprigs
|6 (To Garnish)
|To serve:
|Red bell pepper
|1 , seeded and cut into chunky strips
|Yellow bell pepper
|1 , seeded and cut into chunky strips
|2 , cut into strips
|Celery stalks
|2 , cut into strips
|White bread slice/Whole wheat bread slice
|5 , toasted and cut into triangles
1. Remove and discard any remaining bones from the mackerel fillets and put the fish into a small bowl. Mash the fish with a fork and combine with the yogurt, parsley, and lemon juice and rind. Season to taste with pepper.
2. Divide the pate between 4 ramekins. Cover and let chill until required or serve at once.
3. To serve, garnish the pate with lemon wedges and parsley sprigs and serve with the prepared vegetables and toasted bread.
Recipe Summary
Rate It
Nutrition Rank
Nutrition Facts
Serving size: Complete recipe
Calories 1264 Calories from Fat 585
% Daily Value*
Total Fat 64 g98.3%
Saturated Fat 1.7 g8.5%
Trans Fat 0 g
Cholesterol 9 mg3%
Sodium 826.3 mg34.4%
Total Carbohydrates 101 g33.5%
Dietary Fiber 13.3 g53.2%
Sugars 23.8 g
Protein 71 g141.9%
Vitamin A 538.1% Vitamin C 775.2%
Calcium 42.7% Iron 20.3%
*Based on a 2000 Calorie diet


text:
FREE Shipping on Orders Over $100 Earn 3.5% with All-Star Rewards
This item is In-Store Pick-Up only.
The Thule Force M cargo box offers an affordable way to carry your gear. Shorter and wider than it's Alpine counterpart, the Force M will carry a variety of household/everyday items securely.
Great for duffle bags, carry on type luggage and bigger items like gardening equipment, this Thule box will give you the space you need inside your car and keep your items protected from the elements.
Features include:
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text: OverviewBack to top Champion Performance - Proflex Joint Support Formula - 60 Tablets Item# :57854UPC# :027692134509 Brand:Champion Performance Size/Form:60 Tablets Servings:15 Dosage:4 Tablet(S) Dietary Supplement. Connective tissue and joint support. Helps to reduce inflammation and stiffness. Willow bark.» Chondroitin.» Glucosamine.» MSM.» Curcumin. Few things can be as frustrating or damaging to your life and your game as joint problems. That's why Champion Proflex goes beyond simple glucosamine and chondroitin formulas. By also including such ingredients as willow, curcumin extract and omega fatty acids, Champion Proflex addresses connective tissue and joint support while helping reduce inflammation and stiffness. (These statements have not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure or prevent any disease.)


text:
A woman has died after becoming trapped in a sea cave off the Dorset coast yesterday afternoon.
Rescue teams were called after walkers spotted a man in the sea close to Tilly Whim Caves. Once airlifted to safety, he told the coastguards that his sister had become trapped in a tiny cave that could only be accessed underwater or through a tiny blowhole.
The woman was alive when rescuers arrived on the scene but treacherous conditions prevented them from getting to her.
In an online incident report, Swanage Coastguard, one of the teams that attended the scene. said: "Entry to the cave was either underwater, or through a narrow blowhole at the top of the cave.
"The rescue was considered to be at the very edge of our technical capability."
After over an hour of battling 50 mile per hour gusts of wind, a St Albans' Cliff Technician "showed exceptional courage" and decided to enter the cave through the blowhole. The woman had however died by the time the officer reached her.
"The lifeboat crews had tried to reach the woman through the opening in the front and entering the blowhole from the top was the last resort," a spokesperson for Portland Coastguard told the Dorset Echo.
"They had been communicating with the woman through the blowhole. Sadly, when the officer lowered down through the hole, it was too late and they couldn't get to her."Reuse content


text:
Tropical Fish Keeping - Aquarium fish care and resources (http://www.tropicalfishkeeping.com/forum.php)
- Beginner Freshwater Aquarium (http://www.tropicalfishkeeping.com/beginner-freshwater-aquarium/)
- - A few Questions (http://www.tropicalfishkeeping.com/beginner-freshwater-aquarium/few-questions-8128/)
A few Questions
Hello all,
I have a 75 Gallon Aquarium that I am setting up, I have had it for years but since Ive moved its been sitting empty. I have an AquaClear 500 filter and 2 Aquaclear 270gph powerheads for my under gravel filter from when I had gravel as my substrate. Id like to use sand this time around, so I dont think I am going to use the under gravel filter. Should I use an air pump setup with air stones? Can someone point me in the right direction? I will have live plants in there and most like American Cichlids. Where do I begin? Thanks.
Re: A few Questions
What American cichlids are you referring? Angels, discus, rams and apistogrammas are a few indestructive cichlids. They shouldn't bother your plants.
It is up to you whether you want to use the airpump or not. As for cycling, a sticky thread by fish_4_all is available in this section. API liquid test kit is recommended for best results. You will want zero ammonia and nitrites if you wish to keep fish. Definitely buy fish only after the cycling phase.
Do you have the heaters, thermometer and lighting now?:) Posting more details will definitely help.
Good luck.:)
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text:
Brumers Bikes
motorcycle accessories, motor cycles, Motorcycle Parts
Brumers Bikes can Offer Motorbike Servicing to Any Make Bike, Brumers Bikes can service Honda, Kawasaki, Suzuki, Yamaha, Triumph, BMW, Harley Davidsons, Scooters, Mopeds.Call Brumers Bikes NOW 01823 665100
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Triumph Servicing at Brumers Bikes, High standards at low prices.
Brumers Bikes can supply any Performance Accessory for your bike at Good Prices. Call Now 01823 665100 Mail Order Available
We can arrange for your bike to be MOT'd. and fix any problems that it may have. We will soon
Honda Servicing to a good standard and a good price.
