Incidence and Prognosis of COVID-19 in Patients with Psoriasis: A Multicenter Prospective Study from the Eastern Black Sea Region of Turkey

COVID-19 infection can have a poor prognosis, especial- ly in patients with chronic diseases and those receiving immunosup- pressive or immunomodulating therapies. This study aimed to investigate the severity of COVID-19 infection in patients with psoriasis and compare the infection severity for sys- temic treatments and comorbidities. We conducted a study in the dermatology clinics of five different centers in the Eastern Black Sea region of Turkey. Four hundred and eighty-eight patients were included, and 22.5% were confirmed as having COVID-19 infection. In our study, the frequency of hospitalization rates due to COVID-19 infection were similar (15.4%, 25.9% respectively) in patients receiv- ing biological treatment and receiving non-biological systemic treat- ment (P=0.344). Hospitalization rates were higher in patients with hypertension, androgenetic alopecia, and acitretin use (P=0.043, P=0.028, P=0.040). In conclusion, current biologic treatments and non-biologic system- ic treatments in patients with psoriasis did not appear to increase the risk of the severe form of COVID-19, except for acitretin

Incidence and Prognosis of COVID-19 in Patients with Psoriasis: A Multicenter Prospective Study from the Eastern Black Sea Region of Turkey

COVID-19 infection can have a poor prognosis, especial- ly in patients with chronic diseases and those receiving immunosup- pressive or immunomodulating therapies. This study aimed to investigate the severity of COVID-19 infection in patients with psoriasis and compare the infection severity for sys- temic treatments and comorbidities. We conducted a study in the dermatology clinics of five different centers in the Eastern Black Sea region of Turkey. Four hundred and eighty-eight patients were included, and 22.5% were confirmed as having COVID-19 infection. In our study, the frequency of hospitalization rates due to COVID-19 infection were similar (15.4%, 25.9% respectively) in patients receiv- ing biological treatment and receiving non-biological systemic treat- ment (P=0.344). Hospitalization rates were higher in patients with hypertension, androgenetic alopecia, and acitretin use (P=0.043, P=0.028, P=0.040). In conclusion, current biologic treatments and non-biologic system- ic treatments in patients with psoriasis did not appear to increase the risk of the severe form of COVID-19, except for acitretin

Contemporary Challenges and Solutions

CA18131 CP16/00163 NIS-3317 NIS-3318 decision 295741 C18/BM/12585940The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 “ML4Microbiome” that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.publishersversionpublishe

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies

Combined simulation-optimization of a coastal aquifer by using Genetic Algorithm

Excessive pumping in coastal aquifers results in seawater intrusion where optimal and efficient planning is essential. In this study, numerical solution of single potential solution by Strack (1976) is combined with Genetic Algorithm (GA) to optimize the maximum benefit in a coastal aquifer. Injection wells are added as an artificial recharge to prevent seawater intrusion. The objective is to optimize both pumping rates and locations of injection wells. The model is applied to a previous work by Mantoglou (2003). Two different methods are utilized. First locations and discharge values are optimized, simultaneously. Then, a three-step GA method is introduced where discharge rates and locations are optimized, in an iterative manner

Phosphorus and humic acid application alleviate salinity stress of pepper seedling

WOS: 000281680400011Humic acid is a commercial product that contains many elements which improve the soil fertility and increase the availability of nutrient elements. It consequently affects plant growth and yield and ameliorates the deleterious effects of salt stress. The objective of the study was to determine the effect of humic acids and phosphorus on growth and nutrient content of pepper seedlings (cv. Demre) grown under moderate salt stress in growth chamber conditions. Applications of different levels of phosphorus [0 (P(0)), 50 (P(1)), 100 (P(2)) and 150 (P(3)) mg kg(-1)] and humic acid [0 (HA(0)), 750 (HA(1)) and 1500 (HA(2)) mg kg(-1)] to growing media containing moderate salt dose (8 mM NaCl treatment) were studied. The study was replicated four times with 20 plants in each replicate. Humic acid (HA) and phosphorus applications increased the growth and growth parameter of plants. In company, effects of HA and P application was more effective on growth and growth parameter than each separate effect. The optimum total yield was obtained from 69 mg kg(-1) P application with HA2 doses according to regression analysis. Humic acid application significantly increased N, P, K, Ca, Mg, S, Mn and Cu contents of shoot of pepper seedling. Also, N, P, K, Ca, S, Fe, Mn, Zn and Cu contents of root were increased with humic acid application. Na contents of both shoot and root of pepper decreased with increased humic acid doses. It can be concluded that high humic acid doses has positive effects on salt tolerance based on the plant growth parameters and nutrient contents. The present study suggests that HA treatments can ameliorate the deleterious effects of salt stress on pepper plants and HA could offer an economical and simple application to reduce problems of pepper production in moderately saline soil

Tarsal plate: Protective Structure Peculiar to Buzzard's (Buteo buteo) Palpebra Inferioris

WOS: 000285216200017The study was carried out to investigate the effects of some external egg traits on hatchability using classification tree mRapid increase in human population leads to frequent contact with wild animals. Recently, the number of wild animals brought to the clinic of Faculty of Veterinary Medicine increased in consequence of illegal hunting, injury and road accident. In the present study, 16 palpebra inferiores of 8 buzzards (Buteo buteo) were investigated by subgros and histological methods. Palpebra inferioris responsible of covering cornea was longer than superior palpebra and supported with a dense connective tissue structure called tarsal plate. Tarsal plate in the buzzard has a strong structure and suitable form to protect eye. This strong tarsal plate should be kept in mind during surgical approach of inferior palpebra.Project Menagement Office of Ondokuz Mayis UniversityOndokuz Mayis University [PYO. VET.1901.09.007]This study has been supported by Project Menagement Office of Ondokuz Mayis University (Project No: PYO. VET.1901.09.007

Skin thickness on bony prominences measured by ultrasonography in patients with spinal cord injury

Objective: The detailed assessment of soft tissues over bony prominences and identification of methods of predicting pressure sores would improve the quality of care for patients with spinal cord injury (SCI). Comparing skin thicknesses on bony prominences in patients with SCI to those in healthy individuals will represent, to our knowledge, the first study aimed at determining whether differences in skin thicknesses between these groups can be detected by ultrasound