In [38]:
!pwd
/mnt/synology/retina/projects/bart/website
In [39]:
!ls
Parse+diag.bib.ipynb Scratch_Parse diag.bib.ipynb diag.bib
Rescale Photo.ipynb bibtex_parser.ipynb
In [112]:
!sudo pip install latexcodec
[sudo] password for user:
In [2]:
import latexcodec
with open('diag.bib', 'rb') as f:
diag = f.read().decode('utf-8-sig')
diag_lines = diag.split('\r\n\r\n')
In [3]:
def get_blocks(content, start_character, delim=('{','}')):
'''
yields all blocks (entries enclosed by the specified delimiters)
start_character will look backwards from the start of the block for this character
the result will be a tuple of two strings: from start character to start of the block, and the block content
'''
delim_start, delim_end = delim
stack = []
for i, c in enumerate(content):
if c == '{':
stack.append(i)
elif c == '}' and stack:
start = stack.pop()
if len(stack)==0:
start_index = content.rfind(start_character, 0, start)
yield content[start_index: start], content[start + 1: i]
assert [x for x in get_blocks('abc = {test}, bac = {test2}', 'a')] == [('abc = ', 'test'), ('ac = ', 'test2')]
In [4]:
def tokenize(string, delim=('{', '}'), trim=False):
'''
yields tokens instead of characters
everything enclosed by the delimitors is returned as one token
'''
delim_start, delim_end = delim
stack = []
if trim:
inp = string[1:-1]
else:
inp = string
for i, c in enumerate(inp):
if c == delim_start:
stack.append(i)
elif c == delim_end and stack:
start = stack.pop()
if len(stack) == 0:
if trim:
yield(string[start+2:i+1])
else:
yield(string[start:i+1])
continue
if len(stack) == 0:
yield c
assert [x for x in tokenize('a{abc}c', delim=('{', '}'))] == ['a', '{abc}', 'c']
assert [x for x in tokenize('{a{abc}c{def}gh{i}}', delim=('{', '}'), trim=True)] == ['a', 'abc', 'c', 'def', 'g', 'h', 'i']
In [5]:
def list_split(lst, token):
'''
splits a list on a token
yields individual parts of the list, split by the token
'''
last = -1
for i, t in enumerate(lst):
if t==token:
yield lst[last+1:i]
last = i
yield lst[last+1:]
assert [x for x in list_split([1, 2, 3, 4], 2)] == [[1], [3, 4]]
In [6]:
def token_split(token_list, pattern=' and '):
'''
splits a tokenlist on a pattern
yields individual parts of the tokenlist, split by the pattern
'''
pattern_index = 0
last = -1
for i, t in enumerate(token_list):
if t == pattern[pattern_index]:
pattern_index += 1
if pattern_index == len(pattern):
yield token_list[last+1:i-len(pattern)+1]
last = i
pattern_index = 0
else:
pattern_index = 0
yield token_list[last+1:]
assert [x for x in token_split([1, 2, 1, 'test', 2, 'test'], pattern = [1, 'test'])] == [[1, 2], [2, 'test']]
In [7]:
def rindex(lst, token):
'''
returns the last index of token in lst
'''
return next(i for i, v in zip(range(len(lst)-1, -1, -1), reversed(lst)) if v == token)
assert rindex('abc abc', 'a') == 4
In [8]:
def parse_name(name, omit=('{', '}')):
'''
assumes this format:
https://tex.stackexchange.com/questions/557/how-should-i-type-author-names-in-a-bib-file
cleans the string from characters in 'omit'
returns a tuple (first, von, last, jr)
'''
parts = list(list_split(name, ','))
if len(parts)==1:# "First von Last"
if ' ' in name:
s, e = name.index(' '), rindex(name, ' ')
else:
s, e = 0, 0
first = name[:s]
von = name[s:e]
last = name[e:]
jr = ''
elif len(parts)==2: # "von Last, First"
first = parts[1]
e = rindex(parts[0], ' ') if ' ' in parts[0] else 0
von = parts[0][:e]
last = parts[0][e:]
jr = ''
elif len(parts)==3: # "von Last, Jr, First"
first = parts[2]
e = rindex(parts[0], ' ') if ' ' in parts[0] else 0
von = parts[0][:e]
last = parts[0][e:]
jr = parts[1]
else:
print('warning! bibtex format error in name "{}"'.format(''.join(name)))
first, von, last, jr = '', '', name, ''
def clean(name_part):
return ''.join(letter
for token in name_part
for letter in token
if not letter in omit).strip()
return tuple(clean(x) for x in (first, von, last, jr))
assert parse_name('Bart Liefers') == ('Bart', '', 'Liefers', '')
assert parse_name('Bart von Liefers') == ('Bart', 'von', 'Liefers', '')
assert parse_name('Liefers, Bart') == ('Bart', '', 'Liefers', '')
assert parse_name('von Liefers, Bart') == ('Bart', 'von', 'Liefers', '')
assert parse_name('von Liefers, Jr, Bart') == ('Bart', 'von', 'Liefers', 'Jr')
In [9]:
def parse_authors(author_line):
'''
returns a list of author tuples
'''
author_line = author_line.replace('~', ' ')
# remove enclosing braces
try:
cleaned_line = next(get_blocks(author_line, ''))[1]
except:
print('error in author line: {}'.format(author_line))
cleaned_line = author_line[1:-1]
#split on ' and ' tokens (but not between brackets!) to split out the separate authors
authors = token_split(list(tokenize(cleaned_line)), pattern=' and ')
return [parse_name(author) for author in authors]
assert parse_authors('{a and bandc and d { and } e}') == [('', '', 'a', ''), ('', '', 'bandc', ''), ('d', 'and', 'e', '')]
In [10]:
def get_entry_content(content):
'''
returns a dict mapping the bib-keys to
'''
def get_key_value(lines):
for line in lines:
if not '=' in line:
continue
i = line.index('=')
key = line[:i].strip()
value = line[i + 1:].strip()
if value.startswith('{'):
value = value[:rindex(value, '}') + 1]
elif value.endswith(','):
value = value[:-1]
yield key, value
return {k: v for k, v in get_key_value(content.split('\r\n'))}
def get_entry(entry):
'''
returns a tuple: the bibkey and a dict containing the key-values in this entry
'''
key_index = entry.index(',')
bib_key = entry[:key_index]
content = get_entry_content(entry[key_index:])
return bib_key, content
In [11]:
from collections import defaultdict
In [12]:
def decode_latex(input_string, print_error_key=False):
'''
replace latex characters with unicode
'''
try:
return input_string.encode('utf-8').decode('latex')
except Exception as e:
if print_error_key:
print('{} : warning: encoding error!!!'.format(print_error_key))
print(e)
return input_string
In [13]:
def authors_to_string(authors):
def parse_author(author):
first, von, last, jr = author
if len(first)>=2 and first[1]=='.':
# first probably contains initials
initials = first
else:
initials = '.'.join(x[0] for x in first.split(' ') if x)
if len(initials):
initials += '.'
result = initials
if not von == '':
if len(von)>=2 and von[1]=='.':
# von probably contains some initials
result += von
else:
result += ' ' + von
result += ' ' +last
if not jr == '':
result += ' ' + jr
return result
names = [parse_author(a) for a in authors]
return ', '.join(names[:-1]) + ' and ' + names[-1]
def clean_bib_string(bib_string):
if not bib_string[0] == '{' and bib_string[-1] == '}':
print('unexpected content:', bib_string)
return ''.join(b for b in tokenize(bib_string, trim=True))
In [14]:
class BibItem:
url_syntax = {
'doi': 'http://dx.doi.org/{}',
'pmid': 'http://www.ncbi.nlm.nih.gov/pubmed/{}',
'url': '{}'
}
def __init__(self, key, entry, entry_type):
self.key = key
self.entry = entry
self.entry_type = entry_type
self.values = {}
def __getattr__ (self, key):
if key in self.values:
# memoization
return self.values[key]
if key == 'author':
result = self._get_authors()
elif key in ('journal', 'booktitle', 'title', 'series'):
result = self._get_string_rule_or_decode(key)
elif key in ('year', 'volume', 'pages', 'number'):
result = self._get_simple_value(key).replace('--', '-')
elif key in ('doi', 'pmid', 'url'):
result = self._get_url(key)
else:
result = ''
self.values[key] = result
return result
def _get_authors(self):
if not 'author' in self.entry:
a = []
a = parse_authors(decode_latex(self.entry['author']))
return authors_to_string(a)
def _get_string_rule_or_decode(self, item):
if not item in self.entry:
return ''
result = self.entry[item]
if result.startswith('{'):
return clean_bib_string(decode_latex(result))
else:
return result
def _get_simple_value(self, key):
if not key in self.entry:
return ''
else:
value = self.entry[key]
if value.startswith('{'):
return value[1:-1]
else:
return value
def _get_url(self, key):
url = self._get_simple_value(key)
if len(url):
return self.url_syntax[key].format(url)
return ''
In [15]:
def converter(value_convert, bib_item):
def get_val(k, v):
if not k in bib_item.entry:
return ''
return value_convert[k].format(get_from_string_rule(getattr(bib_item, k)))
return {k:get_val(k, v) for k, v in value_convert.items()}
def HTML_proceedings_formatter(bib_item):
value_convert = {
'booktitle': 'in: <i>{}</i>',
'volume': ', volume {}',
'series': ' of {}'
}
for k in ('year', 'number', 'pages'):
value_convert[k] = ', {}'
return '{booktitle}{volume}{series}{year}{number}{pages}'.format(**converter(value_convert, bib_item));
def HTML_abstract_formatter(bib_item):
value_convert = {
'booktitle': 'in: {}', # italics?
'year': ', {}',
}
return '{booktitle}{year}'.format(**converter(value_convert, bib_item))
def HTML_article_formatter(bib_item):
value_convert = {
'year': ' {}',
'volume': ';{}',
'number': '({})',
'pages': ':{}'
}
values = converter(value_convert, bib_item)
values['journal'] = ''
journal = get_from_string_rule(bib_item.journal)
if bib_item.journal.startswith('arXiv'):
arxiv_id = journal[:6];
values['journal'] = ', <a href="https://arxiv.org/abs/{}">{}</a>'.format(arxiv_id, journal)
else:
values['journal'] = ', <i>{}</i>'.format(journal)
return '{journal}{year}{volume}{number}{pages}'.format(**values)
def get_HTML_Thesis_formatter(name):
value_convert = {
'school': ', {}',
'year': ', {}',
}
def func(bib_item):
return '<i>{name}</i>{school}{year}'.format(name=name, **converter(value_convert, bib_item))
return func
def HTML_Patent_formatter(bib_item):
value_convert = {
'year': '{}',
'nationality': ', {}',
'optnumber': ', patent number {}'
}
return '{year}{nationality}{optnumber}'.format(**converter(value_convert, bib_item))
def HTML_formatter(bib_item):
type_formatters = {
'@InProceedings': HTML_proceedings_formatter,
'@Conference': HTML_abstract_formatter,
'@Article': HTML_article_formatter,
'@PhdThesis': get_HTML_Thesis_formatter('PhD thesis'),
'@Mastersthesis': get_HTML_Thesis_formatter('Mastersthesis'),
'@Patent': HTML_Patent_formatter
}
if bib_item.entry_type in type_formatters:
return type_formatters[bib_item.entry_type](bib_item)
In [63]:
from collections import Counter
In [64]:
Counter(v.entry_type for v in global_index.values())
Out[64]:
Counter({'@Article': 2903,
'@Book': 20,
'@Conference': 212,
'@Electronic': 1,
'@InBook': 2,
'@InCollection': 2,
'@InProceedings': 346,
'@MastersThesis': 4,
'@Misc': 3,
'@Patent': 3,
'@PhdThesis': 170})
In [16]:
index = defaultdict(dict)
global_index = {}
string_rules = {}
for type_name, entry in get_blocks(diag, start_character='@'):
if type_name == '@Comment':
continue
elif type_name == '@String':
k, v = [x.strip() for x in entry.split('=')]
string_rules[k] = v
else:
key, entry_dict = get_entry(entry)
bib_item = BibItem(key, entry_dict, type_name)
global_index[key] = bib_item
index[type_name][key] = bib_item
In [17]:
def find_key(text):
for k, bib_item in global_index.items():
if text in clean_bib_string(bib_item.entry['title']):
return k
In [18]:
find_key('Non-solid and Part-solid Nodules: Compa'), find_key('Automatic Cerebrospinal Fluid Segmentation')
Out[18]:
('Silv17a', 'Pate17a')
In [19]:
global_index['Pate17a'].entry_type
Out[19]:
'@InProceedings'
In [58]:
sorted(global_index.items())
Out[58]:
[('04', <__main__.BibItem at 0x7f5a67730d30>),
('04a', <__main__.BibItem at 0x7f5a67730f60>),
('Aald17', <__main__.BibItem at 0x7f5a676d77f0>),
('Aald17a', <__main__.BibItem at 0x7f5a676dcd68>),
('Aalt11', <__main__.BibItem at 0x7f5a7c05a668>),
('Aarn11', <__main__.BibItem at 0x7f5a7c05cb70>),
('Aarn12', <__main__.BibItem at 0x7f5a7c060898>),
('Aarn12a', <__main__.BibItem at 0x7f5a7c05c358>),
('Aarn12b', <__main__.BibItem at 0x7f5a7c05cfd0>),
('Aarn13', <__main__.BibItem at 0x7f5a7c05c780>),
('Aarn13a', <__main__.BibItem at 0x7f5a7c05aac8>),
('Aarn13b', <__main__.BibItem at 0x7f5a7c060470>),
('Aarn16', <__main__.BibItem at 0x7f5a7c0b5e48>),
('Aars89', <__main__.BibItem at 0x7f5a7c060c50>),
('Aart06', <__main__.BibItem at 0x7f5a7c066c88>),
('Aart06a', <__main__.BibItem at 0x7f5a7c063780>),
('Aart07', <__main__.BibItem at 0x7f5a7c0657b8>),
('Aart07a', <__main__.BibItem at 0x7f5a7c066470>),
('Aart08', <__main__.BibItem at 0x7f5a7c063b70>),
('Aart08a', <__main__.BibItem at 0x7f5a7c065be0>),
('Aart08b', <__main__.BibItem at 0x7f5a7c063f98>),
('Aart09', <__main__.BibItem at 0x7f5a7c0634a8>),
('Aart09a', <__main__.BibItem at 0x7f5a7c066048>),
('Aart10', <__main__.BibItem at 0x7f5a7c065400>),
('Aart12', <__main__.BibItem at 0x7f5a7c060fd0>),
('Aart99', <__main__.BibItem at 0x7f5a7c0bb5c0>),
('Abas05', <__main__.BibItem at 0x7f5a7c06b2e8>),
('Abas05a', <__main__.BibItem at 0x7f5a7c06b0f0>),
('Abbi06', <__main__.BibItem at 0x7f5a7c06b6d8>),
('Abee14', <__main__.BibItem at 0x7f5a7c06bb38>),
('Abel95', <__main__.BibItem at 0x7f5a7c06bba8>),
('Aben11', <__main__.BibItem at 0x7f5a7c06e0b8>),
('Abra08a', <__main__.BibItem at 0x7f5a7c06e3c8>),
('Abuh08', <__main__.BibItem at 0x7f5a6773c128>),
('Adri09', <__main__.BibItem at 0x7f5a7c0726d8>),
('Adri09a', <__main__.BibItem at 0x7f5a7c072ef0>),
('Adri10', <__main__.BibItem at 0x7f5a7c06ea90>),
('Adri11', <__main__.BibItem at 0x7f5a7c072ac8>),
('Adri11a', <__main__.BibItem at 0x7f5a7c06e7f0>),
('Adri11b', <__main__.BibItem at 0x7f5a7c072278>),
('Adri11c', <__main__.BibItem at 0x7f5a7c06ee10>),
('Aebe93', <__main__.BibItem at 0x7f5a7c073358>),
('Aert11', <__main__.BibItem at 0x7f5a7c073b00>),
('Aert12', <__main__.BibItem at 0x7f5a7c0736a0>),
('Aert14', <__main__.BibItem at 0x7f5a7c073ef0>),
