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Journal articles on the topic 'Human Profile'

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Published: 9 March 2023
Last updated: 10 March 2023

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1

MacDonald, R. "Profile: The human league." BMJ 322, no. 7279 (January 20, 2001): 178. http://dx.doi.org/10.1136/bmj.322.7279.178.

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2

Desiderio, D. M., G. H. Fridland, J. T. Francisco, H. Sacks, J. T. Robertson, R. C. Cezayirli, J. Killmar, and C. Lahren. "Opioid peptide profile in human pituitary." Clinical Chemistry 34, no. 6 (June 1, 1988): 1104–7. http://dx.doi.org/10.1093/clinchem/34.6.1104.

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Abstract The comprehensive metabolic profile of endogenous opioid peptides is established here for human pituitary for the first time. Sixteen human pituitaries, obtained postmortem, were analyzed individually by gradient reversed-phase high-performance liquid chromatography together with a radio-receptor assay with [3H]etorphine as ligand. This combination was used to detect opioid receptor activity. The 16 assay profiles were sufficiently consistent for a composite of them to serve as a comparative basis for other studies on the pathophysiology of the human pituitary. To demonstrate one selected comparison, we present data on a distinctively different profile of opioid receptor activity in the pituitary of one patient who died from a drug overdose.
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Karasek-Kędzior, Kinga, and Leszek Porębski. "Serwis społecznościowy jako narzędzie dialogu z wyborcami - profile polskich partii politycznych na Facebooku." Studia Humanistyczne AGH 13, no. 1 (2014): 59. http://dx.doi.org/10.7494/human.2014.13.1.59.

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Patil, Arundhati, and Keerti Deep. "Profile of Children with Human Immunodeficiency Virus Infection: Descriptive Study." Indian Journal of Trauma and Emergency Pediatrics 8, no. 2 (2016): 67–70. http://dx.doi.org/10.21088/ijtep.2348.9987.8216.4.

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5

Tu, Huailu, and Max Costa. "XIAP’s Profile in Human Cancer." Biomolecules 10, no. 11 (October 29, 2020): 1493. http://dx.doi.org/10.3390/biom10111493.

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XIAP, the X-linked inhibitor of apoptosis protein, regulates cell death signaling pathways through binding and inhibiting caspases. Mounting experimental research associated with XIAP has shown it to be a master regulator of cell death not only in apoptosis, but also in autophagy and necroptosis. As a vital decider on cell survival, XIAP is involved in the regulation of cancer initiation, promotion and progression. XIAP up-regulation occurs in many human diseases, resulting in a series of undesired effects such as raising the cellular tolerance to genetic lesions, inflammation and cytotoxicity. Hence, anti-tumor drugs targeting XIAP have become an important focus for cancer therapy research. RNA–XIAP interaction is a focus, which has enriched the general profile of XIAP regulation in human cancer. In this review, the basic functions of XIAP, its regulatory role in cancer, anti-XIAP drugs and recent findings about RNA–XIAP interactions are discussed.
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MCGREGOR, J. M., J. N. W. N. BARKER, M. H. ALLEN, and D. M. MACDONALD. "Antigenic profile of human acrosyringium." British Journal of Dermatology 125, no. 5 (November 1991): 413–18. http://dx.doi.org/10.1111/j.1365-2133.1991.tb14765.x.

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7

Leal, Tereza Cristina A., Nilma C. Leal, and Alzira M. Paiva de Almeida. "RAPD-PCR typing of Yersinia enterocolitica (Enterobacteriaceae) O:3 serotype strains isolated from pigs and humans." Genetics and Molecular Biology 22, no. 3 (September 1999): 315–19. http://dx.doi.org/10.1590/s1415-47571999000300005.