Scooter Servicing with good value.
Motorcycle Diagnostics Work without the main dealer prices.
Triumph Servicing without the Main Dealer price.
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text:
about us
privacy policy
send email
site map
view cart
> Pepino Melon
Pepino Melon
Pepino Melon. "Pepino" means cucumber in Spanish. However, since the pepino is more like a melon, it is called pepino melon, melon pear or bush melon. But, in fact it is related to the tomato and the potato
The pepino melon is native to the temperate Andean regions of Colombia, Peru and Chile. The plant is not known in the wild, and the details of its origin are not known. The fruit is grown commercially in New Zealand, Chile and Western Australia.
The pepino melon plant or bush is about 1 m high and looks a lot like a potato plant. The flowers are small, blue, violet-purple or white marked with purple and they are similar to unopened potato flowers. The plant will not set fruit until the night temperature reaches above 18 °C.
The fruits show considerable diversity in the shape; some being oblong while others are pear or heart shaped. It is up to 15 cm long and 7 cm in diameter. The colour of the smooth skin is from pale green to golden yellow with purple stripes. The fruit flesh is greenish to yellowish-orange and very juicy. The taste is a combination of cantaloupe melon and a cucumber and not particularly sweet. The fruit flesh contains a lot of sweet seeds, which are edible.
The ripe fruit is generally eaten fresh like an apple. Both the skin and the fruit flesh can be eaten. It can, however, also be cut in halves and eaten like other melons. The unripe fruit can be baked like a squash.
Pepino Melon
Regular price: $39.99
Sale price: $29.99
Pepino Melon
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text:
Arike Ogunbowale leads Journal Sentinel's all-area team
Oak Creek's Steve Hluchnik is top coach
There are so many moments that go into winning a conference championship, but for Divine Savior Holy Angels this was the moment that tilted things in its favor.
The Dashers basketball team trailed Sussex Hamilton by as many as 11 points in the first half but rallied. In the fourth quarter, junior guard/forward Arike Ogunbowale, who had been contained to that point, made two steals that led to baskets and then drew a foul on a three-point shot in the final second. She hit two of three free throws with five-tenths of a second remaining to seal a 52-50 victory that helped DSHA win the Greater Metro title by one game.
Ogunbowale finished the night with 12 points and 12 rebounds and once again managed to make something happen for her team when it needed it most. It has become her calling card.
"I just think she can overtake a game," Oak Creek coach Steve Hluchnik said. "Whatever they throw at her, she still gets to the basket and scores."
Ogunbowale handled all the special attention and junk defenses yet still managed to average 22.7 points, 12.3 rebounds, 3.8 assists and 2.8 steals per game to claim her second straight Journal Sentinel area player of the year honor.
The award caps a year in which Ogunbowale also repeated as the Gatorade and Associated Press state player of the year. It also caps a season in which Ogunbowale won her first conference title.
How the team meshed was a highlight of the season for Ogunbowale.
"We lost two key seniors last year and five seniors total. We had a really young team — we lost two seniors this year — and our team clicked right away," she said.
The season also was marked by Ogunbowale becoming the school's all-time leading scorer and rebounder. She'll head into her senior season with 1,477 points and 692 rebounds.
She had a career-high 38 points plus 12 rebounds, two assists and three steals against Milwaukee Pius on Jan. 11. Pius got the victory, but the work it put into defense was symbolic of the lengths teams went to in an attempt to slow down Ogunbowale.
"We boxed-and-oned her. We doubled her and she still got 38 points," Pius coach Scott Herrick said. "If we played her straight up, she might have gotten 108."
Despite the attention Ogunbowale shot 50.7% overall (218 of 430) and 34.6% (36 of 104) from three-point range. This season she also managed to improve her rebounding from 9.0 to 12.3.
The season sets up a big summer for Ogunbowale. In addition to trying to gain a spot on USA Basketball's U17 team and playing on the U18 3x3 team for the second straight year, she presumably will make a college choice before the start of next season. Ogunbowale hasn't discussed her recruitment since tweeting her top 11 schools in the fall. Those schools were Connecticut, DePaul, Duke, Louisville, Marquette, Michigan, Notre Dame, Ohio State, Stanford, UCLA and Wisconsin.
She will play with the North Tartan, Minn.-based Nike Elite team during the off-season with an eye toward next prep season, when she'll play for a new coach at DSHA and have home games off campus while the school's gym is being rebuilt.
"There is going to be a lot of new stuff, so that will be exciting," she said.
Coach of the year: Steve Hluchnik, Oak Creek. The fifth year proved to be the charm for Hluchnik, whose team won the Division 1 state title after improving the past two seasons. Hlucknik said the key was a 39-36 victory over Pius on Jan. 21, a reversal of fortune from the team's losses earlier in the season to Pewaukee and Kimberly.
"I think that at least gave us some confidence that we could win some close games down the stretch," he said.
Oak Creek finished with 17 straight victories after two close loses to Pewaukee and Kimberly. It went 26-2 overall. Its non-conference slate featured eight games against teams that finished first or second in their conference. Pius and Kimberly reached the state tournament. Brookfield Central made it to the sectional finals.
Hluchnik's record is 105-25 at the school.
"Look at their schedule," Brookfield Central's Dan Wandrey said. "He knew what they needed and he didn't shy away from anybody. He had them playing best at the right time."
Access scores, schedules, rosters, statistics and more from area high school sports teams.