('Ahlg10', <__main__.BibItem at 0x7f5a7c0762b0>),
('Akyi15', <__main__.BibItem at 0x7f5a7c076630>),
('Albe11', <__main__.BibItem at 0x7f5a7c076f28>),
('Albe12', <__main__.BibItem at 0x7f5a7c076b00>),
('Albe94', <__main__.BibItem at 0x7f5a7c078208>),
('Alex15', <__main__.BibItem at 0x7f5a7c0785c0>),
('Alon09', <__main__.BibItem at 0x7f5a7c0789e8>),
('Alta13', <__main__.BibItem at 0x7f5a7c078e10>),
('Altm97', <__main__.BibItem at 0x7f5a676c8048>),
('Amer13', <__main__.BibItem at 0x7f5a7c07b240>),
('Amin11', <__main__.BibItem at 0x7f5a7c07b6a0>),
('Amir13', <__main__.BibItem at 0x7f5a7c07b8d0>),
('Amir13a', <__main__.BibItem at 0x7f5a7c07bcc0>),
('Amir14', <__main__.BibItem at 0x7f5a7c07f0f0>),
('Ande05', <__main__.BibItem at 0x7f5a7c07f4e0>),
('Andr12a', <__main__.BibItem at 0x7f5a7c07f908>),
('Araz15', <__main__.BibItem at 0x7f5a676f9978>),
('Aren11', <__main__.BibItem at 0x7f5a7c081898>),
('Aren12', <__main__.BibItem at 0x7f5a7c081c88>),
('Aren13', <__main__.BibItem at 0x7f5a7c081470>),
('Aren15', <__main__.BibItem at 0x7f5a7c0850b8>),
('Aren16', <__main__.BibItem at 0x7f5a7c07ff28>),
('Aria04', <__main__.BibItem at 0x7f5a7c085cf8>),
('Aria06', <__main__.BibItem at 0x7f5a7c0858d0>),
('Aria13', <__main__.BibItem at 0x7f5a7c0854e0>),
('Arif14', <__main__.BibItem at 0x7f5a7c00b2e8>),
('Arif14c', <__main__.BibItem at 0x7f5a7c009e10>),
('Arif15a', <__main__.BibItem at 0x7f5a7c009978>),
('Arif15b', <__main__.BibItem at 0x7f5a7c00b748>),
('Arif16a', <__main__.BibItem at 0x7f5a7c0093c8>),
('Arif16b', <__main__.BibItem at 0x7f5a7c009198>),
('Arma08', <__main__.BibItem at 0x7f5a7c00bb00>),
('Arno16', <__main__.BibItem at 0x7f5a7c00d438>),
('Arno17', <__main__.BibItem at 0x7f5a7c00bef0>),
('Arnt15', <__main__.BibItem at 0x7f5a7c00d860>),
('Arnt16', <__main__.BibItem at 0x7f5a7c063710>),
('Arta09', <__main__.BibItem at 0x7f5a7c00df98>),
('Arta09a', <__main__.BibItem at 0x7f5a7c00dba8>),
('Arte12', <__main__.BibItem at 0x7f5a7c010400>),
('Arzh06', <__main__.BibItem at 0x7f5a7c010be0>),
('Arzh06a', <__main__.BibItem at 0x7f5a7c014240>),
('Arzh07', <__main__.BibItem at 0x7f5a7c012b70>),
('Arzh07a', <__main__.BibItem at 0x7f5a7c0124a8>),
('Arzh07b', <__main__.BibItem at 0x7f5a7c012208>),
('Arzh07c', <__main__.BibItem at 0x7f5a7c012f60>),
('Arzh09', <__main__.BibItem at 0x7f5a7c0145f8>),
('Arzh09b', <__main__.BibItem at 0x7f5a7c010e80>),
('Arzh09c', <__main__.BibItem at 0x7f5a7c010940>),
('Arzh10', <__main__.BibItem at 0x7f5a7c012748>),
('As09', <__main__.BibItem at 0x7f5a7c0149e8>),
('Ashr10', <__main__.BibItem at 0x7f5a7c014da0>),
('Asse11', <__main__.BibItem at 0x7f5a7c017198>),
('Aste08', <__main__.BibItem at 0x7f5a7c017550>),
('Aste15', <__main__.BibItem at 0x7f5a7c017940>),
('Atsm08', <__main__.BibItem at 0x7f5a7c017d68>),
('Atti11', <__main__.BibItem at 0x7f5a7c019128>),
('Avil17', <__main__.BibItem at 0x7f5a676dcf28>),
('Avoi13', <__main__.BibItem at 0x7f5a7c019550>),
('Ayez13', <__main__.BibItem at 0x7f5a7c019828>),
('Babo16', <__main__.BibItem at 0x7f5a7c01cb70>),
('Back09', <__main__.BibItem at 0x7f5a7c01f6a0>),
('Back10', <__main__.BibItem at 0x7f5a7c01f160>),
('Bagl13', <__main__.BibItem at 0x7f5a676d7978>),
('Bail16', <__main__.BibItem at 0x7f5a7c01fb70>),
('Bake15', <__main__.BibItem at 0x7f5a7c022160>),
('Bakk01a', <__main__.BibItem at 0x7f5a7c0225c0>),
('Bakk07', <__main__.BibItem at 0x7f5a7c022908>),
('Bala05', <__main__.BibItem at 0x7f5a7c022cc0>),
('Bald04', <__main__.BibItem at 0x7f5a7c025160>),
('Bald04a', <__main__.BibItem at 0x7f5a7c025550>),
('Bald05', <__main__.BibItem at 0x7f5a7c025978>),
('Ball15', <__main__.BibItem at 0x7f5a7c025c88>),
('Balm04', <__main__.BibItem at 0x7f5a7c0280f0>),
('Balo11', <__main__.BibItem at 0x7f5a7c028518>),
('Balo13', <__main__.BibItem at 0x7f5a7c0287b8>),
('Band17', <__main__.BibItem at 0x7f5a7c028c18>),
('Bank07', <__main__.BibItem at 0x7f5a7c0296d8>),
('Bank12', <__main__.BibItem at 0x7f5a7c029320>),
('Bank15', <__main__.BibItem at 0x7f5a7c028eb8>),
('Barb05', <__main__.BibItem at 0x7f5a676f9e10>),
('Bare07a', <__main__.BibItem at 0x7f5a7c02e6a0>),
('Bare11', <__main__.BibItem at 0x7f5a7c029b38>),
('Bare12a', <__main__.BibItem at 0x7f5a7c02ee80>),
('Bare13', <__main__.BibItem at 0x7f5a7c02c400>),
('Bare15b', <__main__.BibItem at 0x7f5a7c034278>),
('Bare16', <__main__.BibItem at 0x7f5a7c02ca90>),
('Bare16a', <__main__.BibItem at 0x7f5a7c034710>),
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In [61]:
entry.entry
Out[61]:
{'abstract': '{Gene therapy delivers a functional gene into a target cell to restore the physiological levels of the deficient gene (1, 2). This therapeutic methodology has been used in the clinic to treat diseases and cancers induced by genetic disorders (3). For example, a cytotoxic gene can destroy a specific type of cancer cell without excessive damage to normal tissue (4). Because viruses are inherently capable of packaging nucleic acids and delivering them to susceptible cells with high efficiency, they become a preferred system for natural gene therapy delivery (5). Viral vectors can be engineered with a gene expression cassette or converted to a targeted vector. Both methods allow delivery of the gene of interest (transgene) to the desired cells or tissues (3). As a gene therapy vector, the viruses need to meet three criteria: safety, high transfer efficiency, and reliable transgene expression. Assessment of the development of viral vectors in vivo becomes an important step in the implementation of gene therapy in the clinic. With its inherent high spatial resolution, magnetic resonance imaging (MRI) can be effectively used to examine the pharmacokinetics and development of viral vectors in vivo, especially their adsorption, distribution, biotransformation, and excretion. Baculoviruses (BV) are a family of rod-shaped viruses with a circular, double-stranded genome ranging from 80 to 180 kbp that can encode ~100?200 proteins (6). BV mainly replicates in insect cells, not in mammalian cells, through the function of a glycoprotein gp64 (512 amino acids) located on the viral envelop (7). BV can efficiently mediate gene transfer in mammalian cells in the presence of active mammalian cell promoters such as the cytomegalovirus promoter. The inherent inability of BV to replicate in mammalian cells makes it an attractive candidate for gene therapy (7) and for protein expressions such as ion channels, G-protein?coupled receptors, nuclear receptors, and transporters (5). As a gene delivery vector, BV has several unique features, including extremely high levels of gene expression and accessibility and an excellent biosafety profile (5). A BV with avidin is a recombinant BV that has avidin inserted into its native envelope glycoprotein gp64 (8). The presence of avidin on the surface of the BV provides a versatile platform, the avidin displaying BV (Baavi), for binding a variety of biotinylated molecules, including imaging probes (9). The insertion of avidin also increases the transduction efficiency of BV by 5?26-fold (8). Complexation of Baavi with biotinylated ultra-small superparamagnetic iron oxide nanoparticles (bUSPIO) forms an agent (Baavi-bUSPIO) used for MRI imaging of recombinant BV (9). The USPIOs contain an icosahedral core of superparamagnetic crystalline Fe3O4 (magnetite) (10). They possess a high magnetic susceptibility that results in a significant induced magnetization inside a magnetic field. This creates microscopic field gradients that diphase nearby protons and cause a shortening of T2 relaxation times (11). With a 50-nm USPIO and a virus of approximately 25 nm × 200 nm, each bUSPIO binds ~1?2 viruses. The Baavi includes a LacZ transgene, which is a gene for encoding of a common enzymatic reporter protein ?-galactosidase (?-gal) (12). The presence of ?-gal allows for quantitative measurement of transduction efficiency of Baavi-bUSPIO in vitro and/or histological evaluation of Baavi-bUSPIO in targeted tissues ex vivo.}',
'article': '{Avidin-coated baculoviral vectors-biotinylated ultra-small superparamagnetic iron oxide nanoparticles}',
'contribution': '{2008-03-31}',
'keywords': '{Baavi-bUSPIO; Protein, nanoparticle (virus); Other; Other; Magnetic resonance imaging (MRI); Iron oxides}',
'medium': '{Internet}',
'pmid': '{20641353}',
'publisher': '{National Center for Biotechnology Information (US)}',
'publocation': '{Bethesda (MD)}',
'pubstatus': '{ppublish}',
'pubtype': '{Review}',
'revised': '{2008-4-30}',
'sections': '{Background; Synthesis; In Vitro Studies: Testing in Cells and Tissues; Animal Studies; Human Studies; References}',
'title': '{Molecular Imaging and Contrast Agent Database (MICAD)}',
'year': '{2004}'}
In [60]:
entry.entry_type
Out[60]:
'@Article'
In [71]:
entry.entry
Out[71]:
{'abstract': '{Gene therapy delivers a functional gene into a target cell to restore the physiological levels of the deficient gene (1, 2). This therapeutic methodology has been used in the clinic to treat diseases and cancers induced by genetic disorders (3). For example, a cytotoxic gene can destroy a specific type of cancer cell without excessive damage to normal tissue (4). Because viruses are inherently capable of packaging nucleic acids and delivering them to susceptible cells with high efficiency, they become a preferred system for natural gene therapy delivery (5). Viral vectors can be engineered with a gene expression cassette or converted to a targeted vector. Both methods allow delivery of the gene of interest (transgene) to the desired cells or tissues (3). As a gene therapy vector, the viruses need to meet three criteria: safety, high transfer efficiency, and reliable transgene expression. Assessment of the development of viral vectors in vivo becomes an important step in the implementation of gene therapy in the clinic. With its inherent high spatial resolution, magnetic resonance imaging (MRI) can be effectively used to examine the pharmacokinetics and development of viral vectors in vivo, especially their adsorption, distribution, biotransformation, and excretion. Baculoviruses (BV) are a family of rod-shaped viruses with a circular, double-stranded genome ranging from 80 to 180 kbp that can encode ~100?200 proteins (6). BV mainly replicates in insect cells, not in mammalian cells, through the function of a glycoprotein gp64 (512 amino acids) located on the viral envelop (7). BV can efficiently mediate gene transfer in mammalian cells in the presence of active mammalian cell promoters such as the cytomegalovirus promoter. The inherent inability of BV to replicate in mammalian cells makes it an attractive candidate for gene therapy (7) and for protein expressions such as ion channels, G-protein?coupled receptors, nuclear receptors, and transporters (5). As a gene delivery vector, BV has several unique features, including extremely high levels of gene expression and accessibility and an excellent biosafety profile (5). A BV with avidin is a recombinant BV that has avidin inserted into its native envelope glycoprotein gp64 (8). The presence of avidin on the surface of the BV provides a versatile platform, the avidin displaying BV (Baavi), for binding a variety of biotinylated molecules, including imaging probes (9). The insertion of avidin also increases the transduction efficiency of BV by 5?26-fold (8). Complexation of Baavi with biotinylated ultra-small superparamagnetic iron oxide nanoparticles (bUSPIO) forms an agent (Baavi-bUSPIO) used for MRI imaging of recombinant BV (9). The USPIOs contain an icosahedral core of superparamagnetic crystalline Fe3O4 (magnetite) (10). They possess a high magnetic susceptibility that results in a significant induced magnetization inside a magnetic field. This creates microscopic field gradients that diphase nearby protons and cause a shortening of T2 relaxation times (11). With a 50-nm USPIO and a virus of approximately 25 nm × 200 nm, each bUSPIO binds ~1?2 viruses. The Baavi includes a LacZ transgene, which is a gene for encoding of a common enzymatic reporter protein ?-galactosidase (?-gal) (12). The presence of ?-gal allows for quantitative measurement of transduction efficiency of Baavi-bUSPIO in vitro and/or histological evaluation of Baavi-bUSPIO in targeted tissues ex vivo.}',
'article': '{Avidin-coated baculoviral vectors-biotinylated ultra-small superparamagnetic iron oxide nanoparticles}',
'contribution': '{2008-03-31}',
'keywords': '{Baavi-bUSPIO; Protein, nanoparticle (virus); Other; Other; Magnetic resonance imaging (MRI); Iron oxides}',
'medium': '{Internet}',
'pmid': '{20641353}',
'publisher': '{National Center for Biotechnology Information (US)}',
'publocation': '{Bethesda (MD)}',
'pubstatus': '{ppublish}',
'pubtype': '{Review}',
'revised': '{2008-4-30}',
'sections': '{Background; Synthesis; In Vitro Studies: Testing in Cells and Tissues; Animal Studies; Human Studies; References}',
'title': '{Molecular Imaging and Contrast Agent Database (MICAD)}',
'year': '{2004}'}
In [105]:
def check(bib_item):
if 'title' in bib_item.entry and bib_item.entry['title'].endswith('.}'):
title = bib_item.entry['title']
raise Exception('wrong title')
In [110]:
for bib_key, bib_item in global_index.items():
try:
check(bib_item)
except Exception as e:
print(e, bib_key)
print(bib_item.title)
fix = input("Fix? ")
if fix in ('y', 'yes', 'j', 'ja'):
bib_item.entry['title'] = bib_item.entry['title'][:-2] + '}'
wrong title Stul11
Dot1 binding induces chromatin rearrangements by histone methylation-dependent and -independent mechanisms.