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Sixteen strains of Yersinia enterocolitica serotype O:3, isolated from apparently healthy pigs collected in Rio de Janeiro, and four human strains of serotypes O:4, O:5, O:6 and O:13 were analyzed by RAPD-PCR. The strains were grouped into five genotypic profiles according to the amplification patterns obtained with three random primers. Fifteen of the 16 pig strains had identical amplification patterns, which was named genotypic profile 1. The one different profile was named genotypic profile 2. Genotypic profile 1 was also exhibited by the O:6 human serotype strain. The O:4 and O:13 human serotype strains showed similar amplification profiles with two primers. However, the third primer induced a distinct profile in each strain. Therefore, these two strains were placed into genotypic profile 3 and 4, respectively. Each primer produced a completely different amplification profile in the O:5 human serotype strain; therefore, it was named genotypic profile 5. The presence or absence of plasmids in the strains studied did not affect the amplification results. These results show that genetic variations can exist within a serotype, and strains of different serotypes can exhibit the same amplification profile when compared using other primers.
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8

Fortier, Alyssa Lyn, Jaehee Kim, and Noah A. Rosenberg. "Human-Genetic Ancestry Inference and False Positives in Forensic Familial Searching." G3: Genes|Genomes|Genetics 10, no. 8 (June 25, 2020): 2893–902. http://dx.doi.org/10.1534/g3.120.401473.

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In forensic familial search methods, a query DNA profile is tested against a database to determine if the query profile represents a close relative of a database entrant. One challenge for familial search is that the calculations may require specification of allele frequencies for the unknown population from which the query profile has originated. The choice of allele frequencies affects the rate at which non-relatives are erroneously classified as relatives, and allele-frequency misspecification can substantially inflate false positive rates compared to use of allele frequencies drawn from the same population as the query profile. Here, we use ancestry inference on the query profile to circumvent the high false positive rates that result from highly misspecified allele frequencies. In particular, we perform ancestry inference on the query profile and make use of allele frequencies based on its inferred genetic ancestry. In a test for sibling matches on profiles that represent unrelated individuals, we demonstrate that false positive rates for familial search with use of ancestry inference to specify the allele frequencies are similar to those seen when allele frequencies align with the population of origin of a profile. Because ancestry inference is possible to perform on query profiles, the extreme allele-frequency misspecifications that produce the highest false positive rates can be avoided. We discuss the implications of the results in the context of concerns about the forensic use of familial searching.
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9

LINDQVIST, N., S. HEINIKAINEN, A. SIITONEN, and S. PELKONEN. "Molecular characterization of Salmonella enterica subsp. enterica serovar Typhimurium DT1 isolates." Epidemiology and Infection 132, no. 2 (February 26, 2004): 263–72. http://dx.doi.org/10.1017/s0950268803001614.

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Salmonella Typhimurium DT1 is endemic to Finland and has caused human outbreaks since the 1960s. Domestic DT1 isolates (n=235) from 1972 to 1999 from human cases, animals and other sources, as well as foreign DT1 isolates from human cases (n=20) were analysed by molecular methods. Pulsed-field gel electrophoresis (PFGE) yielded 38 XbaI profiles. Of these, XbaI profile 10 was seen in 49% (125/255) of the isolates. Twelve IS200 profiles were obtained; the most common IS200 profile D was seen in 64% (33/52) of the isolates. Two clusters were formed by compilation of the XbaI–, BlnI– and SpeI–PFGE and IS200 profiles and possession of the serovar-specific virulence plasmid. The major cluster contained eight IS200 profiles, including IS200 profile D and XbaI profile 10, and had no virulence plasmid, and can be regarded as typical of the endemic Typhimurium DT1 infection.
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10

Tomes, Nigel. "Human capital and the time-profile of human fertility." Economics Letters 17, no. 1-2 (January 1985): 183–87. http://dx.doi.org/10.1016/0165-1765(85)90154-5.