Stats Leaders


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text:
Without love, we are birds with broken wings.Albom, Mitch
\\\"Without love, we are birds with broken wings.\\\"Albom, Mitch
Happy and thrice happy are those who enjoy an uninterrupted union, and whose love, unbroken by any sour complaints, shall not dissolve until the last day of their existence.Horace
Love is a promise delivered already broken.Steve Martin
"To be commanded to love God at all, let alone in the wilderness, is like being commanded to be well when we are sick, to sing for joy when we are dying of thirst, to run when our legs are broken. But this is the first and great commandment nonetheless. Even in the wilderness - especially in the wilderness - you shall love him."Frederick Buechner
Poetry spills from the cracks of a broken heart, but flows from one which is loved.Christopher Paul Rubero
When love is lost, do not bow your head in sadness; instead keep your head up high and gaze into heaven for that is where your broken heart has been sent to heal.Unknown
Have we not come to such an impasse in the modern world that we must love our enemies - or else? The chain reaction of evil - hate begetting hate, wars producing more wars - must be broken, or else we shall be plunged into the dark abyss of annihilation.Martin Luther King Jr 1929
But to see her was to love her; Love but her, and love for ever. Had we never lov'd sae kindly, Had we never lov'd sae blindly, Never metor never parted, We had ne'er been broken-hearted.Robert Burns


text:
Android Programmer - develop database offline data entry program for tablet
This project received 25 bids from talented freelancers with an average bid price of $646 AUD.Get free quotes for a project like this
Project Budget$30 - $250 AUD
Total Bids25
Project Description
Hi programmers..
I am looking for a quote on what it would cost to build an offline 'sqlite/access' database for an android tablet for data entry in the field and export to CSV.
This is currently done using a windows tablet and access forms but looking to use android, so basically what I'm looking for a style of access database on an iPad.
Project Setup (first page):
[Project Name] is the primary key
Program Setup:
1. Current Project Selected (Dropdown Box)
2. Add new Project
Export Function
1. Select project to export >
2. Select Log number to export (or export all by creating separate files with file name of 'log number' as ZIP) >
3. Run Export to CSV file on local device or Run Export to EMAIL (calling general function on local device)
Delete Function:
1. Delete log number under project
2. Delete entire project (if conation's no 'log numbers')
Project Information Section (For Selected Project)
Each database is entered under a 'log number' (you can have several 'log numbers' under a project - in that 'project name' is a folder and 'log number' is the files inside it)
Project Setup:
1. Current Log Number Selected
2. Add/Change Log Number
This will be the header/setup page containing:
Project setup information to contain total of ~30 fields comprising of mixture of free text entry, small text dropdown (from hard coded list of 5 items) date picker & numerical entry and free comments box. All data is saved on entry (like Access)
Project Section's 1 to 5 (Data Entry Forms)
Each project section (1 to 5) is its own table and is to be exported as a separated CSV (with ProjectName_Log_number [url removed, login to view] for example)
Each data entry form is linked by the "form record number" that is selected (different to log number) - and is only per project section. Form record are incremental and you can move back and forward between them by pressing and you can press ' table view' to see all the text entries as an access style table showing all the form numbers. I.e. basically the same as an access form with the selector at the bottom!
The program will have a hard-coded lookup dictionary in the form of 4 character code and code description (but only store the 4 character code). I suggest the use of AutoCompleteTextView combined with Cursor (as here [url removed, login to view] ) for this - so that data can be selected via spinner, but also selected by entering the first few letters of the code, but also only permitting entry of only 'codes' that exist in the code dictionary.
Each section will have about 5 'pages' (on a standard sized tablet) with 4-6 groups of data entry fields… these data entry fields will mostly be 1 line 'autocompletetextview' dropdowns for selecting a 4 character code.
For example on the first page, will have a "location" group that will have a autocompletetextview dropdown list under it with the name "altitude" that is 1 line and 4 characters wide … when clicking on this field you can select [HIGH - 'High Altitude'] but only the code "HIGH" is stored - description is necessary in the autocompletetextview so the user knows the meaning of the particular code.
At the end of each section it has a 'save record' button that could run some validation (ie required fields are entered) so only records with validated information are saved… when user presses it prompts to save a record if data is entered or discard it.
There will be 5 entire sections for data entry, stored as different tables.
I would provide a full design of what this should look like, validation etc - at the moment looking to get a quote.
Skills Required
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- Outline your proposal
- Get paid for your work
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text:
Less Than Model Behavior at Phoenix Fashion Week
Who knew the fashionably chic were inclined to be so fashionably wasted? Maybe it was the "party all night" atmosphere or the seemingly neverending stream of martinis pouring out of Scottsdale's famed Valley Ho this past Friday, but there was a lot of elbowing, a lot of cussing (even in the ladies room, where a woman apologized for using the word "motherfucker"), and a lot of slurred phrases. You thought what about that dress? It was "fantashbuloshus"??
The right way to do Phoenix Fashion Week: dress chic, smile pretty and sip cocktails slowly.
Cute casual wear like this Route 66 pink tee from local designer Kiss The Girl was the norm at Friday's fashion show, which focused on athletic gear, t-shirts and jeans. KTG's other items included flirty, hippie-chic printed dresses and babydoll tops and graphic tees with peace signs and hoot owl appliques. We scored a fun horseshoe tee with the slogan "I Make Luck" from Kiss the Girl's Scottsdale Fashion Square kiosk just in time for a Vegas trip a few months ago. No big wins at the slots, but we sure got compliments on the shirt.
