Predicting Parkinson’s Disease Related Genes Based on PyFeat and Gradient Boosted Decision Tree (GBDT)

Identifying genes related to Parkinson's disease (PD) is an active and effective research topic in biomedical analysis, which plays a critical role in diagnosis and treatment. In recent years, many studies have proposed different techniques for predicting disease-related genes. However, a few of these techniques are designed or developed for PD gene prediction. Most of these PD techniques are developed to identify only protein genes and discard long non-coding (lncRNA) genes, which play an essential role in biological processes and the Transformation and development of diseases. This paper proposes a novel prediction system to identify protein and lncRNA genes related to PD that can aid in an early diagnosis. First, we preprocessed the genes into DNA FASTA sequences from the UCSC genome browser and removed the redundancies. Second, we extracted some significant features of DNA FASTA sequences using five numerical mapping techniques with Fourier transform and PyFeat method with Adaboost technique as feature selection. Finally, the features were fed to the gradient boosted decision tree (GBDT) to diagnose different tested cases. Seven performance metrics are used to evaluate the performance of the proposed system. The proposed system achieved an average accuracy (ACC) equals 78.1%, the area under the curve (AUC) equals 84.9%, the area under precision-recall (AUPR) equals 85.0%, F1-score equals 78.2%, Matthews correlation coefficient (MCC) equals 0.564, Sensitivity (SEN) equals 79.1%, and specificity (SPC) equals 77.1%. The experiments demonstrate promising results compared with other systems. The predicted top-rank protein and lncRNA genes are verified based on a literature review.

Technology for Formation of Hybrid Microfluidic Biosensor Systems for Label-Free Fluorimetric Express Detection of Protein Structures based on Molecular Recognition

The development and comparative study of technologies for manufacturing elements of hybrid biosensor systems intended for express biomedical analysis has been carried out. The technological process included the formation of the relief of microfluidic channels, chemical modification of their working surface, deposition of solid-state phosphor layers, sealing of the system, installation of inlet ports and packaging.

Alpha-diversity and microbial community structure of the male urinary microbiota depend on urine sampling method

Considerable variation exists in the methodology of urinary microbiota studies published so far including the cornerstone of any biomedical analysis: sample collection. The aim of this study was to compare the urinary microbiota of first-catch voided urine (FCU), mid-stream voided urine (MSU) and aseptically catheterised urine in men and define the most suitable urine sampling method. Forty-nine men (mean age 71.3 years) undergoing endoscopic urological procedures were enrolled in the study. Each of them contributed three samples: first-catch urine (FCU), mid-stream urine (MSU) and a catheterised urine sample. The samples were subjected to next-generation sequencing (NGS, n = 35) and expanded quantitative urine culture (EQUC, n = 31). Using NGS, Bacteroidetes, Firmicutes, and Proteobacteria were the most abundant phyla in our population. The most abundant genera (in order of relative abundance) included: Prevotella, Veillonella, Streptococcus, Porphyromonas, Campylobacter, Pseudomonas, Staphylococcus, Ezakiella, Escherichia and Dialister. Eighty-two of 105 samples were dominated by a single genus. FCU, MSU and catheterised urine samples differed significantly in three of five alpha-diversity measures (ANOVA, p < 0.05): estimated number of operational taxonomic units, Chao1 and abundance-based coverage estimators. Beta-diversity comparisons using the PIME method (Prevalence Interval for Microbiome Evaluation) resulted in clustering of urine samples according to the mode of sampling. EQUC detected cultivable bacteria in 30/31 (97%) FCU and 27/31 (87%) MSU samples. Only 4/31 (13%) of catheterised urine samples showed bacterial growth. Urine samples obtained by transurethral catheterisation under aseptic conditions seem to differ from spontaneously voided urine samples. Whether the added value of a more exact reflection of the bladder microbiota free from urethral contamination outweighs the invasiveness of urethral catheterisation remains to be determined.

Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption

Using real-world evidence in biomedical research, an indispensable complement to clinical trials, requires access to large quantities of patient data that are typically held separately by multiple healthcare institutions. We propose FAMHE, a novel federated analytics system that, based on multiparty homomorphic encryption (MHE), enables privacy-preserving analyses of distributed datasets by yielding highly accurate results without revealing any intermediate data. We demonstrate the applicability of FAMHE to essential biomedical analysis tasks, including Kaplan-Meier survival analysis in oncology and genome-wide association studies in medical genetics. Using our system, we accurately and efficiently reproduce two published centralized studies in a federated setting, enabling biomedical insights that are not possible from individual institutions alone. Our work represents a necessary key step towards overcoming the privacy hurdle in enabling multi-centric scientific collaborations.

Designing a Multiaxial Extensometric Force Platform: A Manufacturing Experience

Studies that lead to the development of more accessible and low-cost electronic technologies and devices for biomechanical and biomedical analysis applications are becoming increasingly needed. In this work, the development of a multiaxial extensometric force platform will be addressed, aiming to improve the sensitivity and reduce the costs of existing platforms. Additionally, this platform can be used for analysis and characterization of flight time and postural characterization of volleyball athletes. As a result, a functional and easily produced prototype was created, due to the processes used (final cost of the developed platform—USD$100). The interfaces of visualization and analysis of the device functions were designed in LabView. The purpose of the experiments is to perform flight analysis of athletes, and all functions designed for the platform strength and endurance are focused on that same purpose. The prototype’s functions were evaluated by applying loads from 700 to 1000 N (Newtons) and its future integration with other instruments such as the surface electromyography (EMG) and an electrocardiogram (ECG) is expected to form an instrument kit that improves the characterization of studies of balance, strength and muscular endurance.