Fix? y
wrong title Sans97
Dehydration in the elderly: strategies for prevention and management.
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-110-1d4ecc88dee0> in <module>()
2 try:
----> 3 check(bib_item)
4 except Exception as e:
<ipython-input-105-fe371876167e> in check(bib_item)
4 title = bib_item.entry['title']
----> 5 raise Exception('wrong title')
Exception: wrong title
During handling of the above exception, another exception occurred:
KeyboardInterrupt Traceback (most recent call last)
/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py in _input_request(self, prompt, ident, parent, password)
720 try:
--> 721 ident, reply = self.session.recv(self.stdin_socket, 0)
722 except Exception:
/usr/local/lib/python3.5/dist-packages/jupyter_client/session.py in recv(self, socket, mode, content, copy)
777 try:
--> 778 msg_list = socket.recv_multipart(mode, copy=copy)
779 except zmq.ZMQError as e:
/usr/local/lib/python3.5/dist-packages/zmq/sugar/socket.py in recv_multipart(self, flags, copy, track)
394 """
--> 395 parts = [self.recv(flags, copy=copy, track=track)]
396 # have first part already, only loop while more to receive
zmq/backend/cython/socket.pyx in zmq.backend.cython.socket.Socket.recv (zmq/backend/cython/socket.c:7683)()
zmq/backend/cython/socket.pyx in zmq.backend.cython.socket.Socket.recv (zmq/backend/cython/socket.c:7460)()
zmq/backend/cython/socket.pyx in zmq.backend.cython.socket._recv_copy (zmq/backend/cython/socket.c:2344)()
/usr/local/lib/python3.5/dist-packages/zmq/backend/cython/checkrc.pxd in zmq.backend.cython.checkrc._check_rc (zmq/backend/cython/socket.c:9621)()
KeyboardInterrupt:
During handling of the above exception, another exception occurred:
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-110-1d4ecc88dee0> in <module>()
5 print(e, bib_key)
6 print(bib_item.title)
----> 7 fix = input("Fix? ")
8 if fix in ('y', 'yes', 'j', 'ja'):
9 bib_item.entry['title'] = bib_item.entry['title'][:-2] + '}'
/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py in raw_input(self, prompt)
694 self._parent_ident,
695 self._parent_header,
--> 696 password=False,
697 )
698
/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py in _input_request(self, prompt, ident, parent, password)
724 except KeyboardInterrupt:
725 # re-raise KeyboardInterrupt, to truncate traceback
--> 726 raise KeyboardInterrupt
727 else:
728 break
KeyboardInterrupt:
In [111]:
global_index['Stul11'].entry
Out[111]:
{'abstract': '{Methylation of histone H3 lysine 79 (H3K79) by Dot1 is highly conserved among species and has been associated with both gene repression and activation. To eliminate indirect effects and examine the direct consequences of Dot1 binding and H3K79 methylation, we investigated the effects of targeting Dot1 to different positions in the yeast genome. Targeting Dot1 did not activate transcription at a euchromatic locus. However, chromatin-bound Dot1 derepressed heterochromatin-mediated gene silencing over a considerable distance. Unexpectedly, Dot1-mediated derepression was established by both a H3K79 methylation-dependent and a methylation-independent mechanism; the latter required the histone acetyltransferase Gcn5. By monitoring the localization of a fluorescently tagged telomere in living cells, we found that the targeting of Dot1, but not its methylation activity, led to the release of a telomere from the repressive environment at the nuclear periphery. This probably contributes to the activity-independent derepression effect of Dot1. Targeting of Dot1 promoted gene expression by antagonizing gene repression through both histone methylation and chromatin relocalization. Our findings show that binding of Dot1 to chromatin can positively affect local gene expression by chromatin rearrangements over a considerable distance.}',
'author': '{Stulemeijer, Iris Je and Pike, Brietta L and Faber, Alex W and Verzijlbergen, Kitty F and van Welsem, Tibor and Frederiks, Floor and Lenstra, Tineke L and Holstege, Frank Cp and Gasser, Susan M and van Leeuwen, Fred}',
'completed': '{2011-07-14}',
'country': '{England}',
'created': '{2011-02-15}',
'doi': '{10.1186/1756-8935-4-2}',
'issn': '{1756-8935}',
'issn-linking': '{1756-8935}',
'issue': '{1}',
'journal': '{Epigenetics \\& chromatin}',
'month': 'feb',
'nlm': '{PMC3038881}',
'nlm-id': '{101471619}',
'owner': '{NLM}',
'pages': '{2}',
'pii': '{1756-8935-4-2}',
'pmc': '{PMC3038881}',
'pmid': '{21291527}',
'pubmodel': '{Electronic}',
'pubstatus': '{epublish}',
'revised': '{2017-02-20}',
'title': '{Dot1 binding induces chromatin rearrangements by histone methylation-dependent and -independent mechanisms}',
'volume': '{4}',
'year': '{2011}'}
In [ ]:
def checks(global_index):
# skip some types
if not bib_item.entry_type in include_keys:
print('missing fields')
continue
# skip if incomplete information
if not all(k in bib_item.entry for k in include_keys[bib_item.entry_type]):
continue
In [92]:
include_keys = {
'@Article': ('author', 'title', 'journal', 'year', 'url'),
'@InProceedings': ('author', 'booktitle', 'journal', 'year')
}
def fwrite_line(f, line):
f.write((line + '\n').encode('utf-8'))
def write_bib(filename, string_rules, global_index):
with open(filename, 'wb') as f:
fwrite_line(f, '% Encoding: UTF-8\n\n')
for k, v in string_rules.items():
fwrite_line(f, "@String{" + k + " = " + v + '}')
for k, bib_item in sorted(global_index.items()):
if not bib_item.entry_type in include_keys:
continue
fwrite_line(f, bib_item.entry_type + '{' + k + ',')
for keyword in include_keys[bib_item.entry_type]:
if not keyword in bib_item.entry:
continue
content = bib_item.entry[keyword]
fwrite_line(f, ' ' + keyword + ' = ' + content + ',')
fwrite_line(f, '}')
fwrite_line(f)
In [93]:
write_bib('diag_bib_out.bib', string_rules, global_index)
In [48]:
!less diag.bib
% Encoding: UTF-8
@String{AA = _Age_and_Ageing_}
@String{AAC = _Antimicrobial_Agents_and_Chemotherapy_}
@String{AACC = _AACN_Advanced_Critical_Care_}
@String{AAPM = _American_Association_of_Physicists_in_Medicine_}
@String{ABDI = _Abdominal_Imaging_}
@String{ACAEMEMED = _Academic_Emergency_Medicine_}
@String{ACHA = _Applied_and_Computational_Harmonic_Analysis_}
@String{ACMCS = _ACM_Computing_Surveys_}
@String{ACMTG = _ACM_Transactions_on_Graphics_}
@String{ACMTIS = _ACM_Transactions_on_Information_Systems_}
@String{ACMTMS = _ACM_Transactions_on_Mathematical_Software_}
@String{ACR = _Anticancer_Research_}
@String{ACSCHENEU = _ACS_Chemical_Neuroscience_}
@String{ACTAB = _Acta_Anaesthesiologica_Belgica_}
@String{ACTANASCA = _Acta_Anaesthesiologica_Scandinavica_}
@String{ACTBIOMAT = _Acta_Biomaterialia_}
@String{ACTNC = _Acta_Neurochirurgica_}
@String{ACTNEUBEL = _Acta_Neurologica_Belgica_}
@String{ACTNEUSCA = _Acta_Neurologica_Scandinavica_}
@String{ACTNP = _Acta_Neuropsychiatrica_}
@String{ACTONC = _Acta_Oncologica_}
:g.bib
In [36]:
global_index['Oei16a'].entry
Out[36]:
{'author': '{Marcel T. H. Oei and Frederick J.A. Meijer and Willem-Jan {van der Woude} and Ewoud J. Smit and Bram {van Ginneken} and Rashindra Manniesing and Mathias Prokop}',
'doi': '{10.1007/s00330-016-4592-z}',
'journal': 'ER',
'number': '{6}',
'pages': '{2411-2418}',
'title': '{Interleaving Cerebral {CT} Perfusion with Neck {CT} Angiography. {Part II}: Clinical Implementation and Image Quality}',
'volume': '{27}',
'year': '{2017}'}
In [37]:
global_index.keys()
Out[37]:
dict_keys(['Mert14', 'Ritt90', 'Kan05', 'Rene03', 'Mare14', 'Peet09', 'Zijl94', 'Schr13a', 'Kort94a', 'Reek02', 'Nune12', 'Band17', 'Kobu14a', 'Stul11', 'Schw15', 'Thij14', 'Ciet14', 'Klei15a', 'Terr15', 'Stee94a', 'Sans97', 'Lave15', 'Sche08', 'Hesk14', 'Seti15a', 'Witt12b', 'Aarn13a', 'Bree00', 'Vuka09a', 'Vuka10', 'Bart15', 'Stou01', 'Galp11', 'Voog11', 'Rudy14', 'Hoog16', 'Voge07a', 'Naga16', 'Kall16a', 'Berk94a', 'Scia11', 'Bejn15', 'Hoek13b', 'Wier07', 'Terr16', 'Pete13b', 'Scho02a', 'Hoog15', 'Wand15b', 'Mord16b', 'LinE05', 'Schi97', 'Adri11c', 'Stil14', 'Stee98a', 'Arzh09b', 'Gatt14', 'Hesk12a', 'Mord17', 'Oost13', 'Hesk13a', 'Tall01', 'Veld10a', 'Puig00', 'Vos08b', 'Mets12', 'Rikx11a', 'Zand01', 'Tann11a', 'Dekk12', 'Brom13', 'Kok07', 'Brom10', 'Dale04', 'Rikx07a', 'Weij10', 'Geor16', 'Arnt16', 'Kars89', 'Kars06', 'Kuip08', 'Boog13', 'Mus17', 'Wate12', 'Scha05a', 'Obde14', 'Thij05', 'Kamm01', 'Surc14a', 'Srin10b', 'Aart09', 'Hans10a', 'Scha16', 'Nune13', 'Koui16a', 'Reic90a', 'Hoop08a', 'Gal13', 'Stee94', 'Gott13', 'Sche05a', 'Leer14', 'Powe17', 'Verh93', 'Loog05', 'Sonn16', 'Pari11', 'Wrig12', 'Boog15', 'King14', 'Laar03a', 'Hans12', 'Kooi17b', 'Esen14', 'Lage16a', 'Jana03', 'Joda14', 'Vrie10b', 'Serl05', 'Treu16', 'Ginn06c', 'Hoge10', 'Blan11', 'Heij13', 'deG13', 'Xu08', 'Berg98', 'Behe07', 'Scho13b', 'Rama16', 'Sana11', 'Pol09', 'Laar05b', 'Arzh09', 'Slee06', 'Arzh06a', 'Wier08', 'Schn03a', 'Waai07', 'Muen14a', 'Dekk16a', 'Breu12', 'Roll10', 'Camb04', 'Riel17', 'Eerd05', 'Vugt11a', 'Manf17', 'deG06c', 'Bom98a', 'Tan16', 'Ven13d', 'Vink88', 'Loka10', 'Verm10', 'Egge03', 'Kali07', 'Hoog03a', 'Horn04a', 'Roel07', 'Post05', 'Kira03', 'Samu07', 'Jaco10a', 'Mann99a', 'Zerb13', 'Tibb95', 'Sche02b', 'Scho15a', 'Fuett12', 'Gall13', 'Wong17', 'Stil13', 'Lesn11', 'Arte12', 'Marc11b', 'Humm14', 'Hart91', 'Nune08', 'Mara17', 'Radk07', 'Phil08', 'Wiel03', 'Wiel10', 'Gube14', 'Vent14a', 'Meij13d', 'Robi03', 'Koui13b', 'Venh15b', 'Yaka12', 'Mikk14', 'Bouc03', 'Mehr17', 'Eile08', 'Scha04', 'Scha92', 'Fabe09', 'Huis96', 'Cann06', 'Gish14', 'Zhai16', 'Mann16a', 'Otte05', 'Meij09d', 'Chyk13', 'Groo14', 'Nieu08', 'Bast06a', 'Jaco15', 'Brui10', 'Jong12', 'Brou03b', 'Gott03', 'Stou07', 'Gott04a', 'Plat14', 'Coen09', 'Guo12a', 'Thij69', 'Scha13', 'Reis15', 'Seln12a', 'Weve95', 'van15f', 'Hoge13a', 'Bert16', 'Brou05a', 'Grin13a', 'Lang98a', 'Boer12b', 'Heer03', 'Wier11', 'Kars96a', 'Rij05', 'Scha09b', 'Garc09', 'Ciom17', 'Rutt10', 'Siae04', 'McLo04', 'Hoge15', 'Kort97b', 'Buit17', 'Beij13', 'Adri10', 'Scha14h', 'Devo04', 'Jans03b', 'DeV03', 'Leyt13', 'Mann10', 'Hoek13a', 'Jans00', 'Hein16', 'Hoge17', 'Kall08b', 'Nigh07', 'Mull13', 'Kapu01', 'Geer11', 'Arif15b', 'Kaem94', 'Oei07', 'Vos13a', 'Jans05', 'Jans15c', 'Jage03', 'Vent13', 