NOD2 Agonism Counter-Regulates Human Type 2 T Cell Functions in Peripheral Blood Mononuclear Cell Cultures: Implications for Atopic Dermatitis.

Atopic dermatitis (AD) is known as a skin disease; however, T cell immunopathology found in blood is associated with its severity. Skin Staphylococcus aureus (S. aureus) and associated host-pathogen dynamics are important to chronic T helper 2 (Th2)-dominated inflammation in AD, yet they remain poorly understood. This study sought to investigate the effects of S. aureus-derived molecules and skin alarmins on human peripheral blood mononuclear cells, specifically testing Th2-type cells, cytokines, and chemokines known to be associated with AD. We first show that six significantly elevated Th2-related chemokine biomarkers distinguish blood from adult AD patients compared to healthy controls ex vivo; in addition, TARC/CCL17, LDH, and PDGF-AA/AB correlated significantly with disease severity. We then demonstrate that these robust AD-associated biomarkers, as well as associated type 2 T cell functions, are readily reproduced from healthy blood mononuclear cells exposed to the alarmin TSLP and the S. aureus superantigen SEB in a human in vitro model, including IL-13, IL-5, and TARC secretion as well as OX-40-expressing activated memory T cells. We further show that the agonism of nucleotide-binding oligomerization domain-containing protein (NOD)2 inhibits this IL-13 secretion and memory Th2 and Tc2 cell functional activation while inducing significantly increased pSTAT3 and IL-6, both critical for Th17 cell responses. These findings identify NOD2 as a potential regulator of type 2 immune responses in humans and highlight its role as an endogenous inhibitor of pathogenic IL-13 that may open avenues for its therapeutic targeting in AD.

PCA-Based Incremental Extreme Learning Machine (PCA-IELM) for COVID-19 Patient Diagnosis Using Chest X-Ray Images.

Novel coronavirus 2019 has created a pandemic and was first reported in December 2019. It has had very adverse consequences on people's daily life, healthcare, and the world's economy as well. According to the World Health Organization's most recent statistics, COVID-19 has become a worldwide pandemic, and the number of infected persons and fatalities growing at an alarming rate. It is highly required to have an effective system to early detect the COVID-19 patients to curb the further spreading of the virus from the affected person. Therefore, to early identify positive cases in patients and to support radiologists in the automatic diagnosis of COVID-19 from X-ray images, a novel method PCA-IELM is proposed based on principal component analysis (PCA) and incremental extreme learning machine. The suggested method's key addition is that it considers the benefits of PCA and the incremental extreme learning machine. Further, our strategy PCA-IELM reduces the input dimension by extracting the most important information from an image. Consequently, the technique can effectively increase the COVID-19 patient prediction performance. In addition to these, PCA-IELM has a faster training speed than a multi-layer neural network. The proposed approach was tested on a COVID-19 patient's chest X-ray image dataset. The experimental results indicate that the proposed approach PCA-IELM outperforms PCA-SVM and PCA-ELM in terms of accuracy (98.11%), precision (96.11%), recall (97.50%), F1-score (98.50%), etc., and training speed.

Ecologic Analysis of Correlates of Cervical Cancer Morbidity and Mortality in Sub-Saharan Africa.

BACKGROUND: Cervical cancer is the fourth leading cause of death among women worldwide, with 85% of the burden falling on low- to middle- income countries. We studied the correlates of cervical cancer incidence and mortality, and case-fatality in Sub-Saharan Africa. METHODS: Country-level data on 16 putative cervical cancer correlates for 37 Sub-Saharan African countries were collected from publicly available data sources. We performed univariate and multiple (stepwise) linear regression analyses to identify correlates of cervical cancer incidence and mortality, and case-fatality. RESULTS: In univariate analyses, incidence and mortality rates were significantly correlated with contraceptive use, penile cancer incidence, and human immunodeficiency virus prevalence. Incidence rates were also correlated with literacy rates, whereas mortality rates were correlated with the proportion of rural population and screening coverage. Multiple regression analyses showed contraceptive use (P = 0.009) and penile cancer incidence (P = 0.004) as associated with cervical cancer incidence. Penile cancer incidence (P = 9.77 × 10-5) and number of medical doctors (P = 0.0433) were associated with mortality. The goodness of fit of the incidence and mortality models was moderate at best, explaining 49% and 37% of variability in the data, respectively. However, the case-fatality model had the best fit explaining most of the variation (adjusted R2 = 0.948; P = 6.822 × 10-16). CONCLUSIONS: To reduce the burden of cervical cancer in Sub-Saharan Africa, it would be important to design multimodal interventions that not only target screening and HPV vaccination, but also focus on cervical cancer correlates. IMPACT: Identifying contextual factors associated with cervical cancer in this region could inform targeted interventions.

A preliminary biomechanical study of cyclic preconditioning effects on canine cadaveric whole femurs.

Biomechanical preconditioning of biological specimens by cyclic loading is routinely done presumably to stabilize properties prior to the main phase of a study. However, no prior studies have actually measured these effects for whole bone of any kind. The aim of this study, therefore, was to quantify these effects for whole bones. Fourteen matched pairs of fresh-frozen intact cadaveric canine femurs were sinusoidally loaded in 4-point bending from 50 N to 300 N at 1 Hz for 25 cycles. All femurs were tested in both anteroposterior (AP) and mediolateral (ML) bending planes. Bending stiffness (i.e., slope of the force-vs-displacement curve) and linearity R(2) (i.e., coefficient of determination) of each loading cycle were measured and compared statistically to determine the effect of limb side, cycle number, and bending plane. Stiffnesses rose from 809.7 to 867.7 N/mm (AP, left), 847.3 to 915.6 N/mm (AP, right), 829.2 to 892.5 N/mm (AP, combined), 538.7 to 580.4 N/mm (ML, left), 568.9 to 613.8 N/mm (ML, right), and 553.8 to 597.1 N/mm (ML, combined). Linearity R(2) rose from 0.96 to 0.99 (AP, left), 0.97 to 0.99 (AP, right), 0.96 to 0.99 (AP, combined), 0.95 to 0.98 (ML, left), 0.94 to 0.98 (ML, right), and 0.95 to 0.98 (ML, combined). Stiffness and linearity R(2) versus cycle number were well-described by exponential curves whose values leveled off, respectively, starting at 12 and 5 cycles. For stiffness, there were no statistical differences for left versus right femurs (p = 0.166), but there were effects due to cycle number (p < 0.0001) and AP versus ML bending plane (p < 0.0001). Similarly, for linearity, no statistical differences were noted due to limb side (p = 0.533), but there were effects due to cycle number (p < 0.0001) and AP versus ML bending plane (p = 0.006). A minimum of 12 preconditioning cycles was needed to fully stabilize both the stiffness and linearity of the canine femurs. This is the first study to measure the effects of mechanical preconditioning on whole bones, having some practical implications on research practices.