Machine Learning-Enhanced SERS for Accurate Azoospermia Diagnosis via Seminal Plasma Exosome Analysis DOI Creative Commons
Zufang Huang, Shiyan Jiang, Jiaxin Shi

и другие.

Journal of Innovative Optical Health Sciences, Год журнала: 2024, Номер unknown

Опубликована: Окт. 30, 2024

Male infertility affects 10–15% of couples globally, with azoospermia — complete absence sperm accounting for 15% cases. Traditional diagnostic methods are subjective and variable. This study presents a novel, noninvasive, accurate method using surface-enhanced Raman spectroscopy (SERS) combined machine learning to analyze seminal plasma exosomes. Semen samples from healthy controls ([Formula: see text]) azoospermic patients were collected, their exosomal SERS spectra obtained. Machine algorithms employed distinguish between the profiles samples, achieving an impressive sensitivity 99.61% specificity 99.58%, thereby highlighting significant spectral differences. integrated approach offers sensitive, label-free, objective tool early detection monitoring azoospermia, potentially enhancing clinical outcomes patient management.

Язык: Английский

Detrimental effects of cadmium on male infertility: A review DOI Creative Commons
N. Zečević,

Jovana Kocić,

Milan Perović

и другие.

Ecotoxicology and Environmental Safety, Год журнала: 2024, Номер 290, С. 117623 - 117623

Опубликована: Дек. 28, 2024

Язык: Английский

Процитировано

2
Diseases of the Prostate DOI

Felix Uchenna Samuel,

Ogunkunle Nathaniel,

Kolawole Jonathan Bamidele

и другие.

Опубликована: Авг. 9, 2024

The prostate gland is an accessory sex organ found in male goats and other mammals. essential reproductive goats, playing a vital role semen production fertility. However, like all living organisms, are susceptible to various diseases that can affect the compromise their health. Some of affecting include prostatitis, benign prostatic hyperplasia (BPH), abscess, cancer. Prostate pathology could result decreased reproduction sperm cell health as it impair capitation fertilization potential.

Язык: Английский

Процитировано

0
Use of Volumetric Apparent Diffusion Coefficient to Distinguish Between Obstructive and Non-obstructive Azoospermia: A Case-control Study DOI Open Access

Mahyar Ghafoori,

Maryam Moaddab,

Farzam Mahmoodi

и другие.

Bakirkoy Tip Dergisi / Medical Journal of Bakirkoy, Год журнала: 2024, Номер unknown, С. 225 - 231

Опубликована: Сен. 18, 2024

Язык: Английский

Процитировано

0
Machine Learning-Enhanced SERS for Accurate Azoospermia Diagnosis via Seminal Plasma Exosome Analysis DOI Creative Commons
Zufang Huang, Shiyan Jiang, Jiaxin Shi

и другие.

Journal of Innovative Optical Health Sciences, Год журнала: 2024, Номер unknown

Опубликована: Окт. 30, 2024

Male infertility affects 10–15% of couples globally, with azoospermia — complete absence sperm accounting for 15% cases. Traditional diagnostic methods are subjective and variable. This study presents a novel, noninvasive, accurate method using surface-enhanced Raman spectroscopy (SERS) combined machine learning to analyze seminal plasma exosomes. Semen samples from healthy controls ([Formula: see text]) azoospermic patients were collected, their exosomal SERS spectra obtained. Machine algorithms employed distinguish between the profiles samples, achieving an impressive sensitivity 99.61% specificity 99.58%, thereby highlighting significant spectral differences. integrated approach offers sensitive, label-free, objective tool early detection monitoring azoospermia, potentially enhancing clinical outcomes patient management.

Язык: Английский

Процитировано

0