Pubmed_CB
Zomparelli_GL
2023-07-26
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########################### BUSCA NO PUBMED #########################
# pacotes
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(RISmed)## Warning: package 'RISmed' was built under R version 4.3.1# palavra-chave de interesse
search_topic <- "weee"
search_query <- EUtilsSummary(search_topic, retmax = 1000)
summary(search_query)## Query:
## "weee"[All Fields]
##
## Result count: 517QueryId(search_query)## [1] "37442475" "37441409" "37300404" "37174242" "37154778" "37085683"
## [7] "37078423" "37058236" "37043296" "37012563" "36995505" "36987169"
## [13] "36934572" "36850984" "36844893" "36772010" "36769929" "36507095"
## [19] "36502638" "36501458" "36413067" "36363253" "36226123" "36206656"
## [25] "36146058" "36097308" "36089035" "36050312" "36011640" "36011636"
## [31] "35939950" "35870363" "35789746" "35779620" "35691194" "35689973"
## [37] "35657548" "35603922" "35512556" "35508235" "35475807" "35472614"
## [43] "35462290" "35427901" "35420779" "35407686" "35395522" "35364180"
## [49] "35282173" "35212576" "35202270" "35175436" "35160542" "35160474"
## [55] "35155992" "35151134" "35141823" "35132386" "35104545" "35055588"
## [61] "34973572" "34948553" "34947183" "34923185" "34908068" "34906834"
## [67] "34896721" "34885483" "34871882" "34851486" "34773908" "34771760"
## [73] "34735538" "34726090" "34683820" "34666086" "34619188" "34619185"
## [79] "34616648" "34600293" "34597928" "34581643" "34502032" "34501885"
## [85] "34500651" "34476712" "34410600" "34378139" "34371353" "34323747"
## [91] "34312751" "34279300" "34252663" "34218064" "34215982" "34134409"
## [97] "34121516" "34069410" "34056348" "33947020" "33946621" "33946200"
## [103] "33884548" "33838506" "33838389" "33773338" "33773154" "33765563"
## [109] "33761368" "33743338" "33743154" "33665699" "33618466" "33601178"
## [115] "33592321" "33588713" "33561771" "33477516" "33476959" "33406001"
## [121] "33308953" "33297517" "33281044" "33275192" "33254638" "33243638"
## [127] "33241733" "33171687" "33071476" "33059196" "33045436" "33040288"
## [133] "33023179" "33010546" "32923546" "32892092" "32829262" "32805603"
## [139] "32715338" "32693685" "32645852" "32638300" "32617815" "32608707"
## [145] "32557023" "32533494" "32531672" "32494109" "32474304" "32464780"
## [151] "32401631" "32388403" "32335485" "32330828" "32310119" "32305760"
## [157] "32250915" "32148304" "32091000" "32069729" "32062437" "32062281"
## [163] "32007879" "32004884" "31991344" "31918651" "31879115" "31864064"
## [169] "31864013" "31806284" "31796321" "31782095" "31756839" "31740297"
## [175] "31669676" "31646235" "31627320" "31627086" "31610473" "31563840"
## [181] "31541924" "31470497" "31470263" "31450178" "31429386" "31421486"
## [187] "31376966" "31351651" "31351637" "31351609" "31351598" "31280060"
## [193] "31279395" "31220758" "31203943" "31203937" "31170651" "31129902"
## [199] "31129466" "31109542" "31109518" "31096423" "31090011" "31079731"
## [205] "31079647" "31067685" "31030164" "31015086" "31001771" "30862075"
## [211] "30803592" "30793245" "30791650" "30774041" "30739853" "30736727"
## [217] "30691910" "30691900" "30642166" "30594016" "30509579" "30502531"
## [223] "30370832" "30366271" "30356001" "30343810" "30343809" "30268981"
## [229] "30268020" "30173027" "30165280" "30078953" "30014768" "30008413"
## [235] "29996450" "29925487" "29890593" "29783730" "29778831" "29778681"
## [241] "29710588" "29687747" "29626841" "29605307" "29602027" "29574370"
## [247] "29502494" "29496382" "29471166" "29470417" "29438937" "29353112"
## [253] "29289283" "29274687" "29269282" "29254608" "29244778" "29146398"
## [259] "29145100" "29058259" "29032002" "29030119" "28967530" "28951149"
## [265] "28946505" "28898811" "28828967" "28803340" "28784296" "28778001"
## [271] "28757222" "28751173" "28739025" "28685328" "28669496" "28636053"
## [277] "28587804" "28579144" "28521663" "28505070" "28483368" "28412098"
## [283] "28402832" "28392121" "28367757" "28353257" "28347586" "28343744"
## [289] "28318965" "28284143" "28215971" "28142111" "28126573" "28094158"
## [295] "28091997" "28089397" "28072866" "28038903" "28034614" "27912186"
## [301] "27898327" "27890594" "27836519" "27793304" "27575028" "27543174"
## [307] "26980485" "26970844" "26873014" "26860423" "26852754" "26783101"
## [313] "26704063" "26653360" "26626812" "26597372" "27769652" "27769650"
## [319] "27744159" "27723459" "27712943" "27687078" "27679968" "27678000"
## [325] "27673726" "27602948" "27596942" "27594574" "29989748" "27554437"
## [331] "27520390" "27478027" "27425863" "27425861" "27353372" "27329553"
## [337] "27281541" "27262786" "27206753" "27184448" "27181905" "27179704"
## [343] "27140655" "27086844" "27060658" "27033992" "26944864" "26820611"
## [349] "26728288" "26709550" "26449571" "26431677" "26413051" "26376121"
