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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
1 24-32 Disease denotes COVID-19 MESH:C000657245
3 405-413 Disease denotes COVID-19 MESH:C000657245
9 212-229 Species denotes novel coronavirus Tax:2697049
10 285-307 Species denotes 2019 novel coronavirus Tax:2697049
11 309-318 Species denotes 2019-nCoV Tax:2697049
12 127-136 Disease denotes pneumonia MESH:D011014
13 344-352 Disease denotes COVID-19 MESH:C000657245
15 879-887 Disease denotes COVID-19 MESH:C000657245
17 1037-1045 Disease denotes COVID-19 MESH:C000657245
20 1431-1440 Disease denotes mortality MESH:D003643
21 1507-1513 Disease denotes deaths MESH:D003643
23 1822-1828 Disease denotes deaths MESH:D003643
25 2014-2020 Disease denotes Deaths MESH:D003643
27 2401-2409 Species denotes patients Tax:9606
39 2762-2765 Species denotes men Tax:9606
40 2774-2779 Species denotes women Tax:9606
41 2803-2806 Species denotes men Tax:9606
42 2884-2889 Species denotes women Tax:9606
43 3009-3017 Species denotes patients Tax:9606
44 3040-3045 Species denotes women Tax:9606
45 2700-2709 Disease denotes mortality MESH:D003643
46 3000-3008 Disease denotes infected MESH:D007239
47 3084-3092 Disease denotes COVID-19 MESH:C000657245
48 3123-3128 Disease denotes death MESH:D003643
49 3470-3479 Disease denotes infection MESH:D007239
54 3915-3923 Species denotes patients Tax:9606
55 4063-4071 Species denotes patients Tax:9606
56 4221-4229 Species denotes patients Tax:9606
57 3736-3744 Disease denotes COVID-19 MESH:C000657245
63 4787-4796 Species denotes 2019-nCoV Tax:2697049
64 4901-4910 Species denotes 2019-nCoV Tax:2697049
65 4733-4742 Disease denotes mortality MESH:D003643
66 4753-4761 Disease denotes COVID-19 MESH:C000657245
67 4881-4890 Disease denotes mortality MESH:D003643
69 5571-5579 Disease denotes COVID-19 MESH:C000657245
76 6454-6467 Species denotes Coronaviridae Tax:11118
77 6388-6421 Disease denotes severe acute respiratory syndrome MESH:D045169
78 6530-6563 Disease denotes severe acute respiratory syndrome MESH:D045169
79 7046-7054 Disease denotes COVID-19 MESH:C000657245
80 7237-7245 Disease denotes COVID-19 MESH:C000657245
81 7366-7374 Disease denotes COVID-19 MESH:C000657245
83 5107-5116 Disease denotes mortality MESH:D003643
87 7985-7993 Species denotes patients Tax:9606
88 7484-7492 Disease denotes COVID-19 MESH:C000657245
89 7601-7610 Disease denotes infection MESH:D007239

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 690-694 Body_part denotes sole http://purl.org/sig/ont/fma/fma25000
T2 3207-3211 Body_part denotes hand http://purl.org/sig/ont/fma/fma9712
T3 4159-4164 Body_part denotes ducts http://purl.org/sig/ont/fma/fma71493
T4 4370-4374 Body_part denotes face http://purl.org/sig/ont/fma/fma24728

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 3207-3211 Body_part denotes hand http://purl.obolibrary.org/obo/UBERON_0002398
T2 4370-4374 Body_part denotes face http://purl.obolibrary.org/obo/UBERON_0001456

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 24-32 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T2 127-136 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T3 344-352 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T4 405-413 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T5 879-887 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T6 1037-1045 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 3084-3092 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 3470-3479 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T9 3736-3744 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T10 4554-4564 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T11 4753-4761 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T12 5571-5579 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T13 6388-6421 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T14 6530-6563 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T15 7046-7054 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T16 7237-7245 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T17 7484-7492 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T18 7601-7610 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T19 8012-8015 Disease denotes Drs http://purl.obolibrary.org/obo/MONDO_0024265

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 210-211 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T2 479-482 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T3 649-654 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T4 729-731 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T5 750-762 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T6 772-773 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T7 1412-1415 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T8 1545-1546 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T9 2025-2026 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T10 2104-2105 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T11 2141-2147 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tested
