Examination of semen characteristics is routinely performed for fertility status investigation of the male partner of an infertile couple as well as for evaluation of the sperm donor candidate. A useful tool for preliminary assessment of semen characteristics might be an artificial neural network. Thus, the aim of the present study was to construct an artificial neural network, which could be used for predicting the result of semen analysis based on the basic questionnaire data.On the basis of eleven survey questions two models of artificial neural networks to predict semen parameters were developed. The first model aims to predict the overall performance and profile of semen. The second network was developed to predict the concentration of sperm.The network to evaluate sperm concentration proved to be the most efficient. 92.93% of the patients in the learning process were properly qualified for the group with a correct or incorrect result, while the result for the test set was 85.71%. This study suggests that an artificial neural network based on eleven survey questions might be a valuable tool for preliminary evaluation and prediction of the semen profile.
Highlights:• We build two models of ANNs to predict (1) the overall performance and quality of semen, and (2) the concentration of sperm. • Evaluation of semen quality and sperm parameters might be performed on the basis of eleven survey questions. • Both models of ANNs are characterized by high values of evaluation indicators of effectiveness of the method.Original research article oligoasthenoteratozoospermia (WHO, 2010). Seminal characteristics might be affected by several factors, including age, weight, psychological stress, environmental and occupational factors (e.g. air pollution, heavy metals), or a certain lifestyle (e.g. recreational and prescription substances, exercise)
Lung cancer is the leading cause of death worldwide among men and women. Tobacco smoking is the number one risk factor for lung cancer. The aim of our study was to evaluate the survivability of patients with single lung cancer in relation to the survival time in patients with multiple neoplasms whose last neoplasm was a lung cancer. A retrospective analysis was con-ducted of data from medical histories of patients hospitalized at the Pulmonary Hospital in Olsztyn (Poland) from 2012 to 2017, with a lung cancer diagnosis as the first or subsequent cancer. The total longevity of women with diagnosed multiple cancers was found to be shorter than that of men: 67.60 years (SD: 7.77) and 69.91 years (SD: 7.97), respectively. Among the ex-smokers, the longevity of men (68.93 years) was longer than that of women (66.18 years). Survival time, counted from the diagnosis of both the first and subsequent cancer, was longer among patients with multiple cancers than among patients with single lung cancer (p = 0.000). Women’s survivability was worse than men’s in the case of multiple cancers and in the group of people who quit smoking (p = 0.037; p = 0.000). To conclude, smoking tobacco affects the survival of patients with lung cancer. Smoking cessation improves overall survival.
The essential oil of celery (Apium graveolens) is characterized by exceptionally high content of alkylphthalides. The mentioned compounds exhibit a number of biological effects (including hypotensive, lipid-lowering, neuroprotective, and cytotoxic) and are also responsible for distinctive aroma of the plant. In the current work, parameters of conventional hydrodistillation (HD) and simultaneous distillation-extraction (SDE) were optimized to obtain phthalide-enriched fractions of celery seeds. A positive correlation was shown between hydrodistillation time and improved essential oil and phthalide yields. The 6-h HD of comminuted seeds yielded essential oil (2.9%) with a higher total phthalide content (51%), as compared to the samples collected after 1.5-3.0 h, which gave 2.4-2.7% of oil containing 24.6-39.2% of total phthalides. The oil contained sedanenolide (36.7%), 3-n-butylphthalide (13.1%), and sedanolide (1.1%). A further increase in the total phthalide content was achieved by omitting the size reduction step prior to hydrodistillation (68.8%) and utilization of the salting-out effect (84.3%). Enzyme pretreatment had a negligible effect on essential oil and phthalide yields. The change of distillation mode from HD to SDE significantly increased the oil yield of whole seeds (from 2.8 to 5.8% for 6 h processing) while maintaining its high phthalide content (62.5%), which translated to an increase in the total phthalide yield from 19.4 to 36.0 g/kg.
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