Cellular and serological markers of disease activity in Indian patients with HIV/AIDS View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

Shobha Sehgal , U. Datta , S. Mujtaba , A. Sood , V. K. Vinayak

ABSTRACT

There has been an exponential rise of HIV positive patients as observed at the surveillance center of Nehru Hospital. Most patients are poor and cannot afford repeated viral load assays. Therefore, there is a need to identify cost effective and reliable surrogate markers of disease activity. In the present study absolute number of CD4 cells, β2 micro-globulin, circulating necleosomes were studied in 30 patients of AIDS, 30 seropositives and 30 healthy controls. In addition viral load, P-24 assay, and TNFR-II assays were done in seropositive and AIDS patients. The mean CD4 cells in patients with AIDS were 69.66 ± 68.25 mm3 while in seropositives values was 370 ± 201.29 mm3 The mean CD4 cells in healthy controls were however 690 ± 198 mm3. The differences in all the groups were highly significant (p 3 this figure is also higher than that observed in the west. P-24 assay failed to delineate between seropositives and patients with AIDS. Although, 132. microglobulin levels were significantly higher in AIDS than in seropositives and higher in seropositives than in controls yet with the best possible cut off, it had a sensitivity of only 70% in delineating the two conditions. The correlation between CD4 cells and viral load was more significant when the CD4 cells were below 200 mm3. Five out of 30 patients with a CD4 of 300−600 mm3 had a viral load of over 1 × 105 cop/ml. The difference in TNF R-II levels between seropositives and AIDS was however more impressive. With a cut off of 550 pg/ml it had a sensitivity of 95% in delineating HIV from AIDS. It is concluded that a combination of absolute number of CD4 cells and TNF R-II assay along with clinical evaluation may be used to monitor therapy in resource poor countries where frequent viral load assay is unaffordable. More... »

PAGES

107-114

Book

TITLE

Advanced Flow Cytometry: Applications in Biological Research

ISBN

978-90-481-6368-7
978-94-017-0623-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-94-017-0623-0_16

DOI

http://dx.doi.org/10.1007/978-94-017-0623-0_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045388947