T12 2206-2211 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tests
T13 2342-2343 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T14 2595-2605 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing is
T15 3099-3100 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T16 3554-3555 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T17 3825-3837 http://purl.obolibrary.org/obo/OBI_0000245 denotes organization
T18 3854-3861 http://purl.obolibrary.org/obo/OBI_0000968 denotes devices
T19 4000-4001 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T20 4159-4164 http://purl.obolibrary.org/obo/UBERON_0000025 denotes ducts
T21 4159-4164 http://purl.obolibrary.org/obo/UBERON_0000058 denotes ducts
T22 4188-4193 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T23 4370-4374 http://purl.obolibrary.org/obo/UBERON_0001456 denotes face
T24 4614-4619 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T25 5199-5200 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T26 5396-5401 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T27 5581-5582 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T28 5861-5866 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T29 5926-5933 http://purl.obolibrary.org/obo/BFO_0000030 denotes objects
T30 5953-5956 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T31 6264-6269 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T32 6432-6433 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T33 6434-6439 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T34 6620-6621 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T35 6637-6642 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T36 6718-6724 http://purl.obolibrary.org/obo/CLO_0001658 denotes active
T37 6907-6908 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T38 8012-8015 http://purl.obolibrary.org/obo/CLO_0002819 denotes Drs
T39 8016-8019 http://purl.obolibrary.org/obo/CLO_0002742 denotes Del

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 3454-3462 Chemical denotes carriers http://purl.obolibrary.org/obo/CHEBI_78059
T2 6622-6629 Chemical denotes carrier http://purl.obolibrary.org/obo/CHEBI_78059

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T1 127-136 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-33 Sentence denotes The Italian Outbreak of COVID-19:
T2 34-72 Sentence denotes Conditions, Contributors, and Concerns
T3 74-359 Sentence denotes In late December 2019, several cases of interstitial pneumonia of unknown origin were reported in Wuhan, China, and on January 9, 2020, a novel coronavirus was identified as the causative infective agent, named 2019 novel coronavirus (2019-nCoV); the disease was termed COVID-19 .1 , 2
T4 360-452 Sentence denotes Figure Potential reasons for the outbreak of COVID-19 in Italy and its regional differences.
T5 453-719 Sentence denotes Since then, the contagion has spread exponentially through China, South Korea, and many other countries, and the presence of asymptomatic cases together with the ease of modern travel allowed the virus to reach every continent, with the sole exception of Antarctica.
T6 720-792 Sentence denotes On March 11, the World Health Organization declared a state of pandemic.
T7 793-974 Sentence denotes Herein, we discuss possible factors that may contribute to the differences in Italy’s COVID-19 outbreak compared with other countries and the differences among regions within Italy.
T8 975-1089 Sentence denotes Italy was one of the first European countries that dealt with COVID-19, with first cases detected in January 2020.
T9 1090-1274 Sentence denotes In mid-February, cases of community spread were detected in the region of Lombardy, and the outbreak soon involved all of northern Italy, eventually appearing elsewhere in the country.
T10 1275-1359 Sentence denotes At first, the fatality rates in Italy and China were comparable, approximating 2.3%.
T11 1360-1541 Sentence denotes However, over the past weeks, the Italian situation has worsened, with mortality rates reaching as high as 8% to 12%, and with the total number of deaths surpassing those in China.3
T12 1542-1725 Sentence denotes As a consequence, and similar to Chinese emergency policy, restrictive measures were then adopted in Italy, including general lockdown, measures shown to check the contagion in Wuhan.
T13 1726-1974 Sentence denotes The grave situation in Italy raises 2 salient questions: “Why have there been so many cases and deaths?” and “Why are there these differences among regions?” There are no answers to these questions, but we offer the following speculations (Figure).
T14 1976-2021 Sentence denotes Why Have There Been So Many Cases and Deaths?
T15 2022-2024 Sentence denotes 1.
T16 2025-2359 Sentence denotes A first point of discussion is that in other countries, including South Korea, a wider sample of the population was tested, whereas in Italy and especially in the north, diagnostic tests were mainly reserved for symptomatic cases seen in the emergency department or symptomatic cases at home with recent contact with a confirmed case.