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11

Torrez Lamberti, Monica F., Evon DeBose-Scarlett, Timothy Garret, Leslie Ann Parker, Josef Neu, and Graciela L. Lorca. "Metabolomic Profile of Personalized Donor Human Milk." Molecules 25, no. 24 (December 8, 2020): 5783. http://dx.doi.org/10.3390/molecules25245783.

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Human milk could be considered an active and complex mixture of beneficial bacteria and bioactive compounds. Since pasteurization drastically reduces the microbial content, we recently demonstrated that pasteurized donor human milk (DHM) could be inoculated with different percentages (10% and 30%) of mother’s own milk (MOM) to restore the unique live microbiota, resulting in personalized milk (RM10 and RM30, respectively). Pasteurization affects not only the survival of the microbiota but also the concentration of proteins and metabolites, in this study, we performed a comparative metabolomic analysis of the RM10, RM30, MOM and DHM samples to evaluate the impact of microbial restoration on metabolite profiles, where metabolite profiles clustered into four well-defined groups. Comparative analyses of DHM and MOM metabolomes determined that over one thousand features were significantly different. In addition, significant changes in the metabolite concentrations were observed in MOM and RM30 samples after four hours of incubation, while the concentration of metabolites in DHM remained constant, indicating that these changes are related to the microbial expansion. In summary, our analyses indicate that the metabolite profiles of DHM are significantly different from that of MOM, and the profile of MOM may be partially restored in DHM through microbial expansion.
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12

Virgiliou, C., L. Valianou, M. Witting, F. Moritz, C. Fotakis, P. Zoumpoulakis, A. C. Chatziioannou, et al. "Metabolic profile of human coelomic fluid." Bioanalysis 9, no. 1 (January 2017): 37–51. http://dx.doi.org/10.4155/bio-2016-0223.

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13

DUCERF, CHRISTIAN, CLAUDE DUCHAMP, and MICHEL POUYET. "Postoperative Electromyographic Profile in Human Jejunum." Annals of Surgery 215, no. 3 (March 1992): 237–43. http://dx.doi.org/10.1097/00000658-199203000-00007.

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14

Ariza, J., T. Pellicer, R. Pallares, A. Foz, and F. Gudiol. "Specific Antibody Profile in Human Brucellosis." Clinical Infectious Diseases 14, no. 1 (January 1, 1992): 131–40. http://dx.doi.org/10.1093/clinids/14.1.131.

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15

Takagi, Mineo, Haruki Abe, Shigeru Hasegawa, Toyohisa Yoshizawa, and Tomoaki Usui. "Velocity Profile of Human Horizontal Saccades." Ophthalmologica 206, no. 4 (1993): 169–76. http://dx.doi.org/10.1159/000310386.

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16

Meyburg, J., E. Mayatepek, D. Kohlmüller, A. Schulze, and O. Linderkamp. "Postnatal changes in human acylcarnitine profile." Pediatric Research 45, no. 6 (June 1999): 922. http://dx.doi.org/10.1203/00006450-199906000-00231.

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17

Lindskog Jonsson, A., F. F. Hållenius, R. Akrami, E. Johansson, P. Wester, and C. Arnerlov. "Bacterial Profile in Human Atherosclerotic Plaques." Journal of Vascular Surgery 66, no. 5 (November 2017): 1625. http://dx.doi.org/10.1016/j.jvs.2017.08.046.

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18

Rohde, Markus, Inga Sinicina, Anja Horn, Norbert Eichner, Gunter Meister, Michael Strupp, and Susanne Himmelein. "MicroRNA profile of human endo-/perilymph." Journal of Neurology 265, S1 (April 17, 2018): 26–28. http://dx.doi.org/10.1007/s00415-018-8862-3.

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19

Chyuan Jy Wu and Jun S. Huang. "Human face profile recognition by computer." Pattern Recognition 23, no. 3-4 (January 1990): 255–59. http://dx.doi.org/10.1016/0031-3203(90)90013-b.

