Optimization of synchrotron radiation parameters using swarm intelligence and evolutionary algorithms.

Alignment of each optical element at a synchrotron beamline takes days, even weeks, for each experiment costing valuable beam time. Evolutionary algorithms (EAs), efficient heuristic search methods based on Darwinian evolution, can be utilized for multi-objective optimization problems in different application areas. In this study, the flux and spot size of a synchrotron beam are optimized for two different experimental setups including optical elements such as lenses and mirrors. Calculations were carried out with the X-ray Tracer beamline simulator using swarm intelligence (SI) algorithms and for comparison the same setups were optimized with EAs. The EAs and SI algorithms used in this study for two different experimental setups are the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). While one of the algorithms optimizes the lens position, the other focuses on optimizing the focal distances of Kirkpatrick-Baez mirrors. First, mono-objective evolutionary algorithms were used and the spot size or flux values checked separately. After comparison of mono-objective algorithms, the multi-objective evolutionary algorithm NSGA-II was run for both objectives - minimum spot size and maximum flux. Every algorithm configuration was run several times for Monte Carlo simulations since these processes generate random solutions and the simulator also produces solutions that are stochastic. The results show that the PSO algorithm gives the best values over all setups.

The predictive role of NF-κB-mediated pro-inflammatory cytokine expression levels in hepatitis B vaccine response.

Hepatitis B virus (HBV) infection is a global health problem leading to cirrhosis, hepatocellular carcinoma, and liver failure. The Hepatitis B vaccine plays a significant role in reducing the incidence of HBV worldwide. Approximately 5-10% of vaccinated people do not produce protective antibody levels. Nuclear factor kappa B (NF­κB) mediates inflammatory responses through pro-inflammatory cytokines. However, the role of the NF­κB signaling pathway and its association with pro-inflammatory cytokines in hepatitis B vaccine response is unclear. We aimed to assess changes in the IL1A, IL6, IL12A, TNF-α, and NFκB1 expression levels in the non-responder and responder. A total of 32 non-responders and 36 responders were included in the study. The expression level of determined genes was analyzed by RT-PCR. Our results showed that IL1A, IL6, IL12A, and NFκB1 mRNA levels significantly increased in the non-responders compared to the responders (p < .01). Furthermore, there was a significant correlation between IL1A, IL6, TNF-α, and NFκB1 in the non-responder and responders. In conclusion, inflammatory signaling pathways may play an important role in response to HBV vaccine. Therefore, NF­κB signaling and associated pro-inflammatory cytokine mRNA levels could predict hepatitis B vaccine response. However, the underlying molecular mechanisms of hepatitis B vaccine immunity need further investigation.

Can prognostic nutritional index and systemic immune-inflammatory index predict disease severity in COVID-19?

BACKGROUND: Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are inflammation-based novel markers that predict the prognosis in various patient populations. We have investigated the relationship between the disease severity in COVID-19, and the PNI and SII scores in the present study. MATERIALS AND METHODS: This cross-sectional retrospective study included 118 hospitalised patients with a confirmed diagnosis of COVID-19. The patients were divided into two groups as those who were hospitalised at the intensive care unit (ICU) and those who had been internalised at the clinic (non-ICU). RESULTS: Of the 118 patients, 50.8% were male. The mean age was 57.7 ± 17.5 years in non-ICU patients and 70.3 ± 11.7 years in ICU patients and the difference was statistically significant (P < .001). The lymphocyte count and the albumin levels were significantly lower in ICU patients (P < .001, P < .001, respectively). The PNI score was significantly lower in ICU patients compared with non-ICU patients (P < .001). The SII score was found to be significantly higher in ICU patients compared with non-ICU patients (P < .001). The value of PNI and SII scores in prediction of the disease severity in COVID-19 was evaluated with the ROC analysis (PNI: AUC = 0.796, 95%CI: 0.715-0.877, P < .001; SII: AUC =0.689, 95% CI: 0.559-0.819, P=.004). When the cut-off value was taken as ≤36.7 for the PNI score, it was found to have 73.4% sensitivity and 70.8% specificity for predicting of the disease severity and ICU admission probability was 4.4 times higher. When the cut-off value was taken as ≥813.6 for SII score, it was found to have 70.8% sensitivity and 66.0% specificity for predicting of the disease severity and ICU admission probability was six times higher. CONCLUSION: The PNI and the SII scores are independent predictors of the prognosis and the disease severity in COVID-19 patients who require hospitalisation at the ICU.

Association of vitamin D insufficiency/deficiency with thyroid artery Doppler ultrasonography in patients with Hashimoto thyroiditis.