T17 2360-2523 Sentence denotes Therefore, the actual number of positive patients could be even 10-fold higher than the estimated number, thus considerably reducing the percentage of fatal cases.
T18 2524-2611 Sentence denotes However, this assumption cannot be confirmed until extended population testing is done.
T19 2612-2614 Sentence denotes 2.
T20 2615-2685 Sentence denotes Epidemiological and demographic differences should also be considered.
T21 2686-2780 Sentence denotes For instance, mortality rates have been higher in the elderly as well as in men than in women.
T22 2781-2890 Sentence denotes This could be because men are more frequent smokers and have more cardiovascular comorbidities than do women.
T23 2891-2978 Sentence denotes In both China and South Korea, life expectancy is lower than that in Western countries.
T24 2979-3129 Sentence denotes In South Korea, most infected patients are young, nonsmoking women, who, generally and in the absence of COVID-19, have a lower overall risk of death.
T25 3130-3305 Sentence denotes This argument may partially explain the differences between Italy on the one hand and South Korea or China, on the other, but not with the rest of Europe or the United States.
T26 3306-3480 Sentence denotes An additional hypothesis is that Italian grandparents spend more time with their young grandchildren, the latter possibly representing asymptomatic carriers of the infection.
T27 3481-3550 Sentence denotes Further epidemiological research is needed with regard to this issue.
T28 3551-3553 Sentence denotes 3.
T29 3554-3752 Sentence denotes A relevant issue is that the Italian health system, which experienced financial cuts in the past years, was poorly positioned and resourced to deal with the emergency imposed by the COVID-19 crisis.
T30 3753-3924 Sentence denotes The lack of an appropriate number of intensive care units, managed care organization, and lifesaving devices such as ventilators may have compromised the care of patients.
T31 3925-4230 Sentence denotes The paucity of personal protective equipment throughout the country caused a spread of the contagion among medical staff and consequently patients.4 Furthermore, the lack of renovation in health care facilities with inappropriate air ducts could have facilitated virus circulation in compromised patients.
T32 4231-4233 Sentence denotes 4.
T33 4234-4396 Sentence denotes The Chinese “disaster response plan” allowed the construction of 2 dedicated hospitals in only 10 days, whereas Italy was unprepared to face emergency conditions.
T34 4397-4399 Sentence denotes 5.
T35 4400-4604 Sentence denotes The Chinese experience emphasized not just the quarantine of asymptomatic and mildly symptomatic cases but also follow-up of possible contacts and of the infectious status so as to attenuate viral spread.
T36 4605-4762 Sentence denotes Finally, virus mutation and the appearance of more virulent genotypes may contribute to geographic differences in morbidity and mortality caused by COVID-19.
T37 4763-4912 Sentence denotes Different genotypes for 2019-nCoV exist, and it is thus intriguing whether genotypes determine the infectivity of and mortality caused by 2019-nCoV.5
T38 4914-4960 Sentence denotes Why Are There These Differences Among Regions?
T39 4961-5119 Sentence denotes Substantial differences occur throughout Italy, with the north of the country, predominantly Lombardy, exhibiting the highest rates of spread and mortality.1.
T40 5120-5412 Sentence denotes One possible explanation is that the above-mentioned Italian regions represent a central driver of the Italian economy, being the headquarters of several major industries; individuals from other regions and other countries who are involved with such industries may spread the virus elsewhere.
T41 5413-5580 Sentence denotes Nevertheless, other Italian cities that are overcrowded because of business and tourism, such as Rome, have not experienced the same prevalence and spread of COVID-19.
T42 5581-5724 Sentence denotes A supposition could be that the northern experience led to severe restrictive measures throughout the country, thereby containing the outbreak.
T43 5725-5727 Sentence denotes 2.
T44 5728-5818 Sentence denotes Climate conditions may also be relevant to the differences reported among Italian regions.
T45 5819-6034 Sentence denotes Higher temperature and humidity may block virus diffusion and reduce its persistence in the air and on the objects.6 This explanation has been given to the unequal distribution of the contagion among the continents.
