Results 31 to 40 of about 124,897 (378)

Social geography of rhinoscleroma and qualitatively and quantitatively abnormal cell-mediated immunity [PDF]

open access: yes, 2018
Rhinoscleroma is a progressive chronic granulomatous disease of the upper respiratory tract that may extend to the tracheobronchial tract. It is common belief that the pathology is determined by Klebsiella Rhinoscleromatis.
A. Ciofalo   +5 more
core   +1 more source

Forecasting Disease Burden In Philippines: A Symbolic Regression Analysis [PDF]

open access: yesarXiv, 2021
Burden of disease measures the impact of living with illness and injury and dying prematurely and it is increasing worldwide leading cause of death both global and national. This paper aimed to propose an index of diseases and evaluate a mathematical model to describe the number of burden of disease by cause in the Philippines from 1990 - 2016. Through
arxiv  

Disseminated perforating necrobiosis lipoidica: A case report and literature review

open access: yesClinical Case Reports, 2023
Key Clinical Message Necrobiosis lipoidica is a rare cutaneous granulomatous disease that mainly affects diabetic patients. The perforating type of the disease is an uncommon variant that is resistant to therapy and can be easily identified using ...
Mina Saber   +2 more
doaj   +1 more source

Recognition and Clinical Presentation of Invasive Fungal Disease in Neonates and Children [PDF]

open access: yes, 2017
AW and JK are supported by the Wellcome Trust Strategic Award (grant 097377) and the MRC Centre for Medical Mycology (grant MR/N006364/1) at the University of AberdeenPeer reviewedPublisher ...
King, Jill   +4 more
core   +1 more source

Non-infectious Complications of Common Variable Immunodeficiency: Updated Clinical Spectrum, Sequelae, and Insights to Pathogenesis

open access: yesFrontiers in Immunology, 2020
Non-infectious complications in common variable immunodeficiency (CVID) have emerged as a major clinical challenge. Detailed clinical spectrum, organ-specific pathologies and associated sequelae from 623 CVID patients followed in New York since 1974 were
Hsi-en Ho   +2 more
doaj   +1 more source

Sarcoidosis presenting as granulomatous myositis in a 16-year-old adolescent [PDF]

open access: yes, 2016
BACKGROUND: Sarcoidosis is a multi-system disease characterized by the presence of non-caseating epithelioid granulomas in affected tissues, including skeletal muscle.
Eutsler, Eric Eutsler   +4 more
core   +2 more sources

Genetic predisposition to porto‐sinusoidal vascular disorder: A functional genomic‐based, multigenerational family study

open access: yesHepatology, EarlyView., 2022
A deleterious variant of FCHSD1 results in mTOR pathway overactivation and may cause porto‐sinusoidal vascular disorder (PSVD). The pedigree of the family demonstrated an autosomal dominant disease with variable expressivity. Whole‐genome sequencing and Sanger sequencing both validated the existence of the FCHSD1 variant and the heterozygosity of c ...
Jingxuan Shan   +19 more
wiley   +1 more source

Chronic Granulomatous Disease: the Experience of Diagnosis and Treatment in Children

open access: yesZdorovʹe Rebenka, 2013
Chronic granulomatous disease — primary immunodeficiency with X-linked and autosomal recessive inheritance, characterized by impaired bactericidal function of phagocytic immune system.
L.I. Chernyshova   +4 more
doaj   +1 more source

Mechanism-based strategies for the management of autoimmunity and immune dysregulation in primary immunodeficiencies [PDF]

open access: yes, 2016
A broad spectrum of autoimmunity is now well described in patients with primary immunodeficiencies (PIDs). Management of autoimmune disease in the background of PID is particularly challenging given the seemingly discordant goals of immune support and ...
Cooper, Megan A   +4 more
core   +2 more sources

CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays [PDF]

open access: yesarXiv, 2021
We systematically evaluate the performance of deep learning models in the presence of diseases not labeled for or present during training. First, we evaluate whether deep learning models trained on a subset of diseases (seen diseases) can detect the presence of any one of a larger set of diseases.
arxiv  

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