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Help! My teen daughter is a witch
- AnonymousJune 11, 2016
شركة القصر الذهبي لخدمات التنظيف
يسر شركة القصر الذهبي لنقل لاثاث ان تقدملكم ارقي خدمات نقل العفش والتنظيف داخل المملكة عن طريق فرق علي مستوي عال من الاحترافية والخبرة وباستخدام احدث الادوات والمعدات شركة تنظيف بالمدينة المنورة
شركة تنظيف بالدمام
شركة تنظيف بالرياض
شركة تنظيف بالمدينة
شركة تنظيف بجدة
شركة تنظيف كنب
غسيل خزانات بالمدينة المنورة
غسيل سجاد وموكيت بالمدينة المنورة
غسيل فلل وعمائر بالرياض
غسيل فلل وعمائر بالمدينة المنورة
غسيل كنب بالمدينة المنورة
شركة تنظيف بالمدينة المنورة
تنظيف فلل بالمدينة المنورة
شركة رش حشرات بالمدينة المنورة
شركة مكافحة حشرات بالمدينة المنورة
شركة نقل عفش بالمدينة المنورة
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- Lulu MoonApril 21, 2015
As a former Christian who is strongly off-put by most Christian articles about pagan religions/practices, I found this article to be very refreshing. While there are a few small inaccuracies in the depiction of Wicca, you got most of the basics right, and more improtantly, you refrained from any vilifying or fear mongering, which I greatly appreciate. It's also nice that you added that Wiccans don't worship Satan, since that's often how Christians portray witches, in an attempt to cause fear. And most importantly, you advise teaching children to approach those with different beliefs with love and kindness, not condemnation. I hope that one day, when my daughter has a discussion about beliefs with a Christian, they treat each other with kindness and respect like you've described here. Blessings!
- Joanna ScarlettNovember 7, 2014
You make Wicca seem as if it is a bad thing which it is not. It actually connects you closer to your surroundings and opens your eyes to things you never noticed before. I used to be Christian but I was being bullied and rejected at church so I slowly drew away from the Christian religion. Treat others as you would treat yourself? I prefer the "An' ye harm none, do as ye will" That basically says if it doesn't hurt others then go and do it if you want. I am now a full Wiccan, but I still have Christian ties since I had been Christian my entire life. Wicca is not bad thing, it is a new experience. You must learn to accept that not everybody is going to accept your beliefs and you can't shove it down their throats. Learn more about what we believe in and you will see we are a peaceful religion.
- Krystle GilesMay 2, 2014
You obviously haven't studied properly, either that or shifted what you have researched to suite your biblical based website. Not all witchcraft practitioners are Wicca and not all Wiccans are witches. For starters, one is a path or type of study whilst the other is an actual religion. I am not a Wiccan but my father is and I know that they have their own Rede, their own set of ethics and in both the Witchcraft practices and Wicca, we honor both feminine and masculine aka: The Gods and the Goddesses. Some people in our belief systems also are what is known as 'Christian', 'Catholic' witches who use their faith into witchcraft practices because they feel that that sort of God is a good deity for them.
- Therese MareNovember 18, 2013
The Wiccan faith or "religion" is frighting to the uninformed. I was a Christian for a long time and then about 10 years ago I was introduced to Wicca by a good friend (a male witch). I started studying it.The more I read up on it the more it became clear to me that it definitely the opposite of what I thought it was. I am a mother of 4 sons and as a Christian I was very strict. My adult sons still teased me about the amount of books and Cd's I burnt because i thought it was 'demonic' :) All I can ask is that you read about Wicca, the Three Fold Law and the Wiccan Rede. Have a look at this website. It explains beautifully what and what Wicca is not. http://wicca.com/celtic/wicca/wicca.htm Blessed Be
- Lost DaughterJune 12, 2013
This may seem strange at first, but as a wiccan I want to thank Katharine for writing this article. I was raised a Jehovah's Witness and in my young adulthood became interested in paganism in general and wicca specifically. I was ostracized by my church community and disowned by my mother. They were constantly accusing me of being a satan worshipper and were convinced that I was possessed by a demon. My mother demanded that I be evaluated by a psychologist because in her mind the only reason to question the church was if you were insane. I tried to be a calm, reasoning adult and even submitted myself to psychoanalysis. When the therapist declared me sane and well adjusted she accused the therapist of being in league with the devil as well. My therapist then introduced me to the cycle of abuse and opened my eyes to the cult-like similarities of the Jehovah's Witness church. I have now been pagan for 15 years and am happy in my own spiritual path. What I wish to express here is the hope that other young women will not be subjected to spiritual abuse and controlling tactics by well meaning but over zealous family members. Katharine has listed some excellent tactics for relating to would be pagans with respect and love. Offer your support and guidance, mostly importantly your love, and allow them to make their own informed choice. Although you may not like their choice, their life path is their own.
- Tuesday WilliamsApril 25, 2013
You know, you talk about witchcraft as though only females can practice it. There are plenty of men who are witches (not "warlocks" or "wizards", but witches). Furthermore, I think that a clearer line needs to be drawn between witchcraft and Wicca. They are two separate ideas; one is a skill, the other is a religion. While they often go hand-in-hand, there are plenty of witches who are not Wiccans. They can be Buddhist, Muslim, Christian, Pagan, or whatever they choose. The practice of witchcraft itself is not a religion. I, myself am a general Theist with both Christian and Wiccan influences. I understand your point of view here, but please make sure that you get your facts straight. Remember that not everyone in the world has to be a Christian! Blessed be! ☆
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text:
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Despite its superficial resemblance to the Lamborghini Gallardo, the 2008 Audi R8 has its own sense of style. With its mid-body-mounted V-8 engine clearly visible (and illuminated by LED lights at night), it's reminiscent of the Ferrari F430, according to Car and Driver, which describes this Audi as being "as much aluminum sculpture as it is machine." According to Cars.com, the 2008 Audi R8 doesn't roll, it stalks. "And when it stalks toward you, it awakens the senses. It stirs the emotions."
Inside, Forbes Autos describes the R8 Audi's cockpit as "minimalist and no-nonsense," while Automobile calls it "somewhat overstyled."