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20

Lindskog Jonsson, Annika, Frida Fåk Hållenius, Rozita Akrami, Elias Johansson, Per Wester, Conny Arnerlöv, Fredrik Bäckhed, and Göran Bergström. "Bacterial profile in human atherosclerotic plaques." Atherosclerosis 263 (August 2017): 177–83. http://dx.doi.org/10.1016/j.atherosclerosis.2017.06.016.

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21

Al-Mubarak, Haitham F. "Human Face Identification from Profile Projection." Journal of Al-Nahrain University Science 17, no. 3 (September 1, 2017): 204–9. http://dx.doi.org/10.22401/jnus.17.3.28.

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22

Sabates-Bellver, J., L. G. Van der Flier, M. de Palo, E. Cattaneo, C. Maake, H. Rehrauer, E. Laczko, et al. "Transcriptome Profile of Human Colorectal Adenomas." Molecular Cancer Research 5, no. 12 (December 1, 2007): 1263–75. http://dx.doi.org/10.1158/1541-7786.mcr-07-0267.

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23

Hashimoto, Shin-ichi, Shigenori Nagai, Jun Sese, Takuji Suzuki, Aya Obata, Taku Sato, Nobuaki Toyoda, et al. "Gene expression profile in human leukocytes." Blood 101, no. 9 (May 1, 2003): 3509–13. http://dx.doi.org/10.1182/blood-2002-06-1866.

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Leukocytes are classified as myelocytic or lymphocytic, and each class of leukocytes consists of several types of cells that have different phenotypes and different roles. To define the gene expression in these cells, we have performed serial analysis of gene expression (SAGE) using human leukocytes and have provided the gene database for these cells not only at the resting stage but also at the activated stage. A total of 709 990 tags from 17 libraries were analyzed for the manifestation of gene expression profiles in various types of human leukocytes. Types of leukocytes analyzed were as follows: peripheral blood monocytes, colony-stimulating factor–induced macrophages, monocyte-derived immature dendritic cells, mature/activated dendritic cells, granulocytes, natural killer (NK) cells, resting B cells, activated B cells, naive T cells, CCR4− memory T cells (resting TH1 cells), CCR4+ memory T cells (resting TH2 cells), activated TH1 cells, and activated TH2 cells. Among 38 961 distinct tags that appeared more than once in the combined total libraries, 27 323 tags were found to represent unique genes in certain type(s) of leukocytes. Using probability (P) and hierarchical clustering analysis, we identified the genes selectively expressed in each type of leukocytes. Identification of the genes specifically expressed in different types of leukocytes provides not only a novel molecular signature to define different subsets of resting and activated cells but also contributes to further understanding of the biologic function of leukocytes in the host defense system.
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24

Hersh, A. D., N. A. Roberts, A. Guz, and T. D. Tetley. "Elastase Profile of Human Lung Lavage." Clinical Science 72, s16 (January 1, 1987): 6P. http://dx.doi.org/10.1042/cs072006p.

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25

di Masi, Alessandra, Loris Leboffe, Armida Sodo, Gaia Tabacco, Roberto Cesareo, Marco Sbroscia, Isabella Giovannoni, et al. "Metabolic profile of human parathyroid adenoma." Endocrine 67, no. 3 (November 30, 2019): 699–707. http://dx.doi.org/10.1007/s12020-019-02146-x.

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26

Majewska, Marta, Aleksandra Lipka, Lukasz Paukszto, Jan Pawel Jastrzebski, Kamil Myszczynski, Marek Gowkielewicz, Marcin Jozwik, and Mariusz Krzysztof Majewski. "Transcriptome profile of the human placenta." Functional & Integrative Genomics 17, no. 5 (March 1, 2017): 551–63. http://dx.doi.org/10.1007/s10142-017-0555-y.