'Diss11', 'Will16', 'Defe16', 'Dijk15a', 'Gain11', 'Broe09', 'Gall11b', 'Velt10', 'Bakk07', 'Thal02a', 'Vers07', 'Silv17a', 'Remi15a', 'van16a', 'Berg15', 'Gala92', 'Ven13a', 'Graa92b', 'Nadar2017b', 'Pury16', 'Tann13', 'Cuyp95', 'Thij85', 'Tan15', 'Lage16b', 'Lust08', 'Hoes13', 'Veli08d', 'Zaim15', 'Geer17', 'Murp12a', 'Troo08a', 'Lave04', 'Buij11', 'Deva11', 'Kobu13a', 'Koen17a', 'Eerd07', 'Heim09', 'Litj14', 'Esma14a', 'Isgu03a', 'Pomp15a', 'Mann17', 'Heer97a', 'Hend05', 'Boll08', 'Barr03', 'Dese11', 'Bank12', 'Brak00a', 'Laur15', 'Geel07', 'Rikx12', 'Schu12', 'Isgu07a', 'Lo13', 'Meeu12', 'Eijc10', 'Eise14', 'Mens09', 'Work17a', 'Kopp04', 'Slui03', 'Arif16a', 'DeV11', 'Mavi10', 'Bert11', 'Oei07a', 'Stie13', 'Kue03', 'Dett14', 'Scha10b', 'Mool99', 'Puar2017b', 'Muse13a', 'Vlie12', 'Garc09a', 'Horn06', 'Heuv15', 'Essi81', 'Gube15d', 'Bol16', 'Gara95', 'Jans04a', 'Wels08', 'Stee97', 'Malo16', 'Jaco15b', 'Brac14', 'Gube10', 'Kroe16a', 'Wein15', 'Bela94', 'Mets16', 'Wieg17', 'Riks06', 'Sabo11', 'Kan06', 'Wal11', 'Breu11a', 'Post03b', 'Veli10', 'Lakh16b', 'Ginn01a', 'Koll12', 'Beek16', 'Litj12', 'Snead16', 'Vila08', 'Enge03b', 'Tan13a', 'Lave11', 'Deba16', 'Enge12', 'Bax08b', 'Scha03b', 'Ven16a', 'Muhs06', 'Klei11', 'Oei12', 'Wijs15', 'Giet07e', 'Nott14', 'Blee08', 'Chen17', 'Lens17', 'Bol16a', 'Grin15', 'Sche02c', 'Xu06a', 'Pelo07', 'Ciom11', 'Litj16c', 'Thij07', 'Huefn99', 'Wrig08', 'Simo06', 'Mend10b', 'Kort15', 'Rikx08c', 'Gott06a', 'Kris07', 'Amir14', 'Weve11', 'Phil15a', 'Berg04c', 'Mass91b', 'Mend09a', 'Nagh03', 'Madu15', 'Lang99a', 'Dijk16', 'Hesk13', 'Buij98a', 'Clae08', 'Kall16', 'Klae05a', 'Hout02', 'Jong10', 'Vos13', 'Ven16', 'Bouc04', 'Eise03', 'Boo09', 'Wate12a', 'Will17', 'Kars93', 'LinE06', 'Kouw07a', 'Vos10b', 'van15h', 'Sanc08b', 'Fuch03', 'Mord16', 'Vlan11', 'Kopp06a', 'Sand11a', 'Kopp05', 'Stil13a', 'Vree16c', 'Heij07', 'Tiel07', 'Lo11', 'Isgu07b', 'Sun14a', 'Ginn03a', 'Murp09a', 'Verz10', 'Yaka12a', 'Grin13b', 'Will16a', 'Zerb14a', 'Fuett11a', 'Tess16', 'Hoek11a', 'Leem15', 'Brou03', 'Kell12', 'Terr14', 'Wimm14', 'Sanc08', 'Vist14', 'Fran15', 'Doll14', 'Boe03', 'Beso15', 'Greu07', 'Hoeb13', 'Woli15', 'Weij12a', 'Maes17', 'Samu08', 'Kock16', 'Klei17', 'Stro14', 'Smid16', 'Hamb10', 'Gran09', 'Haas14a', 'Nill10', 'Budd10a', 'Thij88', 'Rij13', 'Char15b', 'Veld00b', 'Kars91', 'Hups09', 'Bov97', 'Slui02', 'Chau14a', 'Sche11', 'Bran11', 'Scho14c', 'Woli15a', 'Vos10a', 'Giet06', 'Vos14', 'Taya17', 'Mets12i', 'Krab08', 'Keul09a', 'Berk94', 'Lopa11', 'Plat11', 'Idze08b', 'Demi09', 'Smit12', 'Vugt14', 'Oyen09', 'Scho03a', 'Isgu05', 'Aart08', 'Veli08', 'Kooi17d', 'Hoeb14', 'Koek12', 'Jaco12', 'Troo14', 'Kars05', 'Gand15', 'Zelb14', 'Khan14a', 'Prok96', 'Capp03', 'Beic16', 'Fond13', 'Venh17b', 'Somm09', 'Rege13', 'Have03a', 'Oezde16', 'Carv17', 'Litj12c', 'Bex14', 'Dupp15a', 'Scha12', 'Boer12a', 'Bagl13', 'Schi05b', 'Hekm17', 'Xu09', 'Hoek13c', 'Ven11', 'Andr12a', 'Boer08', 'Kall16b', 'Mele14a', 'Over13', 'Laar06b', 'Frid02', 'Isgu11', 'Jong86', 'Trem04', 'Schi05a', 'Wilb14a', 'Liu15', 'Muse15', 'Bald04a', 'Hooi08', 'Trui07', 'Durm14a', 'Ginn00a', 'van16h', 'Hesk16', 'Aben11', 'Doer06', 'Stef99', 'Merc14', 'Henn10a', 'Fue16a', 'Stee97a', 'Ohta09', 'Schr11a', 'Rooi14b', 'John13a', 'Be05', 'Tel13', 'van15g', 'Deba11', 'Wier10', 'Khal12', 'Jans00a', 'Breu12a', 'Kort14a', 'Kort00', 'Kort97a', 'Hooi09', 'Buss11', 'deJ03', 'Troo07', 'Ginn11', 'Madu15a', 'Joha01', 'Gold07b', 'Amir13a', 'Adri09', 'Kadz17', 'Lee09c', 'Leem17', 'Need15a', 'Blac96', 'Pete13', '04', 'Urib11', 'Stoi17b', 'Mann08c', 'Hoge13b', 'Boom12a', 'Pomp15', 'Thij89', 'Fekk16', 'Ruh06', 'Xu08b', 'Aart09a', 'Prin13c', 'Ruh05', 'Hore14a', 'Sawi16', 'Riet07', 'Terr15a', 'Rikx08b', 'Conw11', 'Nedr11', 'Fuet05', 'Brou05b', 'Cany13', 'Mavi12a', 'Kouw05a', 'deG06', 'Roos12', 'Sanc12', 'Stei12', 'Rath98', 'Roel04', 'Roth04', 'Venh17', 'Gran07', 'Wein06', 'Stik03', 'Lopa09b', 'Viss11', 'Chen14', 'Fleu14b', 'Viss09', 'Kouw06c', 'Oost15', 'Kolk15', 'Heer99', 'Wu13a', 'Meli09', 'Schw16', 'Thij87', 'Over16', 'Will04a', 'Carr11', 'Puig03', 'Sard16', 'Rabb14', 'Delh16', 'Ginn01', 'Vree16a', 'Niel16', 'Garc17', 'Graa92a', 'Hoop10a', 'Voge14', 'Scha13g', 'Maaz95', 'Laar05', 'Laue13', 'Tan13', 'Spaa09', 'Brom14b', 'Schr14', 'Verg15', 'Gott06e', 'Timp07', 'Will09', 'Frig17', 'Berg10', 'Boer17a', 'van15b', 'Bare13', 'Bern92', 'Fort14', 'Mend09', 'Marc11c', 'in00', 'Hadl84', 'Seab11', 'Verg16', 'Vijv16', 'Viss07', 'Garc07', 'Broe04', 'van15p', 'Rutt08a', 'Muen10', 'Jasp11', 'Ter17', 'Wrig10', 'Meli10a', 'Ruer07', 'Aarn13', 'Brom16', 'Rijp03a', 'Enge01', 'Loog04d', 'Sabo08', 'Zuij08', 'Mann08', 'Ven13b', 'Oyen05', 'Scha02d', 'Niem10a', 'Scha13a', 'Samu09', 'Hoog17a', 'Prok02', 'Rijp14a', 'Lave02a', 'Bome13', 'Kall08', 'Mann10a', 'Lage12a', 'Prok97a', 'Zerb12a', 'DiF09', 'Hamo14', 'Brui03b', 'Desa11b', 'Hu15', 'Kars11b', 'Kort16a', 'Kall12b', 'Ferr08', 'Mend10a', 'Huig15', 'Kort16', 'Boel15a', 'Jaco13b', 'Phil15', 'Rene08', 'Steen92', 'Isgu09a', 'Roos14', 'Hesk12', 'Holl16a', 'Klom09', 'Wieg17a', 'Heer92', 'Desa10a', 'Blue15', 'Vos15', 'Inag14a', 'Meij13a', 'Cohe16', 'Ginn08e', 'Hoop09a', 'Jaco11a', 'Stev12', 'Reza16', 'Kamm96', 'Stev13', 'Hart93', 'Berk04', 'Klym16', 'Thij93', 'Witt12', 'Gees15b', 'Hari03', 'Scha12a', 'Sand00', 'Plui12', 'Rijp17', 'Mets16a', 'Sava11', 'Vos15b', 'Riel13a', 'Heij07a', 'Lue14', 'Luij10', 'Verb94', 'Keij09', 'Horb17', 'Broe09b', 'Preh09a', 'Kobu15c', 'Thij80', 'Yan07', 'Brun07', 'Ghos12', 'Budd11', 'Less16', 'Arno16', 'Sieg15', 'Hoog88', 'Ven13', 'Groo14a', 'Huo13', 'Cair03', 'Maas13b', 'Coel15', 'Puig02a', 'Brou08', 'Scho17', 'Fort13', 'Araz15', 'Ponc14', 'Hees07', 'Silv17', 'Blee11', 'Koun09', 'Ros90', 'Vila08a', 'Scha03', 'Graa97', 'Scho93', 'Wand17', 'Kamm03', 'Heij12b', 'van15', 'Boer07', 'Lava15', 'Ma14', 'Schu11a', 'Rijp03', 'Muhs06a', 'Seti16', 'Claa16', 'Cesp00', 'Wijn15', 'Dijk15b', 'Herm12a', 'Nair12a', 'Wies17b', 'Groo15a', 'Hoge12', 'Vrie10c', 'Luet14b', 'Prin13d', 'Blee04b', 'Eter16a', 'Schi06c', 'Mets12f', 'Brom12a', 'Veli08a', 'Lutj09', 'Bome14', 'Grae93', 'Schm02', 'Berk95', 'Weid05', 'in99', 'Iqba08a', 'Hekm16', 'Mart05', 'Chun17a', 'Brec12a', 'Grin16c', 'Phil15b', 'Prok97', 'Grot13', 'Dekk14', 'Dese09', 'Gebb93', 'Ring06', 'Prok03b', 'Lake98', 'Aart99', 'Rijk15', 'Wang12', 'Lang98', 'Mooi16', 'Kall09', 'Bank15', 'Desl14', 'Niem11b', 'Chat16a', 'Usui14', 'Shuk02', 'Lass15a', 'Mend07a', 'Zadr02', 'Roth14', 'Senf08', 'Ross12', 'Enge03a', 'Stro14a', 'Brom15', 'Boer15a', 'Blee03', 'Dalm17a', 'Rijp02', 'Slui06', 'Sanc06a', 'Klei15', 'Hoge11', 'Kolk04', 'Brun10', 'Puar16', 'Ginn10b', 'Luts07', 'Heer97', 'Brec09', 'Isgu10', 'Wier04', 'Rong05', 'Prin13b', 'Schi10a', 'Bitt12', 'Klav09', 'Scho14b', 'Futt06', 'Ginn09b', 'Vrie12', 'Ritc16', 'Oyen92', 'Ter16', 'Bejn13', 'Uffm08', 'Wilb14', 'Meij08', 'Gort08', 'Enge05b', 'Carl02', 'Gill00', 'Gijs15c', 'Niel11', 'Sand11', 'Fue16', 'Hase16', 'Lass12', 'Dijk07d', 'Clae08a', 'deV02', 'Enge06c', 'Lage16', 'Moha14', 'Emau15a', 'Pros12', 'Subr13', 'Jans14', 'Zwol2001', 'Stee11', 'Sche09', 'Hint05', 'Lupo03', 'Scha12b', 'Beer08', 'Rooi14a', 'Prok93a', 'Lass15', 'Voge08', 'Blee03a', 'Gott06c', 'Harl11', 'Thij95', 'Huss98', 'Laar09', 'Mann08b', 'Wata16', 'Maas16', 'Pate17b', 'Staa04a', 'Ferg91', 'Aert14', 'Wate14a', 'Schu05', 'Troo09', 'Mend09b', 'Kok05', 'Weim97', 'Kars09', 'Jans13b', 'Enge05', 'Rikx06a', 'Kars97', 'Wies17', 'Verz12', 'Enge02', 'Litj13', 'Teus13', 'Brin08', 'Brak00', 'Altm97', 'Avoi13', 'Ginn15', 'Luij01', 'Idze12', 'Voge07b', 'Grat02', 'Mert12', 'Zech09', 'Vuka12', 'Brow12', 'Boer85', 'Muse15a', 'Gube15c', 'Kok02', 'Roos08', 'Zaid14', 'Hoek11', 'Rooi17a', 'Hoge10a', 'Hamo14a', 'Hoek13', 'Sand99a', 'Gott11', 'Chun15', 'Dey14', 'Thal03a', 'Duss98', 'Hees09', 'Schi06a', 'Litj15', 'Ball15', 'Stei16', 'Scho12a', 'Crim09a', 'Mann06e', 'Kock10a', 'Rene05', 'Schm12', 'Radd08', 'Gebh15', 'Aert11', 'Laar03', 'Scha14d', 'Idze15', 'Murp08c', 'Hoog90', 'Oost08', 'deJ09a', 'Grin12a', 'Lepp95', 'Gube12', 'Ginn08c', 'Romi91', 'Albe12', 'Laar06a', 'Fleu13a', 'Hofs88', 'Veli09', 'Lage13a', 'Thij86', 'Lopa09a', 'Yim11', 'DeGr99', 'Kemp09', 'Litj15c', 'Oyen15', 'Gren10', 'Schw13', 'Kars90b', 'MacM17', 'Nijh13', 'Zerb14', 'Mets12g', 'Will16c', 'Meer17', 'Ven12c', 'Murp08b', 'Cuij07', 'Idze06', 'Broe05', 'Durm14', 'Kapu00a', 'Wies15', 'Will16d', 'Enge00', 'Ciom12', 'Mets12b', 'Mema06a', 'Brow10', 'Murp12', 'Wijm95', 'Bult12', 'Boo11b', 'Napo16', 'Sriv14', 'Oyen11', 'Flac14', 'Post07', 'Meeg14', 'Steen94', 'Meij07', 'Ande05', 'Meij16b', 'Schi09a', 'Care11', 'Vegt06', 'Vers08', 'Somf13', 'Niem05a', 'Voge05b', 'Thal03b', 'Riel15b', 'Fleu11', 'Wijs16', 'Aarn12a', 'Leeu17', 'Gott06b', 'Lee08', 'Niem08a', 'Dijk15', 'Kooi17a', 'Klae05', 'Unde15', 'Zand11', 'Stru13', 'Stoeg17', 'Deba16a', 'Yim11a', 'Stei14', 'Schu00', 'Muse14', 'Bare99', 'Beum16', 'Scha90', 'Ozde13', 'Firo13', 'Sarr13', 'Niem09e', 'Mook08', 'Wrig09', 'Ginn02a', 'Fall16', 'Camb06', 'Gutb11', 'Gott14', 'Hans16', 'Smit91', 'Kort11', 'Thij08', 'Oei11a', 'Grin13', 'Herm12b', 'Oost85', 'Bouc02', 'Bome17', 'Yim10', 'Aebe93', 'Fagg11', 'Hans09', 'Esch17a', 'Kooi17', 'Veld03b', 'Mema07', 'Muse14b', 'Gamb06', 'Aart06', 'Mets13b', 'Laak78', 'Renn07', 'Zand03', 'Mulk04', 'Boo11', 'Morg14', 'Mann14', 'Amer13', 'Isgu09', 'Steen91a', 'Aalt11', 'Meij17a', 'Meij13b', 'Fort12', 'Renn10', 'Brun12', 'Schi05', 'Idze14', 'Mele12', 'Teus15a', 'Troo10a', 'Meij16', 'Simo03', 'Plat12', 'Tall00', 'Blee04a', 'Marc12a', 'Grin14', 'Lopa09', 'Naka11', 'Yang14', 'Mele14b', 'Prok00', 'Brun13', 'Naid13', 'Meij12d', 'Chon11', 'Yen04', 'Gube13a', 'Meij15c', 'Gils99', 'DeSt11', 'Hent16', 'Tate06', 'Hoop10b', 'Holl15a', 'Kamp15', 'Nab92', 'Tanc10', 'Veer14', 'Rikx09b', 'Rikx11d', 'Pale13', 'Gamb04', 'Sanc11b', 'Usma13a', 'Schu14', 'Blic04', 'Litj16b', 'Holl16c', 'Busc16', 'Rikx09a', 'Herm13', 'Niem06b', 'Stoe08', 'deB16a', 'Sari14', 'Niek14a', 'van15d', 'Blue12', 'Rooi14', 'Niek11', 'Pond08', 'Ghaf17c', 'Kobu12a', 'Gibs17', 'Dirn06', 'Dijk06a', 'Suko03', 'Bol14', 'Rikx09d', 'Brou03a', 'Yana15', 'Muld16', 'Vos14b', 'Surc14', 'Troo05', 'Meij17b', 'Jara15a', 'Ginn08b', 'Holl14', 'Kall11a', 'Rikx09c', 