BACKGROUND & OBJECTIVE: During the course of the autoimmune thyroid diseases, ultrasonography change parallel to histopathology. Vitamin D is associated with autoimmune diseases and thus can affect thyroid blood flow. Our aim was to investigate the relationship between vitamin D insufficiency/deficiency and thyroid hemodynamic indices in patients with Hashimoto thyroiditis. METHODS: A total of 93 patients who presented to Sakarya University Endocrinology outpatient clinic from April to September 2016 and diagnosed with Hashimoto thyroiditis were included in this study. Clinical and serologic data, thyroid antibodies and 25(OH)D3 were evaluated. Mean peak systolic velocity(mPSV), mean end-diastolic velocity (EDV), mean resistive index (RI) flows of superior and inferior thyroid arteries were measured with B-mode Doppler ultrasonography. RESULTS: Vitamin D insufficiency/deficiency was detected in 59 (63.4%). TPO Ab and TgAb levels were found higher in patients with vitamin D insufficiency/deficiency. In the normal vitamin D group, superior thyroid artery mPSV (32.21±6.73cm/s) and EDV(13.27±2.80 cm/s) were higher than in the low vitamin D group [mPSV (28.32±8.99cm/s) and EDV(10.67±3.68 cm/s)] (P=0.034, P=0.001, respectively). Inferior thyroid artery EDV value was higher in the normal compared to the low vitamin D group (0.032). RI measured in all arteries were higher in the vitamin D insufficient/deficient group compared to the Vitamin D normal group (p=0.001). CONCLUSION: Vitamin-D insufficiency/deficiency has led to reduced parenchymal blood supply and increased micro-vascular resistance in Hashimoto thyroiditis patients.

Enhanced enchondroma detection from x-ray images using deep learning: A step towards accurate and cost-effective diagnosis.

This study investigates the automated detection of enchondromas, benign cartilage tumors, from x-ray images using deep learning techniques. Enchondromas pose diagnostic challenges due to their potential for malignant transformation and overlapping radiographic features with other conditions. Leveraging a data set comprising 1645 x-ray images from 1173 patients, a deep-learning model implemented with Detectron2 achieved an accuracy of 0.9899 in detecting enchondromas. The study employed rigorous validation processes and compared its findings with the existing literature, highlighting the superior performance of the deep learning approach. Results indicate the potential of machine learning in improving diagnostic accuracy and reducing healthcare costs associated with advanced imaging modalities. The study underscores the significance of early and accurate detection of enchondromas for effective patient management and suggests avenues for further research in musculoskeletal tumor detection.

Association of ABO blood group and age with COVID-19 positive test.

OBJECTIVE: The aim of this study is to evaluate the relation between the coronavirus (SARS-CoV-2) disease (COVID-19) and blood groups and the Rh factor. METHOD: A total of 313 patients hospitalized in the Internal Medicine clinic, at the intensive care unit (ICU) were included in the study. The cases were divided into two groups: those who were COVID-19 positive and those negative, detected with real-time reverse transcription polymerase chain reaction testing. The demographic, clinical, ABO blood groups, and Rh factor data of the cases were obtained from the hospital records retrospectively. RESULTS: The mean age of COVID-19 positive (+) cases was 57.74±16 years and of COVID-19 negative (-) cases, 66.41±15 years. The difference was significant (p<0.001); there was no difference between the two groups in terms of sex (p=0.634). When age was categorically separated in COVID-19 (+) cases, χ2 was extremely significant. Among the ABO blood groups of COVID-19 (+) and (-) cases, χ2 was 4.975 (p=0.174). In the logistic regression, it was 4.1 (p=0.011) in the O blood group. COVID-19 positive test was determined as 13, 4, and 4 times higher in the 31-40, 41-50, and 51-60 age groups, respectively (p=0.001, p=0.010, p=0.003). CONCLUSION: The incidence of COVID-19 has increased in the younger population and in the O blood group. Our findings support that, in this population, the ABO blood groups can contribute to the early detection of COVID-19.

Association of ABO blood group and age with COVID-19 positive test

ABSTRACT OBJECTIVE: The aim of this study is to evaluate the relation between the coronavirus (SARS-CoV-2) disease (COVID-19) and blood groups and the Rh factor. METHOD: A total of 313 patients hospitalized in the Internal Medicine clinic, at the intensive care unit (ICU) were included in the study. The cases were divided into two groups: those who were COVID-19 positive and those negative, detected with real-time reverse transcription polymerase chain reaction testing. The demographic, clinical, ABO blood groups, and Rh factor data of the cases were obtained from the hospital records retrospectively. RESULTS: The mean age of COVID-19 positive (+) cases was 57.74±16 years and of COVID-19 negative (-) cases, 66.41±15 years. The difference was significant (p<0.001); there was no difference between the two groups in terms of sex (p=0.634). When age was categorically separated in COVID-19 (+) cases, χ2 was extremely significant. Among the ABO blood groups of COVID-19 (+) and (-) cases, χ2 was 4.975 (p=0.174). In the logistic regression, it was 4.1 (p=0.011) in the O blood group. COVID-19 positive test was determined as 13, 4, and 4 times higher in the 31-40, 41-50, and 51-60 age groups, respectively (p=0.001, p=0.010, p=0.003). CONCLUSION: The incidence of COVID-19 has increased in the younger population and in the O blood group. Our findings support that, in this population, the ABO blood groups can contribute to the early detection of COVID-19.