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27

Ferdoushi, Aysha, Xiang Li, Muhammad Fairuz Bin Jamaluddin, and Hubert Hondermarck. "Proteomic Profile of Human Schwann Cells." PROTEOMICS 20, no. 1 (December 23, 2019): 1900294. http://dx.doi.org/10.1002/pmic.201900294.

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28

Rabaza, Ana, Federico Giannitti, Martín Fraga, Melissa Macías-Rioseco, Luis G. Corbellini, Franklin Riet-Correa, Darío Hirigoyen, Katy M. E. Turner, and Mark C. Eisler. "Serological Evidence of Human Infection with Coxiella burnetii after Occupational Exposure to Aborting Cattle." Veterinary Sciences 8, no. 9 (September 16, 2021): 196. http://dx.doi.org/10.3390/vetsci8090196.

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Cattle are broadly deemed a source of Coxiella burnetii; however, evidence reinforcing their role in human infection is scarce. Most published human Q fever outbreaks relate to exposure to small ruminants, notably goats. Anti-phase II C. burnetii IgG and IgM were measured by indirect fluorescent antibody tests in 27 farm and veterinary diagnostic laboratory workers to ascertain whether occupational exposure to cattle aborting due to C. burnetii was the probable source of exposure. Four serological profiles were identified on the basis of anti-phase II IgG and IgM titres. Profile 1, characterised by high IgM levels and concurrent, lower IgG titres (3/27; 11.1%); Profile 2, with both isotypes with IgG titres higher than IgM (2/27; 7.4%); Profile 3 with only IgG phase II (5/27; 18.5%); and Profile 4, in which neither IgM nor IgG were detected (17/27; 63.0%). Profiles 1 and 2 are suggestive of recent C. burnetii exposure, most likely 2.5–4.5 months before testing and, hence, during the window of exposure to the bovine abortions. Profile 3 suggested C. burnetii exposure that most likely predated the window of exposure to aborting cattle, while Profile 4 represented seronegative individuals and, hence, likely uninfected. This study formally linked human Q fever to exposure to C. burnetii infected cattle as a specific occupational hazard for farm and laboratory workers handling bovine aborted material.
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Lu, Shufang, Funan Lu, Xufeng Shou, and Shuaiyin Zhu. "DeepProfile: Accurate Under-the-Clothes Body Profile Estimation." Applied Sciences 12, no. 4 (February 21, 2022): 2220. http://dx.doi.org/10.3390/app12042220.

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Accurate human body profiles have many potential applications. Image-based human body profile estimation can be regarded as a fine-grained semantic segmentation problem, which is typically used to locate objects and boundaries in images. However, existing image segmentation methods, such as human parsing, require significant amounts of annotation and their datasets consider clothes as part of the human body profile. Therefore, the results they generate are not accurate when the human subject is dressed in loose-fitting clothing. In this paper, we created and labeled an under-the-clothes human body contour keypoint dataset; we utilized a convolutional neural network (CNN) to extract the contour keypoints, then combined them with a body profile database to generate under-the-clothes profiles. In order to improve the precision of keypoint detection, we propose a short-skip multi-scale dense (SMSD) block in the CNN to keep the details of the image and increase the information flow among different layers. Extensive experiments were conducted to show the effectiveness of our method. We demonstrate that our method achieved better results—especially when the person was dressed in loose-fitting clothes—than and competitive quantitative performance compared to state-of-the-art methods, while requiring less annotation effort. We also extended our method to the applications of 3D human model reconstruction and body size measurement.
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Torp, Andronicus, Andreia Gabriela Andrei, and Anca Alexandra Purcarea. "Human resource performance predictors based on the human energy profile." Proceedings of the International Conference on Business Excellence 12, no. 1 (May 1, 2018): 975–82. http://dx.doi.org/10.2478/picbe-2018-0087.

