Decoding degeneration:the implementation of machine learning for clinical detection of neurodegenerative disorders

Machine learning represents a growing subfield of artificial intelligence with much promise in the diagnosis,treatment,and tracking of complex conditions,including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases.While no definitive methods of diagnosis or treatment exist for either disease,researchers have implemented machine learning algorithms with neuroimaging and motion-tracking technology to analyze pathologically relevant symptoms and biomarkers.Deep learning algorithms such as neural networks and complex combined architectures have proven capable of tracking disease-linked changes in brain structure and physiology as well as patient motor and cognitive symptoms and responses to treatment.However,such techniques require further development aimed at improving transparency,adaptability,and reproducibility.In this review,we provide an overview of existing neuroimaging technologies and supervised and unsupervised machine learning techniques with their current applications in the context of Alzheimer’s and Parkinson’s diseases.

The clinical significance of detection of specific CK-20 mRNA in peripheral venous blood from patients with bladder carcinoma

Objective To determine the diagnostic significance of detecting the specific epithelial keratin CK-20 mRNA in peripheral venous blood from patients with bladder carcinomas. Methods Reverse transcription coupled with two-step polymerase chain reaction (nested RT-PCR) was used to detect CK-20 mRNA expression in the peripheral blood from patients with blodder carcinomas. Results Detection of CK-20 mRNA expression was positive in 37 of 91 patients with bladder carcinoma (41 % ). Among 20 patients with distant metastasis, 17 were positive (85 % ). CK-20 mRNA was not detectable in the blood samples from 25 normal individuals. The frequency of positive CK-20 mRNA expression was signficantly higher in those with distant metastasis. Conclusion The presence of CK-20 mRNA expression in peripheral blood may be used as an early indicator of hematogenous metastasis of bladder carcinoma cells. 6 refs,1 tab.

Nanotechnology-based Detection Strategies for Hypertension Biomarkers

Hypertension significantly increases the risk of cardiovascular diseases and seriously affects people’s health.The incidence of hypertension is rising rapidly in the world and hypertension has become a significant factor influencing the global average life expectancy.The diagnosis of hypertension is generally fulfilled by measuring diastolic and systolic blood pressure,but it is insufficient to differentiate essential hypertension from secondary hypertension,so it is crucial to identifying the cause of hypertension by detecting biomarkers in plasma.In clinical practice,five plasma biomarkers are utilized for diagnosing hypertension,and the detection tasks of a large number of cases have raised increasing demands for cost-effective,efficient,speedy,and diverse methods,which makes many traditional diagnostic technologies inadequate for meeting the needs of clinical diagnosis.The nanomaterial-based detection techniques have frequently attained the qualities of quick reaction,low cost,straightforward operation,high sensitivity,and strong specificity in recent years with the advancement of nanotechnology,so they have great potential for early and rapid diagnosis.In this review,we will introduce the characteristics and drawbacks of current clinical detection methods for hypertension screening,the principles and advancements of nanotechnology-based detection methods,as well as their potentials for clinical application.

Rapid detection of Mycoplasma Pneumoniae in Clinical Samples by the Polymerase Chain Reaction Technique.

The polymerase chain reaction (PCR) technique was used to detect mycoplasma pneumoniae in clinical samples