T46 6035-6174 Sentence denotes In Italy, however, differences in climate among regions are less than what exists between Italy and other parts of the world such as China.
T47 6175-6177 Sentence denotes 3.
T48 6178-6280 Sentence denotes More recently, there is increasing attention on the possible role of air pollution in virus diffusion.
T49 6281-6564 Sentence denotes The correlation between the air pollution index and increased fatality was previously hypothesized for the severe acute respiratory syndrome caused by a virus member of the Coronaviridae family; subsequent evidence supported this hypothesis for the severe acute respiratory syndrome.
T50 6565-6754 Sentence denotes In particular, atmospheric particulate seems to act as a carrier of the virus, facilitating its diffusion and dissemination and allowing its survival in active form for hours and even days.
T51 6755-6906 Sentence denotes Indeed, air pollution imposes an increased vulnerability of the population to respiratory syndromes, even in the absence of microbial causative agents.
T52 6907-7139 Sentence denotes A recently published position paper of the Italian Society of Environmental Medicine in collaboration with 2 Italian universities compared COVID-19 case distribution (updated to March 3) and air pollution levels in the past 20 days.
T53 7140-7376 Sentence denotes Interestingly, northern Italy had both the most polluted area and the highest number of cases of COVID-19, thereby supporting the possibility that the degree of air pollution may contribute to regional differences in cases of COVID-19.7
T54 7377-7511 Sentence denotes In sum, there is no single explanation that accounts for the severity and catastrophic consequences of the COVID-19 outbreak in Italy.
T55 7512-7660 Sentence denotes Intense and sustained effort is needed to optimize strategies that prevent the spread of infection and to devise targeted therapies for the disease.
T56 7661-7793 Sentence denotes In the meantime, severe restrictive measures and strict social distancing are crucial to contain the contagion among the population.
T57 7794-7994 Sentence denotes Hospitals should be provided with appropriate personal protective equipment, ventilators, and further intensive care unit equipment to preserve the medical staff and to optimize care for all patients.
T58 7996-8011 Sentence denotes Acknowledgments
T59 8012-8090 Sentence denotes Drs Del Buono and Iannaccone contributed equally as first author to this work.
T60 8091-8121 Sentence denotes Potential Competing Interests:
T61 8122-8164 Sentence denotes The authors report no competing interests.

LitCovid-PMC-OGER-BB

Id Subject Object Predicate Lexical cue
T1 24-32 SP_7 denotes COVID-19
T2 114-126 UBERON:0005169 denotes interstitial
T3 218-229 NCBITaxon:11118 denotes coronavirus
T4 296-307 NCBITaxon:11118 denotes coronavirus
T5 309-318 SP_7 denotes 2019-nCoV
T6 344-352 SP_7 denotes COVID-19
T7 405-413 SP_7 denotes COVID-19
T9 649-654 NCBITaxon:10239 denotes virus
T10 879-887 SP_7 denotes COVID-19
T11 1037-1045 SP_7 denotes COVID-19
T12 1507-1513 GO:0016265 denotes deaths
T13 1822-1828 GO:0016265 denotes deaths
T14 2014-2020 GO:0016265 denotes Deaths
T15 2847-2861 UBERON:0004535 denotes cardiovascular
T16 2922-2926 UBERON:0000104 denotes life
T17 3084-3092 SP_7 denotes COVID-19
T18 3123-3128 GO:0016265 denotes death