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Abstract This paper is a comparative study on the findings regarding the connection between a person’s energy profile and that person’s professional performance. As the performance predictors that are used within Human Resource Management may provide a company with important information regarding the future performance of an employee, it is of great importance that these performance predictors be kept up-to-date, both in what regards the precision of each predictor, and by including new performance predictors to the present array of HR predictors should such new predictors be found. This paper is an empirical examination of two such predictors, stress and energy, and argues that, based on the available empirical material, it seems to be possible to expand the present selection of HR predictors with these two predictors as well. This study is based on the ontological framework set forth by academics such as Einstein, Hawking, Tiller, Hunt, Motoyama, regarding the possibility of assessing the human being based on their energy profile. The part concerning Human Resource Management is based on the scientific framework put forth by Hunter & Hunter. Their study shows the validity of the vast majority of the performance predictors used within Human Resource Management, and discusses their practical validity. Then, there is the trans-disciplinary approach, where it is shown based on the empirical studies conducted by Torp et al. if, and how, the present array of performance indicators that are used in the field of Human Resource Management may be improved. Here, different and complementary scientific studies are included to document that the proposed Human Resource Management performance predictor is in reality more than just a predictor, it is an assessment tool that can both predict, and at the same time help quantify a series of the most modern initiatives within Human Resource Management, such as integrating sport, mindfulness, diet, etc. in the workday in order to improve performance.
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Li, Jingjing, Jian Zhang, Bo Shao, and Chunxiao Chen. "A latent profile analysis of work passion: structure, antecedent, and outcomes." Personnel Review 49, no. 3 (November 14, 2019): 846–63. http://dx.doi.org/10.1108/pr-04-2019-0145.

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Purpose Previous research draws on the dualistic model of passion (harmonious and obsessive passion) overlooks how the different two types of passion interact within individuals using a variable-centered approach. The purpose of this paper is to identify work passion profiles and their antecedent and consequences adopting a person-centered approach, and to explain inconsistences in previous studies. Design/methodology/approach This paper conducts three studies (n=2,749 in total) using a latent profile analysis. Study 1 identifies three work passion profiles, namely, dual passion, pro harmonious passion and pro obsessive passion; study 2 examines dialectical thinking as an antecedent to work passion profile membership; study 3 examines how each profile relates to work performance and well-being. Findings This paper finds that the participants with a dual passion profile showed higher task performance and subjective well-being than the participants with the other two profiles; the participants with a pro obsessive passion profile were higher in task performance, interpersonal performance and psychological well-being than the participants with a pro harmonious profile. Originality/value This paper is the first that uses a latent profile analysis approach to examining work passion configurations. It provides a unique perspective to investigate how different types of passion configure and interact within individuals; it explores an antecedent (i.e. dialectical thinking) and outcomes (i.e. performance and well-being) of the three work passion profiles.
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Trifonova, O. P., P. G. Lokhov, and A. I. Archakov. "Metabolic profiling of human blood." Biomeditsinskaya Khimiya 60, no. 3 (2014): 281–94. http://dx.doi.org/10.18097/pbmc20146003281.

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Metabolomics is a novel “omics” branch of science intended for studying a comprehensive set of low molecular weight substances (metabolites) of various biological objects. Metabolite profiles represent a molecular phenotype of biological systems and reflect information encoded at the genome level and realized at the transcriptome and proteome levels. Analysis of human blood metabolic profile is universal and promising tool for clinical applications because it is a sensitive measure of both endogenous and exogenous (environmental) factors affected on the patient's organism. Technical implementation of metabolic profiling of blood and statistic analysis of metabolite profiles for effective diagnostics and risk assessments of diseases are discussed in this review.
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George, Varghese, Sethu Babu, Sahoo RS, and Jha RK. "Lipid profile abnormalities in human immunodeficiency virus infected patients- a hospital based study." Asian Pacific Journal of Health Sciences 2, no. 1 (January 2015): 76–81. http://dx.doi.org/10.21276/apjhs.2015.2.1.13.

