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001-es BibID:	BIBFORM118662
035-os BibID:	(WoS)001161390600001 (Scopus)85185143533
Első szerző:	Baráth Sándor (biológus)
Cím:	Enhancing HLA-B27 antigen detection : Leveraging machine learning algorithms for flow cytometric analysis / Baráth Sándor, Singh Parvind, Hevessy Zsuzsanna, Ujfalusi Anikó, Mezei Zoltán, Balogh Mária, Száraz Széles Marianna, Kappelmayer János
Dátum:	2024
ISSN:	1552-4949
Megjegyzések:	As the association of human leukocyte antigen B27 (HLA-B27) with spondylarthropathies is widely known, HLA-B27 antigen expression is frequently identified using flow cytometric or other techniques. Because of the possibility of cross-reaction with off target antigens, such as HLA-B7, each flow cytometric technique applies a "gray zone" reserved for equivocal findings. Our aim was to use machine learning (ML) methods to classify such equivocal data as positive or negative. Equivocal samples (n = 99) were selected from samples submitted to our institution for clinical evaluation by HLA-B27 antigen testing. Samples were analyzed by flow cytometry and polymerase chain reaction. Features of histograms generated by flow cytometry were used to train and validate ML methods for classification as logistic regression (LR), decision tree (DT), random forest (RF) and light gradient boost method (GBM). All evaluated ML algorithms performed well, with high accuracy, sensitivity, specificity, as well as negative and positive predictive values. Although, gradient boost approaches are proposed as high performance methods; nevertheless, their effectiveness may be lower for smaller sample sizes. On our relatively smaller sample set, the random forest algorithm performed best (AUC: 0.92), but there was no statistically significant difference between the ML algorithms used. AUC values for light GBM, DT, and LR were 0.88, 0.89, 0.89, respectively. Implementing these algorithms into the process of HLA-B27 testing can reduce the number of uncertain, false negative or false positive cases, especially in laboratories where no genetic testing is available.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Cytometry Part B-Clinical Cytometry. - [Epub ahead of print] (2024). -
További szerzők:	Singh, Parvind (1995-) (PhD hallgató) Hevessy Zsuzsanna (1966-) (laboratóriumi szakorvos) Ujfalusi Anikó (1968-) (gyermekorvos, laboratóriumi szakorvos) Mezei Zoltán András (1980-) (orvos) Balogh Mária Széles Mariann Kappelmayer János (1960-) (laboratóriumi szakorvos)
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001-es BibID:	BIBFORM101986
035-os BibID:	(WoS)000797541200001 (Scopus)85130347509
Első szerző:	Singh, Parvind (PhD hallgató)
Cím:	Gender-dependent frequency of unconventional T cells in a healthy adult Caucasian population : a combinational study of invariant NKT cells, [gamma] [delta] T cells, and mucosa-associated invariant T cells / Singh Parvind, Szaraz-Szeles Marianna, Mezei Zoltan, Barath Sandor, Hevessy Zsuzsanna
Dátum:	2022
ISSN:	0741-5400
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Journal Of Leukocyte Biology. - 112 : 5 (2022), p. 1155-1165. -
További szerzők:	Széles Mariann Mezei Zoltán András (1980-) (orvos) Baráth Sándor (1977-) (biológus) Hevessy Zsuzsanna (1966-) (laboratóriumi szakorvos)
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001-es BibID:	BIBFORM099847
035-os BibID:	(WOS)000743412100002 (Scopus)85123091562
Első szerző:	Singh, Parvind (PhD hallgató)
Cím:	Age-dependent frequency of unconventional T cells in a healthy adult Caucasian population : a combinational study of invariant natural killer T cells, [gamma][delta] T cells, and mucosa-associated invariant T cells / Singh Parvind, Szaraz-Szeles Marianna, Mezei Zoltan, Barath Sandor, Hevessy Zsuzsanna
Dátum:	2022
ISSN:	2509-2715 2509-2723
Megjegyzések:	Unconventional T cells show distinct and unique features during antigen recognition as well as other immune responses. Their decrease in frequency is associated with various autoimmune disorders, allergy, inflammation, and cancer. The landscape frequency of the unconventional T cells altogether (iNKT, gamma delta T, and MAIT) is largely unestablished leading to various challenges affecting diagnosis and research in this field. In this study, we have established the age group-wise frequency of iNKT, gamma delta T, and MAIT cells altogether on a total of 203 healthy adult samples of the Caucasian population. The results revealed that iNKT cells were 0.095%, gamma delta T cells were 2.175%, and MAIT cells were 2.99% of the total T cell population. gamma delta and MAIT cell frequency is higher in younger age groups than elderly; however, there is no statistically significant difference in the frequency of iNKT cells. Furthermore, gamma delta and MAIT cells were negatively correlating with age, supporting immunosenescence, unlike iNKT cells. Our finding could be used for further age-wise investigation of various pathological conditions such as cancer and their prognosis, autoimmune diseases and their pathogenicity.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Unconventional T cells iNKT cells gamma delta T cells MAIT cells frequency reference range age dependent
Megjelenés:	GeroScience. - 44 : 4 (2022), p. 2047-2060. -
További szerzők:	Széles Mariann Mezei Zoltán András (1980-) (orvos) Baráth Sándor (1977-) (biológus) Hevessy Zsuzsanna (1966-) (laboratóriumi szakorvos)
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