T19 3736-3744 SP_7 denotes COVID-19
T20 3790-3799 CL:0002211 denotes intensive
T21 3800-3804 CL:0002486;UBERON:0003053 denotes care
T22 4159-4164 UBERON:0000058 denotes ducts
T23 4188-4193 NCBITaxon:10239 denotes virus
T24 4591-4596 NCBITaxon:10239 denotes viral
T36 4614-4619 NCBITaxon:10239 denotes virus
T37 4753-4761 SP_7 denotes COVID-19
T38 4787-4796 SP_7 denotes 2019-nCoV
T39 4901-4910 SP_7 denotes 2019-nCoV
T40 5292-5303 NCBITaxon:1 denotes individuals
T41 5396-5401 NCBITaxon:10239 denotes virus
T42 5571-5579 SP_7 denotes COVID-19
T43 5861-5866 NCBITaxon:10239 denotes virus
T44 6264-6269 NCBITaxon:10239 denotes virus
T45 6401-6412 UBERON:0001004 denotes respiratory
T46 6434-6439 NCBITaxon:10239 denotes virus
T47 6454-6467 NCBITaxon:11118 denotes Coronaviridae
T48 6543-6554 UBERON:0001004 denotes respiratory
T49 6637-6642 NCBITaxon:10239 denotes virus
T50 6833-6844 UBERON:0001004 denotes respiratory
T51 7046-7054 SP_7 denotes COVID-19
T52 7237-7245 SP_7 denotes COVID-19
T53 7366-7374 SP_7 denotes COVID-19
T68 7484-7492 SP_7 denotes COVID-19
T2724 24-32 SP_7 denotes COVID-19
T795 114-126 UBERON:0005169 denotes interstitial
T64484 218-229 NCBITaxon:11118 denotes coronavirus
T52796 296-307 NCBITaxon:11118 denotes coronavirus
T15463 309-318 SP_7 denotes 2019-nCoV
T56870 344-352 SP_7 denotes COVID-19
T94558 405-413 SP_7 denotes COVID-19
T18265 7896-7905 CL:0002211 denotes intensive
T5023 7906-7910 CL:0002486;UBERON:0003053 denotes care
T25 581-595 UBERON:0004535 denotes mptomatic case
T26 654-658 UBERON:0000104 denotes to
T27 816-824 SP_7 denotes ible fac
T28 855-860 GO:0016265 denotes diff
T29 1470-1478 SP_7 denotes to 12%,
T30 1524-1533 CL:0002211 denotes those in
T31 1534-1540 CL:0002486;UBERON:0003053 denotes China.
T32 1893-1896 UBERON:0001232 denotes no
T33 1897-1902 UBERON:0000058 denotes answe
T34 1926-1931 NCBITaxon:10239 denotes ut we
T35 2324-2329 NCBITaxon:10239 denotes cent
T18026 2347-2352 NCBITaxon:10239 denotes firme
T61192 2485-2493 SP_7 denotes educing
T50245 2519-2528 SP_7 denotes ses. Howe
T76681 2633-2642 SP_7 denotes d demogra
T24124 3026-3037 NCBITaxon:1 denotes g, nonsmoki
T35277 3130-3135 NCBITaxon:10239 denotes This
T8079 3307-3315 SP_7 denotes n additi
T99598 3598-3603 NCBITaxon:10239 denotes syste
T83796 3997-4002 NCBITaxon:10239 denotes ed a
T57495 4134-4144 UBERON:0001004 denotes s with ina
T34966 4166-4171 NCBITaxon:10239 denotes ould
T22575 4186-4199 NCBITaxon:11118 denotes d virus circu
T55251 4277-4287 UBERON:0001004 denotes d the cons
T37885 4371-4376 NCBITaxon:10239 denotes ace e
T89113 4569-4579 UBERON:0001004 denotes us so as t
T34908 4785-4793 SP_7 denotes r 2019-n
T32424 4977-4985 SP_7 denotes erences
T37206 5106-5114 SP_7 denotes mortali
T54 5292-5303 NCBITaxon:1 denotes individuals
T55 5396-5401 NCBITaxon:10239 denotes virus
T56 5571-5579 SP_7 denotes COVID-19
T57 5861-5866 NCBITaxon:10239 denotes virus
T58 6264-6269 NCBITaxon:10239 denotes virus
T59 6401-6412 UBERON:0001004 denotes respiratory
T60 6434-6439 NCBITaxon:10239 denotes virus
T61 6454-6467 NCBITaxon:11118 denotes Coronaviridae
T62 6543-6554 UBERON:0001004 denotes respiratory
T63 6637-6642 NCBITaxon:10239 denotes virus
T64 6833-6844 UBERON:0001004 denotes respiratory
T65 7046-7054 SP_7 denotes COVID-19
T66 7237-7245 SP_7 denotes COVID-19
T67 7366-7374 SP_7 denotes COVID-19
T20546 7484-7492 SP_7 denotes COVID-19