TheCarConnection.com has little doubt after viewing this 2008 Audi R8 that it was designed to be looked at as much as it was to be driven.


text:
Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis
- Mitchell J Cohen†1Email author,
- Adam D Grossman†2,
- Diane Morabito3,
- M Margaret Knudson1,
- Atul J Butte4 and
- Geoffrey T Manley3
DOI: 10.1186/cc8864
© Cohen et al.; licensee BioMed Central Ltd. 2010
Received: 4 August 2009
Accepted: 2 February 2010
Published: 2 February 2010
Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome.
Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality.
We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters.
Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.
The modern intensive care unit (ICU) is awash in a continuous stream of multivariate data produced from multiple monitors, ventilators, laboratory data and medical staff documentation. The dramatic increase in available information has led to an ICU that is very data-rich. The trauma and critical care communities have turned to these monitors and the data they produce to better understand post-injury physiology and guide resuscitation and treatment. Despite the improvements in, and increasing reliance on monitoring technology, these multivariate data (EKG, arterial blood pressure, ventilator information, and so on) are still recorded intermittently in many ICUs, often as infrequently as every hour, onto a paper chart. Even in ICUs where the paper chart has been replaced by a computerized medical record, these systems are not adequate for the tracking and analysis of complex multivariate relationships. Furthermore, this antiquated, non-relational system of data collection and presentation limits our ability to understand the complex relationship between variables and precludes longitudinal analysis of trends and developing patient pathophysiology. This results in care decisions that are too simplistic in nature. Indeed, most often care orders are written to restrict one variable to a given range (that is, give a fluid bolus for a systolic blood pressure <100) resulting in univariate treatment of complex multivariate physiology. A method to visualize and utilize complex multivariate data is needed, with the ultimate goal of identifying predictive patterns to protocolize and guide medical care. New applications of techniques in bioinformatics and data mining have been developed in the disparate fields of high throughput genomics, physics, and business data management that are aimed at dealing with these increasingly large and complex data sets [1, 2]. These data-intensive fields apply techniques such as hierarchical clustering, k-means clustering and self-organizing maps to permit pattern recognition in data sets that would otherwise be too complex to visualize. Investigations in genetic research use hierarchical clustering to group gene expression data according to patterns based on deviations from the mean or median. These clusters are then visualized as a heat map and dendrogram to highlight the similarity within clusters. This has led to an improved understanding of complex genomic interactions and the development of new tools for the diagnosis and management of human disease [3]. We sought to apply these techniques to the complex multivariate physiologic data collected from severely injured patients in a modern ICU.
Here we show that these clustering methodologies from bioinformatics are applicable to continuous rapidly changing multivariate physiologic data in critically injured patients, yielding important insight into patient physiology and outcomes. We define that at any time, the patient state is made up of a complex pattern of variables that together make up the resuscitative and metabolic milieu. We further hypothesize that these patterns are not easily discernable using traditional clinical measures of physiology. We define 10 patient states by applying hierarchical clustering to our multivariate ICU data. These states were then characterized based on clinical parameters and patient outcome. The states identified by clustering were not obvious by traditional physiological measures, yet they proved to have clinical prognostic value: time spent in some patient states was significantly predictive of subsequent mortality, the development of multiple organ failure, and infection. Furthermore, patients transitioned through multiple states during their ICU stay, reflecting changing post injury physiology and the effect of resuscitation and treatment. Together these findings demonstrate the potential of these techniques to integrate complex information and provide new insights in clinical care.
Materials and methods
Data collection
The study was approved by and conducted under supervision of the Committee on Human Research at the University of California San Francisco. Informed consent was obtained from patients or their surrogates per protocol. Physiological data were collected on 17 severely injured poly-trauma patients at one-minute intervals and stored in our Neurotrauma and Critical Care Database using a multimodal bio-informatics system (Aristein Bioinformatics, Palo Alto, CA, USA).
This system integrates continuous data from the bedside patient monitor (heart rate, oxygen saturation and Mean Arterial Pressure (MAP) with ventilator data and tissue oxygen measurements using a date and time stamp. Intermittent laboratory data, medications, and nursing interventions were derived from the computerized nursing documentation system (CareVue, Philips, Amsterdam, The Netherlands) and integrated with continuous data. Data were stored on a dedicated server in the ICU. Clinical blood gas sampling was supplemented for study purposes using a point-of-care analyzer (Opti CCA, Roche, Mannheim, Germany). Plasma lactate levels were measured (Roche Accutrend® Lactate point of care testing system, Mannheim, Germany). Microdialysis of the deltoid muscle was performed as part of a previously reported study [4] using the Licox® Oxygen Catheter (Integra Neurosciences, Plainsboro, NY, USA) to measure the partial pressure of oxygen in the deltoid muscle as continuous surrogate markers for splanchnic perfusion. Catheters and monitoring took place for seven days or until the patient was extubated.
Patients were selected as a sequential convenience sample but all were severely injured patients that required ICU admission and ongoing resuscitation. The patients were followed until discharge or death, and all complications, including infections and organ dysfunction, were documented in the study database. Infectious complications included bacteremia, urinary tract infection, wound infection, fungemia, sepsis, abscess, infected decubitus ulcer, infected hardware, meningitis, and osteomyelitis. The Multiple Organ Failure (MOF) Score was calculated as described by Ciesla et al [5]. The ordinal MOF score was converted to a binary outcome variable with MOF score ≥4 designated as Multiple Organ Failure. Other outcome variables were mortality and infection.