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Chandraganesh, B., J. Nareshkumar, and S. Thirumal. "Secure Authentication to Identify the Human using Finger Printer Profile in Voting System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 256–58. http://dx.doi.org/10.31142/ijtsrd10860.

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35

Ribeiro-de-Jesus, A., R. P. Almeida, H. Lessa, O. Bacellar, and E. M. Carvalho. "Cytokine profile and pathology in human leishmaniasis." Brazilian Journal of Medical and Biological Research 31, no. 1 (January 1998): 143–48. http://dx.doi.org/10.1590/s0100-879x1998000100020.

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Kim, Nayoung, Yourae Hong, Doyoung Kwon, and Sukjoon Yoon. "Somatic Mutaome Profile in Human Cancer Tissues." Genomics & Informatics 11, no. 4 (2013): 239. http://dx.doi.org/10.5808/gi.2013.11.4.239.

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Lucena, Gema, Candela Reyes-Botella, Olga García-Martínez, Lourdes Díaz-Rodríguez, Francisco Alba, and Concepción Ruiz. "Aminopeptidase Activity Profile in Cultured Human Osteoblasts." Biological Research For Nursing 15, no. 1 (July 15, 2011): 56–61. http://dx.doi.org/10.1177/1099800411414870.

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Aminopeptidases (APs) are enzymes involved in a wide variety of biological processes and present in a variety of different cell populations. The authors studied these enzymes in primary cultured human osteoblasts in order to establish an activity profile and thereby contribute to knowledge of bone tissue. The authors used 13 different substrates ( N-terminal amino acids) and a fluorimetric assay to examine AP activity associated with the membranes of cultured osteoblasts. The authors demonstrated activity > 10 pmol/min/104 cells when glycine, alanine, leucine, arginine, phenylalanine, methionine, and lysine were used as substrates. The activity was markedly lower (<1.6 pmol/min/104 cells) when the other N-terminal amino acids were used. Puromycin and bestatin inhibited AP activity, though not completely, when we used AlaNA or LeuNA as substrates. Further studies are warranted to determine the role of these enzymes in bone tissue physiology.
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Fitzgerald, John P., and Nathan Efron. "Oxygen uptake profile of the human cornea." Clinical and Experimental Optometry 69, no. 4 (June 1986): 149–52. http://dx.doi.org/10.1111/j.1444-0938.1986.tb04579.x.

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Tong, A. W., P. Fulgham, C. Jay, P. Chen, I. Khalil, S. Liu, N. Senzer, A. C. Eklund, J. Han, and J. Nemunaitis. "MicroRNA profile analysis of human prostate cancers." Cancer Gene Therapy 16, no. 3 (October 24, 2008): 206–16. http://dx.doi.org/10.1038/cgt.2008.77.

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Shugaba, A. I., M. B. T. Umar ., and S. P. Singh . "Histomorphometric Profile of the Human Vermiform Appendix." Journal of Medical Sciences 6, no. 3 (April 15, 2006): 445–51. http://dx.doi.org/10.3923/jms.2006.445.451.

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Mei, Yu, Wenya Linda Bi, Noah F. Greenwald, Nathalie Y. Agar, Rameen Beroukhim, Gavin P. Dunn, and Ian F. Dunn. "Genomic profile of human meningioma cell lines." PLOS ONE 12, no. 5 (May 26, 2017): e0178322. http://dx.doi.org/10.1371/journal.pone.0178322.

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Jeon, Y., S. Bekiranov, N. Karnani, P. Kapranov, S. Ghosh, D. MacAlpine, C. Lee, D. S. Hwang, T. R. Gingeras, and A. Dutta. "Temporal profile of replication of human chromosomes." Proceedings of the National Academy of Sciences 102, no. 18 (April 21, 2005): 6419–24. http://dx.doi.org/10.1073/pnas.0405088102.