'Erik16', 'Brin10', 'Jaco91', 'Scha97c', 'Theu15', 'Luij08', 'Sche01', 'Prok05a', 'Rijp15', 'Broe10', 'Thij90a', 'Reic89', 'Kost16', 'Wijs17', 'Walk08', 'Krau07', 'Laba17', 'Gige01', 'Vier11', 'Litj09', 'Hoog17', 'Vos12a', 'Kooi16a', 'Mann00', 'Stei15', 'Hama15', 'Dalm15', 'Moha13', 'Dijk11', 'Lepo15', 'Prok01', 'Schm13', 'Kars11a', 'Eerd14', 'Rij11', 'Kroo17', 'Jeur11', 'Wu09', 'Meel17', 'Mus17a', 'Schi06b', 'Jaco10c', 'Gube11a', 'Enge07', 'Srin15', 'Ginn14', 'van16f', 'Lori13', 'Kopp05a', 'Tan15a', 'Hamb11', 'Elha14', 'Star09', 'Ciom12a', 'Prin12', 'Romi87', 'Reic90', 'Ritc15', 'Mowa13', 'Wand17a', 'Albe11', 'Rutt08', 'Gott07a', 'Scha15', 'Broe05a', 'Bome17a', 'Riel15d', 'Kooi86', 'Kull11', 'Moor13', 'deG08', 'Prok93', 'Kaem95', 'Otte09', 'Teus15', 'Ruer02', 'Niel14', 'Ciom15', 'Niek12', 'Lass11', 'Pane15', 'Ramo13b', 'Kobu16b', 'Mann16c', 'Kapu07', 'Bank07', 'Wieg16a', 'Kars10', 'Scha03e', 'Litj15b', 'Rikx07b', 'Stee17a', 'Vere03', 'Kan04', 'Prok90', 'Bare17', 'Mend11', 'Schi11c', 'Mull15', 'Lang02', 'Nijh16', 'Scha02c', 'Simo05c', 'Kort97', 'Poko14', 'Roos10a', 'Mann06b', 'Boxt15', 'Fuett07', 'Oei08', 'Klei09', 'Laan12', 'Mare11', 'Arzh09c', 'Post03a', 'Stei14a', 'Oezd16', 'Ginn06', 'Broe05b', 'Eter15', 'Nill11', 'deG09', 'Voge06a', 'Loog06b', 'Scha03c', 'Post03d', 'Page12', 'Nieu15a', 'Raza15', 'Aren12', 'Jans15a', 'Berk15a', 'Wille06', 'Will16b', 'Kamm94', 'Joos17', 'Kooi17c', 'Hoop08', 'Vos14a', 'Ciom13a', 'Carr15a', 'Kobu12b', 'Brui03a', 'Boot17', 'Balo11', 'Romi89b', 'Loog02a', 'Doum10', 'Shi09', 'Scho17a', 'Jans04', 'Samu11a', 'Dors04', 'Hend16', 'Berk96a', 'Hesk14b', 'Somf08', 'Nabu08', 'Brui04', 'Vent14b', 'Scho13d', 'Bhun13', 'Marc12b', 'Holt02', 'Lang98b', 'Stav97', 'Lakh14', 'Case99', 'Star10', 'Barr12', 'Deur94', 'Geus07a', 'Huge15', 'Niem09d', 'Ginn01c', 'Nune09', 'Fuett12b', 'Kita07', 'Ven13c', 'Scha14e', 'Ji13', 'Bril11', 'Rikx08', 'Lupo02', 'Kort00a', 'Aarn12b', 'Wand15a', 'Gasp07', 'Abra08a', 'Corv14', 'Thij11', 'Thij82', 'Litj12d', 'Deng09', 'Smit09', 'Graa91a', 'Luca13', 'Niem08', 'Hoog15a', 'Wijn10a', 'Gilh02', 'Sieg17', 'Kale01', 'Nabu10a', 'Ginn09a', 'Desa12a', 'Sanc10a', 'Goed92', 'Garc15', 'Meij15', 'Lee10d', 'Aald17', 'Prok05', 'Arzh07a', 'Vlie07', 'Hump17', 'Wolf98', 'Pete17', 'Isgu03', 'Wink15a', 'Eijc09', 'Popa11', 'Broe10a', 'Chon11b', 'Rens11a', 'Geer15', 'Vend17c', 'Vran12', 'Snoe05', 'Scha99', 'Over06', 'Muyo14', 'Mann07', 'Heij15', 'Snoe03', 'Bare12a', 'Freu14', 'Ginn07a', 'Cesp99', 'Saks14', 'Sche00', 'Berg98b', 'Post11', 'Groo16a', 'Phil04a', 'Mook09', 'Groo16b', 'Mars14', 'Sun03', 'Waai09', 'Verz14', 'Hoog87', 'Kroe09', 'Lesn12a', 'Bejn17', 'Bria16b', 'Chat14', 'Bult12a', 'Boze12', 'Mang09', 'Cloo86', 'Poko15', 'Nabu10', 'Gige13', 'Meij09c', 'Zerb12', 'Jans15b', 'Wolt16', 'Seti15', 'Schi03a', 'Teeu12', 'Sun16b', 'Devo04a', 'Sche07', 'Hoop10', 'Holl17b', 'Dald99', 'Mets02', 'Steh14', 'Eijn09', 'Snoe04', 'Pere15', 'Boer11', 'Gala93', 'Heer94', 'Cann08', 'Koni14', 'Daen87', 'Fens13', 'Veli07', 'Klei04', 'Phil2016', 'Fuett04', 'Kran98', 'Leem17a', 'Klei06a', 'Gala94', 'Brin11', 'Sanc11a', 'deJ09b', 'Desa12', 'Ciom14a', 'Heer93', 'Dijk07a', 'Isba15', 'Sch08', 'Vegt10', 'Jans02a', 'Vugt12', 'Oliv11a', 'Samu08b', 'Lamb06', 'Roth03', 'Mets13c', 'Kouw05b', 'West09', 'Subr13a', 'Hore13b', 'Smit94', 'Gill08', 'Radm11', 'Verz11', 'Fleu14d', 'Muse13b', 'Weve94', 'Blee15', 'Wern04', 'Mele16a', 'Mari17', 'Valc97', 'Leym96', 'Madu13c', 'Ding2006', 'Voge04', 'Usma14a', 'Bare96', 'Lori13a', 'Gees07', 'Lass12a', 'Merc12', 'Srik13', 'Boom14', 'Kyri09', 'Veld09a', 'Klei12', 'Niem05', 'Plat11a', 'deG05', 'Rikx06', 'JPBe01', 'Hart11', 'Moe13', 'Scho14', 'Bald04', 'Timp04', 'Scho14d', 'Elli11', 'Laar07', 'Cloo83', 'Lief17', 'Niem09c', 'Herm11c', 'Stee98', 'Mada11', 'Oz14', 'Madu11a', 'Snoe10', 'Zhan08a', 'McCa02', 'Tang11', 'Lens16', 'Terw13', 'Heij14', 'Wu06b', 'Firo10a', 'Schm92', 'Pins13', 'Olbr95', 'Sper04', 'Ciom14', 'Lee13', 'Pill09', 'Capp98', 'Boo11a', 'Fleu14a', 'Wies17a', 'Jage96', 'Scha93', 'Broc14', 'Groo16j', 'Arzh06', 'Mull99', 'Thoe09', 'Luka04', 'Mann98', 'Oest91a', 'Vell08', 'Mann11', 'Verb05', 'Osch05', 'Cate08', 'Vasa02', 'Ginn12', 'Back09', 'Vos07', 'Albe94', 'Litj10', 'Olbr96', 'Rijp04', 'Chen17b', 'Rij14', 'Stef02', 'Reuv15', 'Vare93', 'Chun11', 'Meij14a', 'Scha13c', 'Hore13a', 'Bare99c', 'teR15', 'Vald16', 'Scha14f', 'Beke16', 'Gome12', 'Bax05', 'Wang15', 'Idze06a', 'Deun10a', 'Enge03', 'Gala92a', 'Schu11', 'Klei03c', 'Fust11', 'Pate17a', 'Schi13c', 'Kort98', 'Corn10', 'Luts09', 'Rooi16', 'Mend12', 'Hori10', 'deH03', 'Scha05', 'Sari11', 'Huan16', 'Scha02e', 'Vran14', 'Muen14', 'Qaiy91', 'Koui13', 'Sari16', 'Hart04a', 'Mord14', 'Schu12a', 'Kan09a', 'Gees08', 'Preh09', 'Lakh16', 'Giet10a', 'Heij09', 'Rein06', 'Samu08a', 'Gube15a', 'Gott02a', 'Klei03b', 'Syme09', 'Mann13a', 'Scha06', 'Niem03b', 'Sail04', 'Mohr16', 'Voge05', 'Ribb07', 'Smit93', 'Sala15', 'Dijk09a', 'Fuett08d', 'Ward2005', 'John01a', 'Diss10', 'Ven12', 'Troo08', 'McBr09', 'Kort02b', 'Wang12f', 'Staa04b', 'Wijk03', 'Vess16', 'Stol09', 'Nill16', 'Scha13e', 'Pomp16a', 'Thal03', 'Merg98', 'Oliv11', 'Kroe13', 'Wick07', 'Enge06', 'Scha08b', 'Hoek12', 'Meij15a', 'Prok03a', 'Eile14', 'Rikx13', 'Velt08', 'Adri11', 'Aren16', 'Will00', 'deG02', 'Heij12a', 'Klom07', 'Kobu15d', 'Veld00', 'Herm11d', 'Trui09c', 'Mele15', 'Brou05', 'Scha05c', 'Riks07', 'Grin16a', 'Luetj14', 'Heim07a', 'Nab90', 'Schm14', 'Vere03a', 'deN16', 'Idze08a', 'Nune14', 'Groo15c', 'Renn02', 'Theu12', 'Desa11', 'Aert12', 'Scha02b', 'Mele12a', 'Veth05', 'Vers97', 'Boss16b', 'Schi07', 'Hove08', 'Mol10', 'Kall12a', 'Hoeb14b', 'Kock10b', 'Mass91a', 'Hart02', 'Kuro14a', 'Madu13a', 'Brak99', 'Boom13', 'Tan12', 'Boer14', 'Broe09a', 'Ghaf13', 'Schm04', 'Vuka09', 'Slui06a', 'Berg99', 'Belk15', 'Keij11', 'Stee09', 'Deba11a', 'Thij89a', 'Gube15b', 'Bone11', 'Gove16', 'Boo12a', 'Jans16', 'Seln12', 'van15l', 'Vegt11a', 'Valv11b', 'Will07a', 'Weij13', 'Aarn13b', 'Dalm15c', 'Graaf04', 'Veni04', 'Tres16', 'Sche07c', 'Isgu09b', 'Sier16', 'Pomp16', 'Chat16', 'Meer16', 'Babo16', 'Jong11a', 'Renn03a', 'Cate05', 'Troo10e', 'Rij16', 'Troo10d', 'Char16c', 'Sard14', 'Alon09', 'Arma08', 'Verh85', 'Kars04', 'Jaco13a', 'Daerr11', 'Will07', 'Ciom15a', 'Yama16', 'Stil10', 'Lave12a', 'Wier07a', 'Sun16', 'Mang05', 'Donc12', 'Lieb15', 'Kamm00', 'Adri09a', 'Brug10', 'Buij90', 'Lass12b', 'Berg15a', 'Sleb15', 'Heer85', 'Kome11', 'Domb99', 'Fleu14', 'Bran07a', 'Schr15', 'Bare11', 'Aren11', 'Donn13', 'Kolk98', 'Mets12a', 'Keul09', 'Rose10a', 'Ding08', 'Vree16b', 'Ciom09', 'Wiel11', 'Berg10a', 'Scho11', 'Mets12e', 'van15a', 'Witj03', 'Kull11a', 'Gube15f', 'Hesc89', 'Marc12', 'Kaem96', 'Holl17a', 'Zhan14a', 'Boss01', 'Sanc06', 'Ciom16a', 'Veli13', 'Bast09', 'DeV16', 'Walk08a', 'Stou01a', 'Noeba01', 'Brun11a', 'Kale94', 'Yous16', 'Kan07', 'Ritc15a', 'Kloo14', 'Meij10a', 'Blee09a', 'Hori10a', 'Mako11', 'Vegt08', 'Ciom16', 'Mord16a', 'Giet10', 'Roess16', 'van16c', 'Lee08a', 'Dine10', 'Scha97', 'Hups10', 'Moe12', 'Jara15', 'Madu16', 'Jaco14a', 'Sari11a', 'Bert16a', 'Koui16', 'Oonk14', 'Meye12', 'Somf13b', 'Prok97c', 'Thij78', 'Bout08', 'Boo12', 'Aart12', 'Zels12', 'Giam14', 'Kobu11', 'Smit10', 'Mann04b', 'Greb14', 'Hees15', 'Kall08a', 'Klei02a', 'Vran16', 'Berk16', 'Xiao10', 'Blee05', 'Vend16', 'Venh15a', 'Gott06', 'Werr05', 'Vos08a', 'Mann10e', 'Gott07', 'Amin11', 'Aarn12', 'Bink08', 'Stie14', 'Vos11b', 'Hero14', 'Kort02a', 'van15n', 'deJ07', 'Berk96', 'Horn04', 'Renn02a', 'Chun17', 'Hamo13', 'Grin12', 'Robb11', 'Klaa17', 'Rutt15', 'Kopp06c', 'Eerd05a', 'Thij93a', 'Riel15', 'Gamb10', 'Oyen07', 'Graa10a', 'Be07', 'Dijk12', 'Isgu04', 'Timp06', 'Tan13e', 'Scho14f', 'Jaco13', 'Rikx12a', 'Beuc06', 'Aars89', 'Yaka11c', 'Luko08', 'Dijk07', 'Witt04', 'Moye14', 'Brid17', 'Dijk10c', 'Seff14', 'Mann16', 'Aart08a', 'Styb12', 'Lave07', 'in98', 'Scho17b', 'Staa04', 'Hend89', 'Jans13a', 'Arzh07c', 'Kall12', 'Brun09', 'Lass17', 'Meij17d', 'Deva17', 'Aste15', 'Lupo02a', 'Ginn05a', 'Rous01', 'Sche01a', 'Hell12', 'Eder10', 'Syme11a', 'Kort94', 'Visw14', 'Hage04', 'Poza06', 'Hove08a', 'Lamm12a', 'Durm12', 'Akyi15', 'Kapu00', 'Schi03', 'Lopa10a', 'Kroe17', 'Rads11', 'Gran03', 'Buss13', 'Venh16a', 'Leeu11', 'Enge98', 'Tixi16', 'Vend16a', 'Arif15a', 'Scha08c', 'Sieb06', 'Simo02', 'Pate17', 'Ciom10a', 'deJ11b', 'Wijs16a', 'Bern96', 'Schm12a', 'Ven15', 'Thij76', 'Vrie15a', 'Lass14', 'Budi11', 'Wies16a', 'Vrie09c', 'Gatt09', 'Scha12c', 'Geve14a', 'Laak79', 'Niem09a', 'Lang94', 'Ciha99', 'Uffm04', 'Hama13', 'Maas13', 'Fuett12a', 'Thal07', 'Witt11', 'Jans13', 'Brow09', 'Link09', 'Hees08', 'Scho15b', 'Reic91', 'Venh15c', 'Ginn03b', 'Hoge13', 'Isgu10a', 'Kan07a', 'Keij09a', 'Mann05a', 'Eise12', 'Staa07', 'Lave02b', 'Stee93', 'Post12', 'deG07b', 'Mord12', 'Avil17', 'Scha14j', 'Scha05d', 'Scha13h', 'Wieg16', 'Valv11', 'Brem99', 'Ciom13', 'Trui09a', 'Jans10', 'Riet06', 'Hari15', 'Kloo15', 'Ciom09a', 'Dijk13b', 'Heer04', 'Hesk10', 'Chri13b', 'Brun11', 'Lyck97', 'Cox11', 'deK07', 'Lopa10', 'Hanc16', 'Be03', 'Grin16', 'deR15', 'Mann06', 'Niem06a', 'Luts08', 'Berg00a', 'Klom09a', 'Kobu16', 'Li12', 'Seme13', 'Wang15b', 'Zhan07', 'Loog03', 'Hunt05', 'Geus15', 'Brec08', 'Ginn02b', 'Fort13b', 'Huss00', 'Idze08', 'Ginn17', 'Lier12', 'Blee05a', 'vanr99', 'Seab10', 'Verb09', 'Peng05a', 'Isgu04a', 'Kars08b', 'Siep10', 'Gree16', 'Brui02', 'Bald05', 'Huis05', 'Yaka10', 'Ghaf17', 'Garc05', 'Uffm05a', 'Hoeb10', 'Adri11b', 'deG07', 'Lopa10c', 'Lo12', 'Jagt09', 'Kauc15', 'Brou04', 'Ghaf16', 'Madu13', 'Heij12c', 'Rikx11', 'Fuch08', 'Prok91', 'Kobu12', 'Thal02', 'Heer97b', 'Blee07b', 'Riel15c', 'Gube11', 'Dick11', 'Zand10', 'Haas15', 'Niek14', 'Ramo13a', 'Vrie11a', 'Peet05c', 'Niem11a', 'Schu99', 'Breu12b', 'Dijk07b', 'Gamb05a', 'Gott06f', 'Char13', 'Kell12a', 'Tan13d', 'Kall15a', 'Arif14', 'Graa11', 'Murp10a', 'Soly15', 'Yaka08', 'Dijk10', 'Ciom14c', 'Steg09', 'Kauc15a', 'Idze09', 'Wang08b', 'Perr13a', 'Voge05a', 'Male10', 'Litj11', 'Velt08a', 'Arta09a', 'Bala05', 'Wrig12b', 'Fleu13', 'Sanc09b', 'McWi02', 'Chat15', 'Ahlg10', 'Hawk16', 'Scho13c', 'Nune11', 'Vos06a', 'Dels13', 'Gamb11', 'Arif14c', 'Wand15', 'Holl16b', 'Tan14', 'Post03', 'Giet07d', 'Perr13', 'Desa16', 'Bos15a', 