Hierarchical clustering
A total of 45 variables of physiological, clinical, and treatment data were collected every minute. For the clustering analysis we used only continuous variables for which the data were complete (heart monitor, ventilator, and microdialysis data), resulting in 52,000 points across 14 variables.
with di, jbeing the distance between observations i and j, n being the number of elements per observation, and xk, i/jbeing element k of observation i or j. These distances are calculated for every pair of observations, yielding m*(m-1)/2 distances for m observations.
with C(A, B) the distance from cluster A to cluster B. The maximum function indicates that we take the cluster distance to be the maximal distance between any two points in the cluster.
Univariate Linear Classifier
When using multidimensional analysis techniques, it is important to consider whether simpler univariate techniques could produce similar results. Therefore we attempted to train a univariate linear classifier using linear discriminant analysis (LDA) to classify our binary outcome. LDA produced an a posteriori that each data point falls under our outcome assignments.
In order to provide the LDA algorithm with the best possible chance of providing equivalent or better performance as the multivariate clustering we only use a single set of data rather than splitting our data into distinct training and test sets - a non-standard method that advantages the univariate method over the multivariate. We used all of the data that were input into the clustering algorithm as input into the LDA algorithm.
Between-cluster correlation analysis
We next calculated the Pearson correlation coefficients for each pair of variables within the clusters with the highest and lowest probabilities of death. Significance of correlations was determined using both bootstrapping and label shuffling resampling methods (10,000 iterations of each) to obtain a null distribution for the correlation coefficients. We then compared the corresponding correlation coefficients between the two clusters of interest.
Demographic data
Patient demographics
Gun shot wound
Pedestrians vs. auto
Other penetrating
MV/MC crash
Bike crash
Mean ± s.d.
Age (years)
38 ± 18
18 to 72
ICU length of stay (days)
24 ± 21
1 to 78
Hospital length of stay (days)
40 ± 42
1 to 172
28 ± 10
16 to 50
Injury sites (maximum AIS)
Number of patients
% patients
Hierarchical clustering
Clinical evaluation of clusters
Variable means ± standard deviation for each cluster
Heart Rate
PmO2 Temp
Lung Compliance
Minute Vol
Cluster 1
83 ± 13
99 ± 17
37 ± 15
37 ± 1
37 ± 12
8 ± 4
10 ± 2
99 ± 2
52 ± 19
3.7 ± 2.7
7.0 ± 2.3
7.4 ± 5.5
213.2 ± 25.2
0.016 ± 0.011
Cluster 2
82 ± 13
96 ± 21
36 ± 10
37 ± 2
36 ± 14
8 ± 3
10 ± 2
98 ± 2
55 ± 19
2.2 ± 0.7
7.2 ± 2.2
9.2 ± 4.4
113.9 ± 32.7
0.020 ± 0.014
Cluster 3
76 ± 16
102 ± 11
43 ± 13
37 ± 1
199 ± 49
5 ± 0
8 ± 2
100 ± 1
32 ± 5
6.2 ± 1.3
6.6 ± 0.1
5.6 ± 3.3
533.2 ± 28.0
0.012 ± 0.002
Cluster 4
82 ± 12
105 ± 28
31 ± 10
37 ± 1
41 ± 25
7 ± 3
9 ± 2
99 ± 2
45 ± 14
7.3 ± 2.1
6.8 ± 2.2
10.6 ± 15.1
523.4 ± 32.9
0.014 ± 0.004
Cluster 5
87 ± 17
101 ± 26
29 ± 11
36 ± 1
30 ± 12
8 ± 3
9 ± 2
98 ± 4
52 ± 18
7.4 ± 2.0
6.1 ± 2.0
12.4 ± 12.7
430.7 ± 30.0
0.017 ± 0.005
Cluster 6
84 ± 13
104 ± 16
32 ± 11
37 ± 1
34 ± 15
7 ± 3
10 ± 2
99 ± 2
46 ± 15
5.4 ± 2.1
7.0 ± 2.7
12.1 ± 10.5
322.4 ± 39.4
0.017 ± 0.007
Cluster 7
86 ± 2
89 ± 1
45 ± 7
38 ± 0
210 ± 63
4 ± 0
14 ± 1
96 ± 2
40 ± 0
1.1 ± 0.0
7.6 ± 0.1
8.5 ± 0.1
87.2 ± 0.6
0.013 ± 0.000
Cluster 8
81 ± 13
115 ± 11
37 ± 8
37 ± 1
38 ± 23
7 ± 3
9 ± 1
99 ± 1
42 ± 13
10.7 ± 2.7
6.4 ± 2.6
14.6 ± 16.2
697.3 ± 60.0
0.015 ± 0.003
Cluster 9
76 ± 13
109 ± 11
32 ± 8
37 ± 1
34 ± 15
6 ± 1
9 ± 2
99 ± 2
40 ± 9
11.8 ± 2.8
7.9 ± 4.8
11.6 ± 11.3
847.5 ± 51.8
0.013 ± 0.003
Cluster 10
96 ± 25
104 ± 4
23 ± 3
37 ± 1
29 ± 5
5 ± 0
9 ± 2
99 ± 1
41 ± 8
12.3 ± 2.6
11.9 ± 2.9
30.4 ± 26.5
989.5 ± 48.3
0.012 ± 0.003
Univariate linear classifier
To test whether individual variables were individually statistically significant predictors of outcome we performed Linear Discriminant Analysis (LDA). LDA shows that no single variable was capable of correctly predicting patient outcome significantly better than the chance level of 10.8%. In fact, all but two variables failed to correctly classify a single data point as belonging to a patient who died. The ability of the classifier was poor enough that its optimal strategy was to call every data point as coming from a patient who lived, resulting in an error rate of 10.8%. Even the best classifier (for PmO2 Temp) was an inadequate predictor and generated an error rate of 8.5%. This shows that none of the variables are composed of two distinct normally distributed populations with significantly different means and hence are by themselves not predictive of outcome.