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Panfilov, V. E., and V. S. Gurfinkel. "Biomechanical profile of the human-spacesuit interaction." Human Physiology 39, no. 7 (December 2013): 750–55. http://dx.doi.org/10.1134/s036211971307013x.

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Kivelä, T. "Antigenic profile of the human lacrimal gland." Journal of Histochemistry & Cytochemistry 40, no. 5 (May 1992): 629–42. http://dx.doi.org/10.1177/40.5.1374091.

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Abstract:
The antigenic profile of 13 normal formalin-fixed, paraffin-embedded human main and accessory lacrimal glands, biopsied from patients aged 11 to 78 years, was studied using a panel of 27 polyclonal and monoclonal antibodies. Secretory cells of lacrimal acini reacted with antibodies to S-100 protein and simple epithelium-type cytokeratins CK 7, CK 8, CK 18, and CK 19. Their luminal membranes were labeled with antibodies to carcinoembryonic antigen, epithelial membrane antigen, and epithelial glycoproteins recognized by Ber-EP4. Myoepithelial cells were often immunopositive for S-100 protein, vimentin, glial fibrillary acidic protein (GFAP), and alpha-smooth muscle actin. More rarely, they reacted with antibodies recognizing CK 5, CK 13, and CK 14, which consistently labeled the basal cells of lacrimal ducts. Unlike myoepithelial cells, basal ductal cells were immunopositive for CK 7, CK 8, CK 18, and CK 19. In main excretory ducts, dendritic melanocyte-like cells co-expressing vimentin and S-100 protein intermingled with ductal epithelial cells. The luminal cells of lacrimal ducts basically paralleled secretory cells in their antigenic profile, although they lacked Ber-EP4 and were immunopositive for CK 4. Antibodies to neuron-specific enolase and synaptophysin reacted with nerve fibers among negatively reacting secretory acini. This antigenic profile closely parallels that of salivary glands and provides a basis for studies of lacrimal gland pathology.
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García-Suárez, Olivia, Marta G. Calavia, Francisco J. Pérez-Moltó, Covadonga Alvarez-Abad, Pablo Pérez-Piñera, Juan M. Cobo, and José A. Vega. "Immunohistochemical Profile of Human Pancreatic Pacinian Corpuscles." Pancreas 39, no. 3 (April 2010): 403–10. http://dx.doi.org/10.1097/mpa.0b013e3181bc0372.

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Pogue, Robert, Eiman Sebald, Lily King, Erik Kronstadt, Deborah Krakow, and Daniel H. Cohn. "A transcriptional profile of human fetal cartilage." Matrix Biology 23, no. 5 (August 2004): 299–307. http://dx.doi.org/10.1016/j.matbio.2004.07.003.

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Gao, Yongsheng, and Maylor K. H. Leung. "Human face profile recognition using attributed string." Pattern Recognition 35, no. 2 (February 2002): 353–60. http://dx.doi.org/10.1016/s0031-3203(01)00023-1.

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Leonard, P., T. Sharp, S. Henderson, D. Hewitt, J. Pringle, A. Sandison, A. Goodship, J. Whelan, and C. Boshoff. "Gene expression array profile of human osteosarcoma." British Journal of Cancer 89, no. 12 (December 2003): 2284–88. http://dx.doi.org/10.1038/sj.bjc.6601389.

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Imai, Ryokichi, Motoyasu Hirao, Hiroshi Tsubota, and Tetsuo Himi. "Expression profile of human defensins in tonsils." International Congress Series 1257 (December 2003): 81–83. http://dx.doi.org/10.1016/s0531-5131(03)01559-0.

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Scaffa, P. M. C., N. M. T. Barros, K. C. S. Modena, C. M. P. Vidal, L. Wang, M. R. Carrilho, and M. A. R. Buzalaf. "Proteolytic activity profile of human dentinal fluid." Dental Materials 32 (2016): e82. http://dx.doi.org/10.1016/j.dental.2016.08.171.

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