'Vos11', 'Bake15', 'Haax07', 'Remi15', 'Bult15a', 'Loog06', 'Jaco15a', 'Land05a', 'Dana97', 'Klik06', 'Ridg15', 'Hamb12', 'Ghaf17b', 'Jost02', 'Wals00', 'Wolf93', 'Bria16a', 'Brow08a', 'Oonk15', 'Ven14', 'Stav96', 'Fuett08b', 'Mele14', 'Nill11a', 'Brou04b', 'deJ09', 'Sper02', 'Pate10', 'Eerd06a', 'Gort08a', 'Breu14', 'Mour16', 'Ginn13a', 'Deun09', 'Zhou12a', 'Bax09', 'Graa91b', 'Lave12', 'Crol11', 'Frei14', 'Gube16', 'Legt02', 'Hees12', 'Thij96', 'Mahm14', 'Rooi17', 'Kort03', 'Hill2016', 'Timp05', 'Meij17c', 'Bitt14', 'Gott10a', 'Dick13', 'Heij11', 'Idze12a', 'Brui16', 'Gott03c', 'Dess16', 'Kapu14', 'Huis01', 'Huis10', 'Lest05', 'Graa91c', 'Meye11', 'Gees15', 'Ven11a', 'Scho11a', 'Igle09', 'Mord13', 'Jaco10f', 'Moto10', 'Rutt15a', 'Srin10', 'Schu09', 'Loog04e', 'Verh91', 'Boek99', 'Blok12', 'Thom12', 'Chit11', 'Huis98b', 'Kall10', 'Vrie15', 'Reis12', 'Meij09', 'Char16a', 'Scho12d', 'Kaem00', 'Sanc04', 'Niem10', 'Kadz16a', 'Vrie09', 'Sun12', 'Troo15', 'Madu13b', 'Heet11', 'Eerd10', 'Scha05g', 'Jong09', 'Berr15a', 'Sech15', 'Leen04', 'Jaco10e', 'Boze14', 'Ven10b', 'Meij11', 'Ginn99b', 'Somf13a', 'deG12a', 'Schi10', 'Terr14a', 'Schu07', 'Idze13', 'Berg98a', 'Toxo15', 'Rijk14', 'Habr09', 'Scha14', 'Desa09', 'Stee06', 'Lo13a', 'Ramo12', 'Dalm16', 'Bol15', 'Veld00a', 'Brug13', 'Roel06', 'Choe12', 'Blee07a', 'Bare16', 'Ruij15', 'Mus12', 'Koe05', 'Bhas13', 'Scho10', 'Vrie10a', 'Kabu09', 'Veer15', 'Delh10', 'Mets12c', 'Renn04b', 'Witt97', 'Mend10', 'Loog06a', 'Wier05', 'Work17', 'Wijn10', 'Sand97', 'Valv11a', 'Shin13a', 'Klei03a', 'Vend17b', 'Hups09a', 'Ginn10', 'Will14b', 'Scho10c', 'Silv13a', 'Klae03a', 'Grin15a', 'Poet14', 'Char16b', 'Sche15a', 'Fuett06', 'Gall16', 'Navi13', 'Aart07a', 'Smit13', 'deJ11a', 'Madu11', 'Vare06', 'Wang13b', 'Bone12', 'Corn94', 'Vers14', 'He15', 'Fuett08', 'Rikx09e', 'Scha05e', 'Wate14b', 'Estr12', 'Litj15a', 'Call15', 'Hesk15a', 'Stou11', 'Jans13c', 'Murp11a', 'Brus04', 'Herp09', 'Kuro14', 'Peng07', 'Melb11', 'Lage17', 'Litj12b', 'den06', 'Koop06', 'Koop08a', 'Kobu15a', 'Geve14', 'Vos08', 'Trom12', 'Jaco14', 'Voge07', 'Bong05', 'Drie16', 'Hoek09', 'Bare16a', 'Deur01b', 'Diez14', 'Meij14', 'Thal05', 'Buss10', 'Litj14c', 'Oyen04', 'Madu09', 'Koop16', 'Verb12', 'Jaco12c', 'Niem04a', 'Kool94', 'Hesk14c', 'Dick12', 'Dijk13c', 'Kemp06', 'Gall12a', 'Thom07', 'Ginn08', 'Pegg17b', 'Cara17', 'deJ11', 'Dekk13', 'Hari16a', '04a', 'Vleu12', 'Hend06', 'Hern17', 'Klom08a', 'Meeu11a', 'Kobu13', 'Aarn16', 'Heme16', 'Rene11a', 'Tang08', 'Huls13', 'Rozi99', 'Dale07b', 'Char16', 'Stee16', 'Rott15', 'Vos06', 'Kan09', 'Broe09c', 'Slui05a', 'Ciom10', 'Kars08', 'Rozi98', 'Broc12', 'Vegt11', 'Aren15', 'Voge06', 'Hans10b', 'Meij09a', 'Haer95', 'deG06b', 'van15r', 'Niem05b', 'Vos12b', 'Hans12a', 'Meij13c', 'Stap15', 'Grin16b', 'Wate13', 'Tan05', 'Hoff16', 'Heer88a', 'Stee17', 'Buss11a', 'Stil07', 'Lage13', 'Tigc16a', 'Fue15', 'Yaka11', 'Scha05f', 'DeK09', 'Kobu15', 'Vos13c', 'Mann12b', 'Habe15', 'Lave08', 'Prok14', 'Gott04', 'Murp07', 'Boer12', 'Laar10', 'Kars10b', 'Lave00', 'Need15', 'Verh02', 'Lesn12', 'Ginn99a', 'Vrie11', 'Rikx10b', 'Lamm13', 'Brui03', 'Tula13', 'Witj00', 'Kall11', 'Firo08', 'Hoop10c', 'Wate14', 'deR15a', 'Erni84', 'Iqba08', 'Gott06d', 'Bare07a', 'Jac07', 'Usma15', 'Viss12', 'Kort99a', 'Ven10', 'Boud16', 'Eerd06', 'Chon11a', 'Behr02', 'Idze14a', 'Homo02', 'Garc16', 'Kobu11a', 'Hoog03b', 'Char15a', 'Rij05a', 'Sand99b', 'Maka10', 'Merl17', 'Arzh07', 'Fekk15', 'Scha02g', 'Vos10', 'Luyt89', 'Laar05c', 'Riks05', 'Hups12a', 'Hend12', 'Kawa08', 'Frer07', 'Muen12a', 'Jaco10d', 'Voge07c', 'Murp11', 'Kroon2017', 'Abee14', 'Cohe16a', 'ter12', 'Koui13a', 'Hoog92', 'Bast12', 'Wilb13', 'Deur01a', 'Kort99', 'Litj14b', 'Atti11', 'Claa14', 'Terl80', 'Sun14', 'Eijc11', 'Thij14a', 'Vorw94', 'Schi11a', 'Fuett09', 'Bois12', 'Petr12', 'Arta09', 'Troo10b', 'Hoss16', 'Weve99', 'Horb17a', 'Vree15a', 'Huge15a', 'Rahm11', 'Fuett08c', 'Ghad14', 'Mema05', 'Smit12a', 'Zame14', 'Lang09b', 'Kram03', 'Ashr10', 'Litj16', 'Witt12c', 'Leak14', 'Sch03a', 'Samu06', 'Kars9b', 'Uffm04a', 'Thij81', 'Lope03', 'Tan11c', 'Stou12', 'Chia08', 'Klom07a', 'Fisc09', 'Vrie14', 'Scha12d', 'Huis07', 'Stol09b', 'Aren13', 'deG06a', 'van15j', 'Viss11a', 'Blum15', 'Yana15a', 'Wand15c', 'Huis10a', 'Roth15f', 'Mavi09', 'Stri02', 'Kars93c', 'Nabu12', 'Renn03', 'Niem09', 'Vrie09a', 'Voer12', 'Cate10', 'Rein09a', 'Lakh16a', 'Zulf12', 'Kouw06d', 'Riel15e', 'Gott14a', 'Goto13', 'Puar2017a', 'Breu15', 'Lamm13a', 'Brom14a', 'Wang15a', 'Rior11', 'Bug15', 'Aart10', 'Will14', 'Thij85a', 'Wate06', 'Mets12h', 'Ghaf16a', 'Ledo96', 'Adri11a', 'Nill15a', 'Woli16', 'Frie12a', 'Klom11b', 'Dams99a', 'Esma14', 'Aria06', 'Idem12', 'Wand16', 'Broe13', 'Aart07', 'Scha14g', 'Sanc10', 'Cuyp95a', 'Graa96', 'Jans12', 'Heer89', 'Dijk10b', 'Hoes12', 'Bos15', 'Plat07', 'Wijn10b', 'Kock10', 'Koen14', 'Sard17', 'vand76', 'Graa99a', 'Idze12c', 'Blee04d', 'Lave06', 'Niel16a', 'Kok02a', 'Abbi06', 'Bare15b', 'Nott11', 'Clem10', 'Scha14a', 'Post13', 'Stol08', 'Kraa17', 'Hari16', 'Giam14a', 'Kouw04', 'Bijg16', 'Ring07', 'Viss10a', 'Velt10a', 'Laar05a', 'Deun07', 'Post04', 'Firo12a', 'Vuka08', 'Nune14a', 'Murp08', 'Nill08', 'Gamb08', 'Lang03', 'Bome12', 'Giam13', 'Pouw09', 'Hiary13', 'Firo12', 'Litj17', 'Stei17', 'Rikx10', 'Huij15', 'Bart13', 'Kars99a', 'Sche00a', 'Wijn10c', 'Mett17', 'Chri13a', 'Vaal91', 'Hans14', 'Chan06', 'Wild06', 'Deur01', 'Lave03', 'Navi11', 'Hoog15b', 'Scha14b', 'Mann99', 'Floh02', 'Nadar2017', 'Meli10', 'Lave09', 'Yoo16', 'Mets13', 'Prin13', 'Erke17', 'Mann09', 'Khan14', 'Liu17', 'Marc12c', 'Sche08d', 'Sald91', 'Phil13', 'Mann09a', 'Ginn04', 'Syme12', 'John12a', 'Graa10', 'Mets03', 'Oei13', 'Gube13', 'Weij98a', 'Beck02', 'Stol10', 'Lo10', 'Thij91', 'Huis98', 'Chen15b', 'Dijk14', 'Thij00', 'Mann09b', 'Vos07a', 'Bria13', 'Aart08b', 'Lave02', 'Oei14', 'Kest14', 'Thom14', 'Hans16a', 'Pete17a', 'Zimm04', 'Oost03a', 'Bult14a', 'Huds10', 'Mets11a', 'Scha05b', 'Haan04', 'Buch10', 'Gott03b', 'Meeu11b', 'Mann04a', 'Vos12c', 'Wrig12a', 'Chav93', 'Renn04a', 'Dese04', 'Behr02a', 'Berk14a', 'Pros13', 'Kobu14', 'Luye11', 'Kars08a', 'Klym16a', 'Uffm09', 'Jagt2016', 'Bern92a', 'Laar06', 'Kort17', 'Koet06', 'Thij84', 'Kaem94a', 'Kolk98a', 'Roos11', 'Hups13', 'Rope07', 'Lue12', 'Wies15a', 'Berg07', 'Brou04a', 'Mosh12', 'Tang07', 'Bult14', 'Kroo16', 'Zeng17', 'Litj12a', 'Gott13a', 'Litj14a', 'Oost93', 'Bipa08', 'Helm11', 'Dijk13', 'Tres16a', 'Boel08', 'Shar12', 'Koel07', 'Enge06a', 'Jong10c', 'Blee07c', 'Brak01', 'Kadi10', 'Kok03', 'Moha13a', 'Fuet06', 'Mord15', 'Scho13a', 'Hart10', 'Fort13a', 'Niem07b', 'Wijn12', 'Kort06', 'Doyl01', 'Bast06', 'Mann06c', 'Roll09', 'Mann13', 'Kort09', 'Dale07', 'Rikx05', 'As09', 'Hama11', 'Ramo15', 'Mann10c', 'Nadar2017a', 'Laur16', 'Slui04', 'Tan12a', 'Arno17', 'Rikx10a', 'Prin12a', 'Boel10', 'Uffm05', 'Scha01b', 'Rij05b', 'Srin10a', 'Vos14c', 'Aart06a', 'Hoeb14a', 'Lafe08', 'Lang01', 'Fuet07', 'Pomp17', 'Aarn11', 'Jans16a', 'Dijk14b', 'Gott10b', 'Fant16', 'Huis98a', 'Pate16', 'Beul09', 'Yen07', 'Tops16', 'Stie15a', 'Dalm17', 'Sonn15', 'Scha14i', 'Rooy11', 'Graaf00', 'Timp06a', 'Nada17', 'Schi06', 'Eerd04', 'Lerr13', 'Alta13', 'Gamb05', 'Garc06', 'Samu11', 'Holl15c', 'Rijp14', 'Roll08', 'Leen03a', 'Dijk10a', 'Scha96', 'Hoge10b', 'Snoe07', 'Rooy90', 'Brin09a', 'Luij09', 'Brin08a', 'Mend06', 'Timp10', 'Litj10a', 'Veli09a', 'Hoog88a', 'Quak15', 'Seti13', 'Engb12', 'Madu11b', 'Corn93', 'Jaco11c', 'Kopp06b', 'Sie97', 'Schi08', 'Puar2017', 'Smit15', 'Prok03', 'Lage12', 'Meij12a', 'Mann10d', 'Maat14', 'Bond02', 'Balo13', 'Joos10', 'Sanc09a', 'Brou02', 'Vos11a', 'Meijer2017', 'Heyd11', 'Dijk07c', 'Berd00', 'Ehte16', 'Rikx09', 'Riad13', 'Bail16', 'Jaco11', 'Keij11a', 'Gall14', 'Wijn17', 'Sche08a', 'Stol96', 'Litj11b', 'Holl16', 'Delg12', 'Hame13', 'Zwee98', 'Ginn03', 'Chri11', 'Slui03a', 'Ven10c', 'Luet15', 'Dana99', 'Kolw09', 'Cloo85', 'Nete06', 'Gova12', 'Hups13a', 'Bare90', 'Heuv16', 'Ginn98', 'Somf12', 'Kock17a', 'Corn95', 'Seti14', 'Meij15b', 'Deun09a', 'Imai12', 'Bakk01a', 'Muse16', 'Kall15', 'Jaco10', 'Kall15b', 'Hoes12a', 'Hees06', 'Schi09', 'Roru16a', 'Hooi07', 'daS11', 'Vree15', 'Oost89', 'Giet07a', 'Hans13', 'Niem11', 'Vent14', 'Murp10', 'Stil12', 'Nill07', 'Arzh10', 'Leen03', 'Schu02', 'Veli10a', 'Waai07a', 'Thij02', 'Kars16', 'Veli12', 'Wimm16', 'Nill09a', 'Wata16a', 'Zhai15', 'Cesp97', 'Srik12', 'Oei16a', 'Balm04', 'Scha14c', 'Gott04b', 'Brin09', 'Vrie05', 'Kuij10', 'Meij17', 'Moha11', 'Troo10c', 'Eerd03', 'Fort17a', 'Boet01', 'Breu10', 'Heij15a', 'Roth02', 'Corn94a', 'Mann10b', 'Geur12', 'Lopa10b', 'Reed12', 'Geus08', 'Brom11', 'Zhao16', 'Wage06', 'Takx14', 'Gube16a', 'Murp08a', 'Mann04', 'Taou13', 'Stie15b', 'Gool91', 'Dong10', 'Eijc13', 'Keij08a', 'Selv06', 'Gijs17', 'Bozo16', 'Hore14b', 'deG06d', 'Makr14', 'Pegg17', 'Kars98', 'Sanc09', 'Blic06', 'Mohs15', 'Gees17', 'Gijs15', 'Brom12', 'Groo15', 'Rikx10c', 'Mann15a', 'Lang99', 'Kost16a', 'Dien99', 'Brou04c', 'Huys00', 'Vend17a', 'Wijk02', 'Venh17a', 'Oei16', 'Niem09b', 'Poza08', 'Scho11c', 'Witt10', 'Kouw05', 'Moha15', 'Dijk07e', 'Murp09', 'Heer88', 'Lo09', 'Gott02', 'deG12', 'Berr17', 'Kars87', 'Verg17', 'Ploe10', 'Beic11', 'Deun10', 'Ginn06b', 'Winf15', 'Over14', 'Sche08c', 'Bosc17', 'Lerr13a', 'Ginn02', 'Aria04', 'Wens06', 'Will14a', 'Heuv17b', 'Schi14', 'Hoog91', 'Abas05', 'Gamb07', 'Kouw04a', 'Wilb15', 'Budd10', 'Kuij07', 'Kort98a', 'Brak98', 'Ayez13', 'Ciet11', 'Kars88', 'Wijs13', 'Back10', 'Hama06', 'Amir13', 'Nabu12a', 'Inag14', 'Thij77', 'Gees17a', 'Zhao09', 'Mele16', 'Kare14', 'Maur14', 'Hove04', 'Liu15a', 'Wood97', 'Kan10', 'Lave14', 'Mari16', 'Capp99', 'Hamb08', 'Kobu16a', 'Wong16', 'Oost03', 'Corn05', 'Zink97', 'Sith10', 'Nill09', 'Eijk12', 'Meij12', 'Maff01', 'Schw00', 'Prok01a', 'Brin09b', 'Muse13', 'Koui17', 'Brom10a', 'Rikx08a', 'Lise08', 'Witt12a', 'Oyen03', 'Rikx12b', 'Gott03a', 'Boom12', 'Kars99', 'Will01', 'Hoor14', 'Schi11', 'Jans07', 'Humm17', 'Rooi94', 'Ginn99', 'Usui14a', 'Phil09', 'Terr14b', 'Gube15', 'Niek09', 'Danc16', 'Wang14', 'Broe06', 'Lage15a', 'Mang02', 'Schu99a', 'Hu10', 'Kroo16a', 'Wies16', 'Cool99', 'Abel95', 'Poll10', 'Bomm14', 'van15c', 'Klom01', 'Hayd15a', 'Bejn14', 'Heer07', 'Timp02', 