scholarly journals Hormone Imbalance

2020 ◽  
Author(s):  
Keyword(s):  
Author(s):  
F. Al-Bagdadi ◽  
D. Hoyt ◽  
P. Karns ◽  
G. Martin ◽  
M. Memon ◽  
...  

The most frequently occuring abnormality of the male genital system in mammals is the failure of one or both testes to descend into the scrotum. The reasons for abdominal or inguinal retention of testes could be anatomic malformation, faulty development or hormone imbalance.Cryptorchidism has been associated with either greatly reduced or absent spermatogenesis (Kaueakami et al, 1984), and being a source of neoplasia. According to Stick (1980), germinal carcinoma cells have been believed to be the cause of teratomas in equine cryptorchid testicles. Neoplasia has been reported in descended testes of unilateral cryptorchid patients (Martin et al, 1981).No distinction has been made in relating the problem of cryptorchid testes to inguinal or abdominal retention. The purpose of this study is to record the morphological differences between inguinal and abdominal cryptorchid testes as an aid in diagnosis and prognosis.


Inflammation ◽  
2018 ◽  
Vol 41 (4) ◽  
pp. 1384-1395 ◽  
Author(s):  
Yang Su ◽  
Jingxiao Lu ◽  
Xianguo Chen ◽  
Chaozhao Liang ◽  
Pengcheng Luo ◽  
...  

2019 ◽  
Vol 8 (4) ◽  
pp. 7396-7399

PCOS is an endocrine disorder which occurs due to hormone imbalance. PCOS may leads to infertility, diabetes mellitus and cardiovascular diseases. It may be identified by physical appearance, ultrasound scanning and clinical trials. The PCOS ovary can be identified as the follicles which are arranged peripherally and measuring 2-9mm of size. The dataset used in this paper consists of 119 samples with 17 features which represents the physical appearance and psychological characteristics such as stress, exercising methods, eating habits, etc. The classification algorithms can be applied on these data to predict the present of PCOS. The aim of the paper is to compare the accuracy of the classification model and find the algorithm which best suites for the dataset in predicting the occurrence of PCOS


2019 ◽  
Vol 8 (S1) ◽  
pp. S45-S57 ◽  
Author(s):  
Yvonne Konkol ◽  
Heikki Vuorikoski ◽  
Tomi Streng ◽  
Johanna Tuomela ◽  
Jenni Bernoulli

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