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sehgal", 
        "givenName": "Shobha", 
        "id": "sg:person.01217163165.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217163165.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Datta", 
        "givenName": "U.", 
        "id": "sg:person.01261435265.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261435265.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mujtaba", 
        "givenName": "S.", 
        "id": "sg:person.0610736254.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610736254.12"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sood", 
        "givenName": "A.", 
        "id": "sg:person.01030362046.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01030362046.97"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vinayak", 
        "givenName": "V. K.", 
        "id": "sg:person.01243515152.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01243515152.69"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/s0167-5699(98)01322-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003474356"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm199001183220305", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009388900"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/archinte.1990.00390130083011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013101323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0166-0934(88)90097-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016720188"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0166-0934(88)90097-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016720188"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(86)92673-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023442587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(86)92673-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023442587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm198912143212401", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023546723"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002030-199607000-00009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025042438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002030-199607000-00009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025042438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0090-1229(89)90188-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027333710"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0140-6736(91)91166-r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039470542"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0140-6736(91)91166-r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039470542"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002030-199813000-00004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041417912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002030-199813000-00004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041417912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm198710293171804", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050326613"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1365-2249.1998.00736.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052922780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.6189183", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062635034"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.6200935", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062635710"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1079506409", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2003", 
    "datePublishedReg": "2003-01-01", 
    "description": "There has been an exponential rise of HIV positive patients as observed at the surveillance center of Nehru Hospital. Most patients are poor and cannot afford repeated viral load assays. Therefore, there is a need to identify cost effective and reliable surrogate markers of disease activity. In the present study absolute number of CD4 cells, \u03b22 micro-globulin, circulating necleosomes were studied in 30 patients of AIDS, 30 seropositives and 30 healthy controls. In addition viral load, P-24 assay, and TNFR-II assays were done in seropositive and AIDS patients. The mean CD4 cells in patients with AIDS were 69.66 \u00b1 68.25 mm3 while in seropositives values was 370 \u00b1 201.29 mm3 The mean CD4 cells in healthy controls were however 690 \u00b1 198 mm3. The differences in all the groups were highly significant (p 3 this figure is also higher than that observed in the west. P-24 assay failed to delineate between seropositives and patients with AIDS. Although, 132. microglobulin levels were significantly higher in AIDS than in seropositives and higher in seropositives than in controls yet with the best possible cut off, it had a sensitivity of only 70% in delineating the two conditions. The correlation between CD4 cells and viral load was more significant when the CD4 cells were below 200 mm3. Five out of 30 patients with a CD4 of 300\u2212600 mm3 had a viral load of over 1 \u00d7 105 cop/ml. The difference in TNF R-II levels between seropositives and AIDS was however more impressive. With a cut off of 550 pg/ml it had a sensitivity of 95% in delineating HIV from AIDS. It is concluded that a combination of absolute number of CD4 cells and TNF R-II assay along with clinical evaluation may be used to monitor therapy in resource poor countries where frequent viral load assay is unaffordable.", 
    "editor": [
      {
        "familyName": "Sobti", 
        "givenName": "R. C.", 
        "type": "Person"
      }, 
      {
        "familyName": "Krishan", 
        "givenName": "Awtar", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-94-017-0623-0_16", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-90-481-6368-7", 
        "978-94-017-0623-0"
      ], 
      "name": "Advanced Flow Cytometry: Applications in Biological Research", 
      "type": "Book"
    }, 
    "name": "Cellular and serological markers of disease activity in Indian patients with HIV/AIDS", 
    "pagination": "107-114", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-94-017-0623-0_16"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d83503306efaea32836fab94d6361bd4b199b722ff13954b647d760fb26961f7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1045388947"
        ]
      }
    ], 
    "publisher": {
      "location": "Dordrecht", 
      "name": "Springer Netherlands", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-94-017-0623-0_16", 
      "https://app.dimensions.ai/details/publication/pub.1045388947"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T12:34", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8663_00000271.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-94-017-0623-0_16"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-0623-0_16'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-0623-0_16'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-0623-0_16'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-0623-0_16'


 

This table displays all metadata directly associated to this object as RDF triples.