## [355] "26351732" "26347415" "26323203" "26264931" "26209344" "26139137"
## [361] "26087646" "26086878" "26070501" "26059074" "26055751" "26054962"
## [367] "26028407" "26022405" "25990983" "25947126" "25946954" "25913003"
## [373] "25869844" "25797074" "25782361" "25776743" "25746178" "25716742"
## [379] "25618642" "25599136" "25488733" "25464945" "25460941" "25453321"
## [385] "25406121" "25395159" "25281341" "25173859" "25062546" "24997795"
## [391] "24984918" "24910142" "24768515" "24726822" "24681442" "24633555"
## [397] "24632487" "24613592" "24491317" "24209362" "24068305" "24045170"
## [403] "24040839" "24035727" "24011783" "23973476" "23973472" "23933454"
## [409] "23921179" "23910246" "23899476" "23892135" "23890798" "23831004"
## [415] "23746984" "23651788" "23566340" "23561798" "23454465" "23360773"
## [421] "23337392" "23323842" "23305811" "24587980" "23246772" "22993131"
## [427] "22951495" "22921899" "22921510" "22884581" "22851536" "22851535"
## [433] "22840636" "22784477" "22552041" "22492263" "22463615" "22452958"
## [439] "22424707" "22410623" "22398030" "22370049" "22126427" "22115841"
## [445] "22107914" "22014584" "21963338" "21939231" "21939226" "21839627"
## [451] "21824987" "21824985" "21820883" "21771871" "21751577" "21742626"
## [457] "21536380" "21470841" "21399802" "21376556" "21342702" "21242175"
## [463] "21236569" "21147524" "21147523" "21146974" "20952178" "20951410"
## [469] "20843675" "20705678" "20696562" "20675114" "20570559" "20406755"
## [475] "20231083" "20117791" "20031385" "20022623" "20020324" "19857950"
## [481] "19850461" "19695860" "19581078" "19569352" "19470530" "19427188"
## [487] "19216066" "19201534" "19174199" "18829288" "18554788" "18513864"
## [493] "18511058" "18346846" "18262405" "18023973" "17993225" "17935966"
## [499] "17874657" "17612322" "17257150" "17253004" "17207844" "17198752"
## [505] "17008085" "16820262" "25868502" "16323764" "16169574" "15737719"
## [511] "15729818" "14700314" "14594087" "12870640" "12758010" "12630485"
## [517] "9713249"records <- EUtilsGet(search_query) # pode levar um tempo...
# colunas para comporem a planilha
pubmed_data <- data.frame('Title' = ArticleTitle(records),
'Abstract' = AbstractText(records),
'ID' = ArticleId(records),
"Tipo" = PublicationType(records),
"Língua" = Language(records),
'Year' = YearArticleDate(records),
"Day" = DayArticleDate(records),
"Month" = MonthArticleDate(records),
"AnoPubmed" = YearPubmed(records),
"MesPubmed" = MonthPubmed(records),
"DiaPubmed" = DayPubmed(records))
pubmed_data$data_pubmed <- paste(pubmed_data$AnoPubmed, pubmed_data$MesPubmed, pubmed_data$DiaPubmed, sep = "-")
pubmed_data$data_artigo <- paste(pubmed_data$Year, pubmed_data$Month, pubmed_data$Day, sep = "-")
pubmed_data <- select(pubmed_data, select = -c("Day", "Month", "MesPubmed", "DiaPubmed"))
View(pubmed_data)
unique(pubmed_data$Tipo)## [1] "Journal Article" "Editorial"
## [3] "Dataset" "Published Erratum"
## [5] "Case Reports" "English Abstract"
## [7] "Comparative Study" "Review"
## [9] "Clinical Trial, Phase III" "Evaluation Study"unique(pubmed_data$Língua)## [1] "eng" "chi"head(pubmed_data, n = 1)## Title
## 1 Are UK E-waste recycling facilities a source of environmental contamination and occupational exposure to brominated flame retardants?
## Abstract
## 1 Investigations into the impacts of regulated electrical and electronic waste (e-waste) recycling activities on urban environments in Europe remain rather scarce. In this study, dust samples taken both inside and outside of five UK e-waste recycling facilities were analysed for concentrations of polybrominated diphenyl ethers (PBDEs), novel brominated flame retardants (NBFRs), and hexabromocyclododecane (HBCDD). Average concentrations of ∑BFRs in dust inside and outside UK e-waste recycling facilities were 12,000 ng/g and 180 ng/g, with median concentrations of 7500 ng/g and 85 ng/g, respectively. BDE-209 and decabromodiphenyl ethane (DBDPE) were the most abundant BFRs in both indoor and kerb dust, making a combined contribution to ∑BFRs of ~90 % on average. While four out of the five studied e-waste facilities showed a lack of significant impact on BFR contamination in surrounding environment, one of the studied e-waste recycling facilities was identified as a likely source of BFR contamination to UK urban environments, with industrial activities as another potential source of NBFRs. Occupational exposure of UK e-waste recycling workers to BFRs via dust ingestion was generally lower than that estimated for e-waste recyclers from other countries, but was comparable to BFR exposure via dust ingestion of UK office workers. Our estimates suggested that health burdens posed by dust ingestion of BFRs were minimal for UK e-waste recycling workers.
## ID Tipo Língua Year AnoPubmed data_pubmed data_artigo
## 1 37442475 Journal Article eng 2023 2023 2023-7-14 2023-7-12length(pubmed_data$ID)## [1] 517# write.csv(pubmed_data, 'weee.csv')