'Seln16', 'Bax03', 'Vos12', 'Capp00', 'Liu14', 'Zels17', 'Mert17', 'Mavi12', 'Mass98', 'Ginn10a', 'Brec12', 'Kwit13', 'Nock05', 'Schi13', 'Rubi99', 'Prin13a', 'Boer03', 'Vuka11', 'Nete15', 'Aria13', 'Scho12c', 'Loog04f', 'Rutt16', 'Fort14a', 'Oei17a', 'Rutt09', 'Thom13b', 'Nege96', 'Wout12', 'Blee04c', 'Oyen13', 'Meij16a', 'Meli10b', 'Daou17', 'Gras07', 'Luet14a', 'Lang97', 'Bom98', 'van16', 'Heij12', 'Verd07', 'Zand04', 'Scha07', 'Rij04', 'Oree06', 'Asse11', 'Ohta09a', 'Vare05', 'Isgu12', 'Zels13', 'Kars92', 'Kars90', 'Fe14', 'Firo10', 'Silv17b', 'Vent12', 'Kann00', 'Witt13', 'Bodd08', 'Luet14', 'Davi06', 'Scho10b', 'den03', 'Kall12c', 'Prok99', 'Vos09', 'Scha09a', 'Kock12', 'Brun07a', 'Hout01', 'Kopp06', 'John01', 'Bom00', 'Dale07a', 'Beum17', 'Reed12a', 'Laud16', 'Berg08', 'Moto10a', 'Drai09', 'Trui08', 'Enge06b', 'Vrie09b', 'Vugt11', 'Kuma15', 'Jaco11b', 'Snij13', 'Atsm08', 'Gube15e', 'Keij10', 'Hamb12b', 'Reek04', 'Pete17b', 'Cao2017', 'Sche04', 'Muhs06b', 'Post03c', 'Ten11', 'Niem03a', 'Litj14d', 'Feng10', 'Vlie05', 'Kopp03', 'Kamm04', 'Riel13', 'Turi50', 'Scha13d', 'Kars96b', 'Kome11a', 'Kobu14b', 'Mann08a', 'Nonn17', 'Peem13', 'Hesc88', 'Jong10a', 'Puar15', 'Hoop12', 'Yama16a', 'Roel03', 'Hesk15', 'Ten09', 'Ehte16a', 'Abas05a', 'John13', 'Barb05', 'Samu11c', 'Hols95', 'Stoi17a', 'Breu11', 'Puar16a', 'Holl17', 'Herm11', 'Eerd03a', 'Sarr12', 'Prok97b', 'Verz09', 'Sikk09', 'Klom11a', 'Zyl-17', 'Tan16a', 'Heij12e', 'van15k', 'Frer13', 'Rikx07', 'Silv13', 'Ramo13', 'Muen09', 'deG04', 'Klae03', 'Plan14a', 'Meij09b', 'Blok14', 'Mann12a', 'Klom04', 'Fuij12a', 'Meij12b', 'Sche05', 'Os11', 'Deba10', 'Kess15', 'Iers07', 'Kok04', 'MacL08', 'Jans02', 'Klom06', 'Valv11c', 'Deur93', 'Ruer09', 'Imai12a', 'Vos10c', 'Wu11', 'Vos16', 'Viss08', 'Chen15', 'Litj14e', 'Jong08', 'Kobu15b', 'deG07a', 'Renn04', 'Kars93a', 'Ginn08a', 'Klom03', 'Luetj17', 'Sana11a', 'Jans15', 'Isgu07', 'Idze07', 'Beck16', 'Ginn07', 'Gatt10', 'Rij14a', 'Berr15', 'Cohe17', 'Scha01a', 'Lamm12', 'Reim90', 'Moe11', 'Stie15', 'Schi13a', 'Deur03', 'Koui14', 'Beic13', 'Huo11', 'Muen12b', 'Rich11', 'Boer11a', 'Gala93a', 'Weid11', 'Krab09', 'Teki91', 'Veld99a', 'Schu01', 'Lang99b', 'Alex15', 'Fuett08a', 'Laar04', 'Lave01', 'Choe13', 'Enoc99', 'Idze05', 'Pete15', 'Sand99', 'Wess06', 'Leli08', 'John12', 'Madu14', 'Verh93a', 'Voer17', 'Ploe05', 'Mand02', 'Samu10', 'Buss14', 'McWi98', 'Ginn05', 'Rose11', 'Meij12c', 'Fleu14c', 'Dams99', 'Kare11', 'van16d', 'Holl15', 'Devo05', 'Dalm15a', 'Seti17', 'Loog04c', 'Slui05', 'Prok98', 'Scha03a', 'Kars11', 'Dijc11', 'Sanc15a', 'Boer17', 'Lave10', 'Vleu13', 'Xu16c', 'Ma13', 'Stou05', 'Muen12', 'Hesk14a', 'Oest91', 'Ginn00', 'Uffm05b', 'deB16', 'Pike15', 'Voer14', 'Meijer2017a', 'Dupp15', 'Boud16a', 'Steg10', 'Ginn06a', 'Math14', 'Gott10', 'Gott10c', 'Keij10a', 'Kooi16', 'Arzh07b', 'Wens11', 'Mele17', 'Oei17', 'Ginn08d', 'Berk14', 'Meij13', 'Schr11', 'Koen15', 'Grub06', 'Niem07a', 'Tan11d', 'Oei14a', 'Hoeb11', 'Scha11', 'Blue10', 'Yim09a', 'Niem05c', 'Syme11', 'Huis98c', 'Vree16', 'Rema16', 'Frel09', 'Arif16b', 'Brin13', 'Zand00', 'Heuv17', 'Scha13f', 'Oe15', 'Leac12', 'Vegt10a', 'Scho12b', 'Idze08c', 'Deun09b', 'Berg96', 'Staa02', 'Wage12', 'Hamb12a', 'Facc12', 'Nage13', 'Bome16a', 'Aste08', 'Pegg17a', 'Das07', 'Jans12a', 'Berc15', 'Mann07a', 'Rikx11b', 'Corn95a', 'Lava09', 'Verh04a', 'Mole13', 'Rodr17', 'Scha13b', 'Vrie10d', 'Arnt15', 'Tan13c', 'Berk08', 'Mann06a', 'Gill10a', 'Kock14', 'West2011', 'Jans14c', 'Sloc13', 'Rijp13', 'Mann09c', 'Schu04', 'Sanc11', 'Rene07', 'Heuv17a', 'Brom14', 'Ginn00b', 'Uffm01', 'Mets13a', 'Esbe10', 'Schm92a', 'Hoop09', 'Hack15', 'Koen16', 'Deur94a', 'Kopp06d', 'Lohn15', 'Habe15a', 'Brak99b', 'Jaco12b', 'Troo06', 'Dijk13a', 'Char15', 'van15m', 'Rutt11', 'Stol09a', 'Boet07', 'Maas13a', 'Thij90', 'Thor12', 'Weij15a', 'Garc08a', 'Scho13', 'Kars03', 'Hoes11', 'Quak11', 'Koop08', 'Keij08', 'Simo08', 'Romi89a', 'Kort02', 'Lage14', 'Eerd05b', 'Scho16', 'Graa08', 'Petr14', 'Tan11', 'Oost91', 'Hups08', 'Hutt16', 'Kort00b', 'Roer15', 'Jaco12a', 'Fraa90', 'Kaem97', 'Wal14', 'Schu06', 'Verh04', 'Uden15', 'Valv10', 'Thij92', 'Holl15b', 'Ginn13', 'Giet07c', 'Meel16', 'Blee04', 'Dese10', 'Scha01c', 'Pros14', 'Lest11', 'Saar02', 'Ginn01b', 'Oldh98', 'Isgu05a', 'Vree15b', 'Fran14', 'Eras08', 'Jagt14', 'van15q', 'Luet14c', 'Groo16', 'Trui09', 'Cann08a', 'Scho15', 'Este17', 'Hoek03', 'Verd09', 'Abuh08', 'Ter11', 'Schu09a', 'Mend15a', 'Rene03a', 'Kok01', 'Lanc85', 'Klom11', 'Muse14a', 'Mert16', 'Aald17a', 'Phil14a', 'van16b'])
In [21]:
def get_from_string_rule(value):
if value in string_rules:
return string_rules[value].replace('_', ' ').strip()
else:
return value
def print_item(key):
print(key)
bib_item = global_index[key]
print(bib_item.author)
print(bib_item.title)
print(HTML_formatter(bib_item))
print(bib_item.doi)
print(bib_item.pmid)
print()
for key in ('Hump17', 'Riel17', 'Oei16a', 'Ghaf17b', 'Mele17'):
print_item(key)
Hump17
G.E. Humpire Mamani, A. Arinda Adiyoso Setio, B. van Ginneken and C. Jacobs
Organ detection in thorax abdomen CT using multi-label convolutional neural networks
in: <i>Medical Imaging</i>, volume 10134 of Proceedings of the SPIE, 2017
http://dx.doi.org/10.1117/12.2254349
Riel17
S.J. van Riel, F. Ciompi, C. Jacobs, M.M. Winkler Wille, E.T. Scholten, M. Naqibullah, S. Lam, M. Prokop, C. Schaefer-Prokop and B. van Ginneken
Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines
, <i>European Radiology</i> 2017
http://dx.doi.org/10.1007/s00330-017-4767-2
http://www.ncbi.nlm.nih.gov/pubmed/28293773
Oei16a
M.T. H. Oei, F.J.A. Meijer, W. van der Woude, E.J. Smit, B. van Ginneken, R. Manniesing and M. Prokop
Interleaving Cerebral CT Perfusion with Neck CT Angiography. Part II: Clinical Implementation and Image Quality
, <i>European Radiology</i> 2017;27(6):2411-2418
http://dx.doi.org/10.1007/s00330-016-4592-z
Ghaf17b
M. Ghafoorian, A. Mehrtash, T. Kapur, N. Karssemeijer, E. Marchiori, M. Pesteie, C.R. G. Guttmann, F. de Leeuw, C.M. Tempany, B. van Ginneken, A. Fedorov, P. Abolmaesumi, B. Platel and W.M. Wells
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation
in: <i>Medical Image Computing and Computer-Assisted Intervention</i>, 2017
Mele17
J. Melendez, R.H.H.M. Philipsen, P. Chanda-Kapata, V. Sunkutu, N. Kapata and B. van Ginneken
Automatic versus human reading of chest X-rays in the Zambia National Tuberculosis Prevalence Survey
, <i>International Journal of Tuberculosis and Lung Disease</i> 2017;21:880-886
http://dx.doi.org/10.5588/ijtld.16.0851
http://www.ncbi.nlm.nih.gov/pubmed/28786796
In [22]:
author_index = defaultdict(set)
for bib_key, bib_item in global_index.items():
try:
authors = bib_item.authors
for first, von, last, jr in authors:
author_index[last].add(bib_key)
except AttributeError:
print('--------------')
print(bib_key)
print('--------------')
In [23]:
parse_authors(global_index['Hoss16']['author'])
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-23-d99bd163ac66> in <module>()
----> 1 parse_authors(global_index['Hoss16']['author'])
TypeError: 'BibItem' object is not subscriptable
In [233]:
global_index['Amin11']['author']
Out[233]:
'{S. Amin and J.G. Goldin and M.R. Zeidler and E. Kleerup and P. Lu and M. Galperin-Aizenberg and E. M. van Rikxoort and D. Gjertson and D. Ross}'
In [201]:
for type_name, entries in index.items():
print(type_name)
print(entries[0])
@InProceedings
Abas05a,
author = {D. Ab\'asolo and C. G\'omez and J. Poza and M. Garc\'ia and C. I. S\'anchez and M. L\'opez},
title = {{EEG} background activity analysis in {A}lzheimer's disease patients with sample entropy},
booktitle = {International Conference on Computational Bioengineering},
year = {2005},
pages = {1067--1076},
optnote = {DIAG, RADIOLOGY},
owner = {clarisa},
timestamp = {2010.06.24},
@Conference
Amin11,
author = {S. Amin and J.G. Goldin and M.R. Zeidler and E. Kleerup and P. Lu and M. Galperin-Aizenberg and E. M. van Rikxoort and D. Gjertson and D. Ross},
title = {Air trapping on {HRCT} assessed by quantitative image analysis as an early predictor of bronchiolitis obliterans syndrome in lung transplant recipients},
booktitle = ATS,
year = {2011},
abstract = {{RATIONALE:} {C}urrent diagnosis of bronchiolitis obliterans syndrome ({BOS}) in lung transplant recipients by spirometry identifies the disease process after the point at which treatment appears to be effective. Earlier identification of BOS may allow improved outcomes. We aim to identify early predictors of {BOS} by quantitatively assessing air trapping in computed tomography scans ({HRCT}) of transplanted lungs. Previous studies of air trapping by visual analysis of {HRCT} were poor at early identification of {BOS}. {METHODS:} {T}he clinical {HRCT} images of eight lung transplant recipients who met spirometric criteria for {BOS} by {FEV1}, and who had the absence of infection and rejection confirmed by bronchoalveolar lavage and transbronchial biopsy within one month of spirometry, were reviewed. For each patient, the {HRCT} within one month of the spirometric diagnosis of {BOS} (visit 2) was evaluated. A previous {HRCT} (visit 1) at least two months prior to visit 2 and six months after transplantation was compared. Semi-automatic lung and lobar segmentation followed by quantitative image analysis were performed on the images of the transplanted lung at residual volume ({RV}) and total lung capacity ({TLC}). For each scan, previously published quantitative measures of air trapping were assessed: lobar volume at {RV} ({RVCT}), whole lung {RV/TLC} ratio ({RV/TLCCT}), density masks between -950 and -860 {HU} at {RV} ({DM}-950-860), median {HU} at {RV}, and 10th percentile {HU} at {RV} were computed. The changes in these measurements between visits 1 and 2 were compared using a t-test. {RESULTS:} {V}isit 1 scans were an average of 144 (range 42-243) days prior to visit 2 scans. The mean {RVCT} increased 52.53 cc (p=.48) and the mean change in {RV/TLCCT} increased 3.35% (p=0.47) at visit 2 when compared to visit 1. The {DM}-950-860 of the expiratory images increased by 0.48 % (p=0.78) from visit 1 to visit 2. Between the two visits, the average median {HU} at {RV} and 10th percentile of {HU} at {RV} decreased by 0.24 % (p=0.95) and 0.32 % (p=0.85), respectively. {CONCLUSION:} {I}n our small sample of lung transplant patients, we found that quantitative measures of air trapping seen at the time of spirometric {BOS} diagnosis were also seen approximately five months earlier. These measures may serve as an earlier marker of chronic lung transplant rejection; however, additional analysis of {CT} images over an extended period of time is necessary.},