149 TRIPLES      23 PREDICATES      42 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-94-017-0623-0_16 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N431d574fd19b4e5d9e9e4f0d43d27b23
4 schema:citation https://app.dimensions.ai/details/publication/pub.1079506409
5 https://doi.org/10.1001/archinte.1990.00390130083011
6 https://doi.org/10.1016/0090-1229(89)90188-8
7 https://doi.org/10.1016/0140-6736(91)91166-r
8 https://doi.org/10.1016/0166-0934(88)90097-3
9 https://doi.org/10.1016/s0140-6736(86)92673-5
10 https://doi.org/10.1016/s0167-5699(98)01322-x
11 https://doi.org/10.1046/j.1365-2249.1998.00736.x
12 https://doi.org/10.1056/nejm198710293171804
13 https://doi.org/10.1056/nejm198912143212401
14 https://doi.org/10.1056/nejm199001183220305
15 https://doi.org/10.1097/00002030-199607000-00009
16 https://doi.org/10.1097/00002030-199813000-00004
17 https://doi.org/10.1126/science.6189183
18 https://doi.org/10.1126/science.6200935
19 schema:datePublished 2003
20 schema:datePublishedReg 2003-01-01
21 schema:description There has been an exponential rise of HIV positive patients as observed at the surveillance center of Nehru Hospital. Most patients are poor and cannot afford repeated viral load assays. Therefore, there is a need to identify cost effective and reliable surrogate markers of disease activity. In the present study absolute number of CD4 cells, β2 micro-globulin, circulating necleosomes were studied in 30 patients of AIDS, 30 seropositives and 30 healthy controls. In addition viral load, P-24 assay, and TNFR-II assays were done in seropositive and AIDS patients. The mean CD4 cells in patients with AIDS were 69.66 ± 68.25 mm3 while in seropositives values was 370 ± 201.29 mm3 The mean CD4 cells in healthy controls were however 690 ± 198 mm3. The differences in all the groups were highly significant (p 3 this figure is also higher than that observed in the west. P-24 assay failed to delineate between seropositives and patients with AIDS. Although, 132. microglobulin levels were significantly higher in AIDS than in seropositives and higher in seropositives than in controls yet with the best possible cut off, it had a sensitivity of only 70% in delineating the two conditions. The correlation between CD4 cells and viral load was more significant when the CD4 cells were below 200 mm3. Five out of 30 patients with a CD4 of 300−600 mm3 had a viral load of over 1 × 105 cop/ml. The difference in TNF R-II levels between seropositives and AIDS was however more impressive. With a cut off of 550 pg/ml it had a sensitivity of 95% in delineating HIV from AIDS. It is concluded that a combination of absolute number of CD4 cells and TNF R-II assay along with clinical evaluation may be used to monitor therapy in resource poor countries where frequent viral load assay is unaffordable.
22 schema:editor N65b40189aee249c9acb779e7f067fca4
23 schema:genre chapter
24 schema:inLanguage en
25 schema:isAccessibleForFree false
26 schema:isPartOf N5398e873b30f4a6c8e46e774aaedbd50
27 schema:name Cellular and serological markers of disease activity in Indian patients with HIV/AIDS
28 schema:pagination 107-114
29 schema:productId N2ee63000f66241b3afaba5adfc4a05b6
30 N6398a9f5384b45bba82491aa6dff83f3
31 Na60e2f6c10274730ab43f7ee8c73479c
32 schema:publisher N422947ebf24c49768ec27316ec247b8a
33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045388947
34 https://doi.org/10.1007/978-94-017-0623-0_16
35 schema:sdDatePublished 2019-04-15T12:34
36 schema:sdLicense https://scigraph.springernature.com/explorer/license/
37 schema:sdPublisher Ne40b82f2cd164eb6bcd5b3c174cae9fd
38 schema:url http://link.springer.com/10.1007/978-94-017-0623-0_16
39 sgo:license sg:explorer/license/
40 sgo:sdDataset chapters
41 rdf:type schema:Chapter
42 N09c5059d959747eab09a5f162757c6f5 schema:name Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India
43 rdf:type schema:Organization
44 N1cd605b4915443e399ca4fef7aca2b97 schema:name Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India
45 rdf:type schema:Organization
46 N2ee63000f66241b3afaba5adfc4a05b6 schema:name doi
47 schema:value 10.1007/978-94-017-0623-0_16
48 rdf:type schema:PropertyValue
49 N422947ebf24c49768ec27316ec247b8a schema:location Dordrecht
50 schema:name Springer Netherlands
51 rdf:type schema:Organisation
52 N431d574fd19b4e5d9e9e4f0d43d27b23 rdf:first sg:person.01217163165.38
53 rdf:rest Nd9507e0f10ba44a3a5235ef5b9c58a92
54 N48677ae944ba4531996a6dac30950cea schema:name Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India
55 rdf:type schema:Organization
56 N5398e873b30f4a6c8e46e774aaedbd50 schema:isbn 978-90-481-6368-7
57 978-94-017-0623-0
58 schema:name Advanced Flow Cytometry: Applications in Biological Research
59 rdf:type schema:Book
60 N6398a9f5384b45bba82491aa6dff83f3 schema:name readcube_id
61 schema:value d83503306efaea32836fab94d6361bd4b199b722ff13954b647d760fb26961f7
62 rdf:type schema:PropertyValue
63 N65b40189aee249c9acb779e7f067fca4 rdf:first N96339b9445de495b8c8d35493d7d1ae8