Cluster assignment over time
Cluster representation of novel physiological relationships
Several variables showed no correlation or difference between clusters 1 and 4. For example, as expected, compliance and mGlucose were not correlated in either cluster (Figure 6a). This makes physiologic sense as there should be no obvious correlation between these disparate variables, and indeed we can determine no reason a relationship between these variables should be reflected in patient outcome. Furthermore, these two variables were not closely clustered in the physiologic variable dendrogram (Figure 1). Another pair of variables with minimal correlation and no discrimination between outcome clusters is PmO2 and mGlutamate (Figure 6b).
Other pairs of correlations represent pertinent physiology that should be similar in patients with any outcome; the strong correlation between mLactate and the ratio between muscle lactate and pyruvate (mLP) is similar in clusters 1 and 4. (Figure 6c). This represents what we know physiologically to be true, namely that as anaerobic respiration takes place there is an increase in both lactate production and pyruvate consumption, resulting in an increase in mLP. Figure 6d also shows a similarly strong positive correlation between FIO2 and PEEP, both variables that clinicians adjust to the degree of physiologic derangement. Close correlation between the variables and similarity between the clusters makes sense, as these parameters are usually adjusted in an identical direction depending on pulmonary physiology.
While these results provide good evidence that the clustering process is physiologically meaningful, we next looked for correlations that were disparate between clusters. Figure 6e shows the correlation between PMO2 and mLactate. In cluster 1 there exists the expected correlation of increasing lactate with reduced oxygen. This is in keeping with the relationship between muscle oxygen and lactate that our group has previously described [4]. In the cluster that represented patients who died, however, this basic physiologic effect was lost. Indeed, the correlation between muscle oxygen and lactate was very small, indicating the possibility of cellular or sub cellular (mitochondrial) metabolic dysfunction. Lastly, the opposite direction of the correlations between MAP and HR shown in Figure 6f clearly reflect differences between under resuscitated/critically ill patients and those more likely to survive.
We have shown here the utility of hierarchical clustering as an unsupervised non-linear classification schema in the prediction of outcome in severely injured trauma patients. We obtained clusters that were enriched for patients who died, contracted an infection, and suffered multiple organ failure. These clusters were not merely dominated by a few specific patients with a particular outcome. Indeed each of the clusters was made up of multiple patients' data and each patient transitioned through multiple clusters during their ICU stay. Lastly, the prognostic information incorporated in the clustering results was not obtainable by univariate traditional statistical analysis and persists in the face of univariate analyses that could not predict any of these outcomes.
Despite the near continuous monitoring of many physiologic variables and treatment parameters, traditional care in the ICU fails to fully use all these data in an efficient manner. Currently, clinicians base understanding of patient state and appropriate manipulation of that state on intermittent examination of patient variables (vital signs, labs, studies and physical examination). It has been shown, however, that more frequent data collection and analysis better defines patient physiology [6], and there has been much work in using continuous data, including the alarms built into the standard ICU bedside monitors [7, 8]. While these monitors are excellent as instant alarms regarding critical parameters, they do nothing to help predict long-term outcomes. Improvements in diagnosis and care have traditionally resulted from both improved clinical acumen and scientific advancement, mostly surrounding scientific examination of a single or small group of adjuncts. Indeed, the critical care literature is full of examinations of monitors, scoring systems, measurements and biomarkers, all of which seek to define and predict the degree of injury, physiological insult and resuscitation [8, 9]. Despite this proliferation, multivariate understanding of resuscitation state and identification of occult hypoperfusion remain elusive and an open experimental question. Multivariate decision tools using supervised learning algorithms have been implemented to detect hypovolemia [10] and alarms for critical care patients [8]. In contrast to our current work, this previous work used relatively few types of data (five and nine, respectively), giving a less complete picture of the patient's physiology. Additionally, multiple logistic regression models have been shown to predict MOF 12 hours post-injury [11], but these suffer from the inability to discover new physiology or make use of complex multivariate physiological relationships. In ground breaking work in the mid 90s Rixen and collegues utilized K-means clustering to define patient states based on 17 non-continuous variables. Through clustering and comparison to reference states (derived from non-injured controls) this group elegantly proposed that patient state could be defined in multidimentional state space [12, 13]. This work represented the first attempt at defining patient state as a multivariate entity. Here we extend these analyses using continuous data with no a priori understanding of the relationship between these data and outcome. We then extend these analyses by tracing patient state through the state space over time.
The use of unsupervised learning with large multivariate data sets comprised of continuous data represents a rarely used combination of techniques to predict and improve patient outcomes. Nelson et al. [14] used self-organizing maps to visualize patterns in microdialysis data from patients with traumatic brain injury, finding that individuals were likely to cluster together, in contrast to our results showing much movement among clusters. The work presented here extends previous observations from our group that employed methods similar to those we report here, except that they used aggregate data from each patient rather than q1 minute data, and our methods provide predictions of outcome in addition to the clinical insights discussed by the authors [15]. To fully utilize our data, we required a technique to distill all variables into a meaningful single value - in this case, a patient state. This could then, in turn, be defined in terms of clinically relevant patient outcome or physiologic state, as we have done here by associating each cluster with the probability of an outcome. Instead of fixation on one or a few physiologic parameters, transformation of all data into a single reproducible and clinically relevant value allows all available data to be used simultaneously. Furthermore, the complex relationships among multiple variables are preserved and exploited. Our analysis has shown that without inputting any prior knowledge, unsupervised algorithms are able to discern data (unobtainable by traditional statistics) that are indicative of death, infection, and MOF. With our data obtained every minute, the fact that patients transition through many clusters throughout their observation period attests to rapidly changing complex physiology. We have demonstrated our ability to both define patient state using hierarchical clustering and to track the progress of individual patients through these clusters over time. Indeed, patients tend to move between clusters during their stay, and we would expect most of them to experience under-resuscitation during part of their first 24 hours of care. Future analysis could reveal the potential of assigning transition probabilities between clusters based on physiology, which combined with knowledge of the likelihood of death in each state suggests potential methods of steering the physiology away from clusters with high mortality towards clusters associated with safety. The ability to do this in real time would greatly improve patient care decisions, leading to potentially enormous gains in outcomes.