optnote = {DIAG, RADIOLOGY},
owner = {Eva},
timestamp = {2011.07.05},
@Misc
Mann09a,
author = {R. Manniesing},
title = {Read and Write Support for MevisLab Dicom/Tiff Format},
year = {2009},
url = {http://www.insight-journal.org/browse/publication/311},
abstract = {MevisLab [2] is a development environment for medical image processing and visualization, which supports the reading and writing of combined dicom/tiff images. In this document we provide the source code (ImageIO factory) and testing data for the Insight Toolkit (ITK) framework [4].},
authors = {manniesing},
citeseerurl = {http://www.insight-journal.org/browse/publication/311},
file = {Mann09a.pdf:pdf\\Mann09a.pdf:PDF},
optmonth = {Oct},
optnote = {DIAG, RADIOLOGY},
owner = {rashindra},
timestamp = {2010.12.03},
@Patent
Leem17a,
author = {S.C. van de Leemput and B. van Ginneken and R. Manniesing},
title = {Deriving {3D} {CT} and Perfusion Images from one {4D} {CT} Image with Deep Learning},
year = {2017},
nationality = {European Patent},
owner = {rashindra},
timestamp = {2017.02.03},
@MastersThesis
Gube10,
author = {Gubern-M\'erida, A.},
title = {Multi-class probabilistic atlas-based segmentation method in breast {MRI}},
year = {2010},
file = {Gube10.pdf:pdf/Gube10.pdf:PDF},
optnote = {DIAG, RADIOLOGY},
owner = {michiel},
school = {Universitat de Girona / Radboud University Nijmegen},
timestamp = {2010.07.14},
@InCollection
Phil2016,
author = {Philips, Bart WJ and Scheenen, Tom W},
title = {Methodology of Clinical MRS: Technical Challenges and Solutions},
booktitle = {Magnetic Resonance Spectroscopy of Degenerative Brain Diseases},
year = {2016},
publisher = {Springer},
pages = {31--54},
optnote = {RADIOLOGY, BioMR},
@String
AA = _Age_and_Ageing_
@Comment
jabref-meta: databaseType:biblatex;
@PhdThesis
Aart09,
author = {Frits Aarts},
title = {Cytoreductive Surgery and Radioimmunotherapy to treat Peritoneal Carcinomatosis of Colorectal Cancer},
year = {2009},
url = {http://repository.ubn.ru.nl/handle/2066/65647},
copromotor = {T. Hendriks},
file = {Aart09.pdf:pdf\\Aart09.pdf:PDF},
optmonth = {January 30},
optnote = {TRACER, NM, RADIOLOGY},
owner = {Sjoerd},
promotor = {R.P. Bleichrodt, O.C. Boerman, W.J.G. Oyen},
school = {Radboud Universiteit Nijmegen},
timestamp = {2015.01.15},
@Article
Oe15,
author = {{{\"{O}}zdemir-van Brunschot}, Denise M D. and Rottier, Simone J. and {den Ouden}, Judith E. and {van der Jagt}, Michel F. and d'Ancona, Frank C. and Kloke, Heinrich and {van der Vliet}, Daan J A. and {Schultze Kool}, Leo J. and Warl{\'{e}}, Michiel C.},
title = {Preoperative CT-Angiography Predicts Ex Vivo Vein Length for Right Kidneys After Laparoscopic Donor Nephrectomy.},
journal = {Ann Transplant},
year = {2015},
language = {eng},
volume = {20},
pages = {532--538},
doi = {10.12659/AOT.894131},
url = {http://dx.doi.org/10.12659/AOT.894131},
abstract = {BACKGROUND Implantation of a kidney with a short renal vein is technically more challenging and therefore prone for technique-related complications. It remains unclear whether pre-operative computed tomography angiography (CTA), to assess vascular anatomy of the donor kidney, can be used to predict renal vein length. MATERIAL AND METHODS Right and left renal vein lengths of 100 consecutive kidney donors were measured in an oblique-coronal plane multiplanar reconstruction image of 100 consecutive kidney donors in whom ex vivo vein length was measured after recovery. In a second retrospective cohort of 100 consecutive kidney donors donating a right kidney, preoperative CTA vein length measurements were correlated to anastomosis time and early graft outcome. RESULTS Left and right renal vein lengths, measured on CTA, were 43.2 mm and 30.0 mm, respectively. No correlation was found between CTA and ex vivo measurements for the left renal vein (p=.610), whereas a significant correlation was found for the right renal vein (p=.021). In the retrospective cohort, right renal vein length was significantly correlated with the anastomosis time but not with early graft outcome. CONCLUSIONS The length of the right, but not the left, renal vein can be predicted by preoperative CTA, but this does not hold true for the left renal vein.},
institution = {Department of Surgery, Radboud University Medical Center, Nijmegen, Netherlands.},
medline-pst = {epublish},
optnote = {RADIOLOGY},
owner = {Leonie},
pii = {894131},
pmid = {26356283},
timestamp = {2015.12.07},
@Electronic
Pate16,
author = {Patel, A. and Manniesing, R.},
title = {Automatic interpretation of {4D} computed tomography images in acute stroke},
year = {2016},
url = {http://dx.doi.org/10.1117/2.1201609.006617},
month = {sep},
doi = {10.1117/2.1201609.006617},
file = {:pdf\\Pate16.pdf:PDF},
journal = {{SPIE} Newsroom},
optnote = {DIAG, RADIOLOGY},
owner = {Ajay},
publisher = {{SPIE}-Intl Soc Optical Eng},
timestamp = {2016.09.28},
@Book
Beic11,
author = {R. Beichel and M. de Bruijne and B. van Ginneken and S. Kabus and A. Kiraly and J. M. Kuhnigk and J. McClelland and K. Mori and E. M. van Rikxoort and S. Rit},
title = {The {F}ourth {I}nternational {W}orkshop on {P}ulmonary {I}mage {A}nalysis},
year = {2011},
publisher = {CreateSpace.com},
url = {http://www.amazon.com/Fourth-International-Workshop-Pulmonary-Analysis/dp/1466200162/},
abstract = {This was the fourth time that a satellite workshop solely devoted to pulmonary image analysis was held in conjunction with the Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference. We have received many high quality submissions for the fourth edition of this workshop. All papers underwent a thorough peer review process. A team of 21 scientists performed peer-reviews, and each paper received at least three detailed reviews. Out of the 24 accepted papers, eight were selected for oral presentation, fourteen for poster presentation and two for software demonstration. In addition, the workshop included an invited keynote talk given by Heidi Roberts, Professor of Radiology at the University of Toronto. The proceedings of this workshop are organized into two parts. The first part consists of sixteen regular workshop papers that deal with different aspects of pulmonary image analysis, including topics like segmentation, registration, quantification, computer-aided detection/diagnosis of lung disease, and visualization. The second part of the proceedings is a collection of papers submitted for the international segmentation challenge called LOLA11 (LObe and Lung Analysis 2011, http://www.lola11.com). The goal of LOLA11 was to compare methods for (semi-) automatic segmentation of the lungs and lobes from chest computed tomography scans. Nine international teams participated in this challenge. We thank the organizers of MICCAI 2011 for handling the workshop logistics and all the colleagues that were involved in the peer-review process. We are grateful to Siemens Corporate Research, MedQIA, Philips Healthcare, and VIDA Diagnostics for the financial support of the Fourth International Workshop on Pulmonary Image Analysis.},
file = {Beic11.pdf:pdf\\Beic11.pdf:PDF},
optnote = {DIAG, RADIOLOGY},
owner = {Eva},
timestamp = {2011.09.27},
@InBook
Kars10b,
author = {Karssemeijer, Nico and Snoeren, Peter R.},
title = {Image Processing},
booktitle = DIGMAM,
year = {2010},
editor = {Bick, U. and Diekmann, F.},
series = {Medical Radiology},
note = {10.1007/978-3-540-78450-0_5},
publisher = {Springer Berlin Heidelberg},
isbn = {978-3-540-78450-0},
chapter = {5},
pages = {69-83},
url = {http://dx.doi.org/10.1007/978-3-540-78450-0_5},
abstract = {Image processing is a crucial element of modern digital mammography. Optimizing mammogram presentation may lead to more efficient reading and improved diagnostic performance. Despite that the effects of image processing are often much larger than those of acquisition parameter settings, little is known about how image processing can be optimized. Experts agree that comparison of features in various mammographic views is very important. This issue must be addressed by processing. Variation of image presentation across views and subsequent mammograms should be minimized. The dynamic range of electronic displays is limited. Therefore, processing techniques should be designed to limit the dynamic range of mammograms. This can effectively be done by applying peripheral enhancement in the uncompressed tissue region near the projected skin?air interface. Adaptive contrast enhancement can be applied to enhance micro-calcifications and dense tissue in the interior of the mammogram. Mammogram processing should be aimed at displaying all relevant information in good contrast simultaneously, as human interaction to manipulate contrast during reading is too time-consuming to be applied on a regular basis.},
file = {Kars10b.pdf:pdf/Kars10b.pdf:PDF},
keyword = {Medicine & Public Health},
optnote = {DIAG, RADIOLOGY},
timestamp = {2011.04.20},
In [ ]:
In [117]:
def decode_latex(input_string, print_error_key=None):
'''
replace latex characters with unicode
'''
try:
return input_string.encode('utf-8').decode('latex')
except Exception as e:
if print_error_key:
print('{} : warning: encoding error!!!'.format(print_error_key))
print(e)
return input_string
In [ ]:
def get_entry(entry):
bib_key = entry[:entry.index(',')]
content = get_entry_content(entry)
if 'author' in content:
content['author'] = parse_authors(decode_latex(content['author']))
for key in 'title', 'abstract':
if key in content:
content[key] = decode_latex(content[key])
return bib_key, content
Content source: DIAGNijmegen/literature
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