64 rdf:rest Nd03143a571d94e828be6d14bb4e86a6a
65 N91f673e417cf453cb3e48b26c0068292 schema:name Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India
66 rdf:type schema:Organization
67 N96339b9445de495b8c8d35493d7d1ae8 schema:familyName Sobti
68 schema:givenName R. C.
69 rdf:type schema:Person
70 Na60e2f6c10274730ab43f7ee8c73479c schema:name dimensions_id
71 schema:value pub.1045388947
72 rdf:type schema:PropertyValue
73 Nb4a73c5fb58343f98c8bd12d2dba838c rdf:first sg:person.0610736254.12
74 rdf:rest Nbec1a4fc2b5d438abf8267d330444a4f
75 Nbec1a4fc2b5d438abf8267d330444a4f rdf:first sg:person.01030362046.97
76 rdf:rest Nef1ce89bff244d4c9aceae24164ec26a
77 Nd03143a571d94e828be6d14bb4e86a6a rdf:first Nfa4de9dd28a1434abba0b5d27f2d4bf8
78 rdf:rest rdf:nil
79 Nd9507e0f10ba44a3a5235ef5b9c58a92 rdf:first sg:person.01261435265.79
80 rdf:rest Nb4a73c5fb58343f98c8bd12d2dba838c
81 Ne40b82f2cd164eb6bcd5b3c174cae9fd schema:name Springer Nature - SN SciGraph project
82 rdf:type schema:Organization
83 Nef1ce89bff244d4c9aceae24164ec26a rdf:first sg:person.01243515152.69
84 rdf:rest rdf:nil
85 Nfa4de9dd28a1434abba0b5d27f2d4bf8 schema:familyName Krishan
86 schema:givenName Awtar
87 rdf:type schema:Person
88 Nfc800c1fa06544f88bf99096f9d7d9b2 schema:name Chandigarh and Department of Biotechnology, Departments of Immunopathology & Internal Medicine PGIMER, New Delhi, India
89 rdf:type schema:Organization
90 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
91 schema:name Medical and Health Sciences
92 rdf:type schema:DefinedTerm
93 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
94 schema:name Clinical Sciences
95 rdf:type schema:DefinedTerm
96 sg:person.01030362046.97 schema:affiliation N91f673e417cf453cb3e48b26c0068292
97 schema:familyName Sood
98 schema:givenName A.
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01030362046.97
100 rdf:type schema:Person
101 sg:person.01217163165.38 schema:affiliation N09c5059d959747eab09a5f162757c6f5
102 schema:familyName Sehgal
103 schema:givenName Shobha
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217163165.38
105 rdf:type schema:Person
106 sg:person.01243515152.69 schema:affiliation N48677ae944ba4531996a6dac30950cea
107 schema:familyName Vinayak
108 schema:givenName V. K.
109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01243515152.69
110 rdf:type schema:Person
111 sg:person.01261435265.79 schema:affiliation Nfc800c1fa06544f88bf99096f9d7d9b2
112 schema:familyName Datta
113 schema:givenName U.
114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261435265.79
115 rdf:type schema:Person
116 sg:person.0610736254.12 schema:affiliation N1cd605b4915443e399ca4fef7aca2b97
117 schema:familyName Mujtaba
118 schema:givenName S.
119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610736254.12
120 rdf:type schema:Person
121 https://app.dimensions.ai/details/publication/pub.1079506409 schema:CreativeWork
122 https://doi.org/10.1001/archinte.1990.00390130083011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013101323
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/0090-1229(89)90188-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027333710
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/0140-6736(91)91166-r schema:sameAs https://app.dimensions.ai/details/publication/pub.1039470542
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/0166-0934(88)90097-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016720188
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/s0140-6736(86)92673-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023442587
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/s0167-5699(98)01322-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1003474356
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1046/j.1365-2249.1998.00736.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1052922780
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1056/nejm198710293171804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050326613
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1056/nejm198912143212401 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023546723
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1056/nejm199001183220305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009388900
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1097/00002030-199607000-00009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025042438
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1097/00002030-199813000-00004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041417912
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1126/science.6189183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062635034
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1126/science.6200935 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062635710
149 rdf:type schema:CreativeWork
 




Preview window. Press ESC to close (or click here)


...