We acknowledge that our results are dependent on our choice of similarity measure and clustering method. Our choice of Euclidean distance is natural for the problem at hand, as we were interested in the similarity of all variables to each other, not in how they varied with each other. Though the techniques of traditional linear statistics, correlation and regression analyses, can reveal differences between groups or correlations between pairs of physiological variables, we have shown here that they do not easily define a state made up of many variables with complex interrelationships.
There are several limitations to this preliminary study. First, the analysis here is based on a limited number or patients (17) and data points (52,000). Future studies should incorporate more patients (and more data) representing the primary outcomes. While a potential criticism is that a few clusters were dominated by the few patients with poor outcome, resulting in an overfit model, we stress that the clusters were defined in a way blind to patient outcome yet remained enriched for those outcomes.
Our results, while novel, represent a proof of concept study to show that cluster analysis can reveal complex patterns and predict outcome. Even so, we remain aware that to test the general applicability of these results, future studies will have to use a training data set to produce clusters/states that would then be applied to a test data set from separate patients. While we have tried to address the limitations of our single set data and the existence of serial dependence of data points using bootstrap analysis and by showing that each state was populated by data from many patients, future studies can conclusively address these concerns with separate training and test data sets. It also remains unclear how to select the correct number of clusters. As there is little guidance in the literature and these analyses have never been attempted in this manner we selected 10 clusters as a trade-off between inter- and intra-cluster distance and a usable number of patient states for analysis. Future studies could easily compare the prognostic information obtained from more or fewer clusters thereby discerning the correct number of states for a similar analysis.
Lastly, while our current work is limited to retrospective assignment of data to clusters, future work should include developing a single score that indicates both the patient's current state and their likelihood of dying during their hospital stay.
In summary, we have shown the applicability of hierarchical clustering to physiological data to a much greater degree than previous work. We have shown that we can make predictions of outcome and model physiology simultaneously - without specifically including any of our outcome measures in the analysis. Delving into the clustering results enabled us to learn more about the changes in physiology that are more representative of patients dying or living than could be determined using all the data, in aggregate form, from individual patients who lived or died. Comparing correlation coefficients of matching pairs of variables between clusters revealed differences predictive of life and death and disparate physiologic relationships depending on injury and resuscitation state. These insights into physiology also suggest new experiments to determine whether these results hold for larger populations than our polytrauma patients. While preliminary, this analysis shows that complex techniques can improve classification and prediction for severely injured trauma patients. This provides the groundwork for our eventual goal of using automated data-driven methods to provide real time classification and clinical decision support, radically improving outcome for critically ill and injured patients.
Key messages
Patient states are comprised of complex relationships of constantly changing physiology which are not otherwise discernable to clinicians.
These states can be defined using ICU data capture and cluster analysis and are enriched for outcomes.
Patients transition between states based on their injury patterns and resuscitation state.
Further studies are warranted to explore real time predictive monitoring of patient state, state transition and clinical decision support toward improved outcomes.
emergency department
intensive care unit
linear discriminate analysis
mean arterial pressure
multiple organ failure
positive end expiratory pressure
- PmO2:
partial pressure of muscle oxygen.
The work was performed at the Departments of Surgery and Neurosurgery at San Francisco General Hospital, University of California San Francisco, CA. The study was supported in part by NIH K08 GM-085689 (MJC) RO1 NS050173 (GTM) UC Discovery Grant GCP06 10226 (GTM, MJC DM), CDC R49/CCR903697-07 (MJC, MMK, GTM), Lucile Packard Foundation for Children's Health (AJB, ADG), and the Bio-X Graduate Fellowship (ADG).
Authors' Affiliations
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Which Joe gave his name to 'sloppy joes'? We look at five interesting sandwiches and their lexical origins.
Denoting or relating to a molecular structure in which two particular atoms or groups lie on the same side of a given plane in the molecule, in particular denoting an isomer in which substituents at opposite ends of a carbon–carbon double bond are on the same side of the bond.'the cis isomer of stilbene'Compare with trans
- 'But ultraviolet light converts the molecule to the cis isomer, in which both propellers are on the same side.'
- 'For example, the cis double bond at the centre of the fatty chain in erucamide and oleamide appears vital for slip performance.'
- 'As in our system, here again the cis isomer remains photoactive.'
- 'Examples of stereoisomers include the cis and trans isomers of the alkenes.'
- 'Greater reductions occur when cis double bonds are located near the middle of the acyl chains.'
Independent usage of cis-.
- 'we do not make arbitrary distinctions between trans and cis women'short for cisgender
- 'Cooper's take on masculinity is that all of us—male or female, trans or cis—take it for granted, fail to question it, and thus are "complicit" with it.'
- 'Trans people tend to be more aware of transphobia than most cis people are.'
- 'It's been really amazing to see the response from our cis allies against transphobia from parts of the radical feminist community.'
- 'To witness black cis women and trans women support one another is indeed a radical representation of the possibilities of black solidarity.'
- 'They're also implicitly acknowledging that gender is never fixed, it is never a constant for anyone, cis or trans.'
- 'I wasn't trying to set up a competition or hierarchy between trans and cis people.'
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