Telemedicine in French Memory Clinics During the COVID-19 Pandemic

This multicenter study was conducted in French memory clinics during the first COVID-2019 lockdown (March–May 2020). The objective was to evaluate the effect of a telemedicine consultation on treatment modification in dementia care. Among 874 patients who had a telemedicine consultation, 103 (10.7%) had treatment modifications, in particular those living with a relative or diagnosed with Alzheimer’s disease. A control group of patients referred March–May 2019 was also included. Treatment modification rate was similar between periods with an adjusted percentage difference of –4% (p = 0.27). Telemedicine consultations allowed treatment modifications with only a minor short-term negative impact on therapeutic strategies.

A binary ABC algorithm based on advanced similarity scheme for feature selection

© 2015 Elsevier B.V. All rights reserved. Feature selection is the basic pre-processing task of eliminating irrelevant or redundant features through investigating complicated interactions among features in a feature set. Due to its critical role in classification and computational time, it has attracted researchers' attention for the last five decades. However, it still remains a challenge. This paper proposes a binary artificial bee colony (ABC) algorithm for the feature selection problems, which is developed by integrating evolutionary based similarity search mechanisms into an existing binary ABC variant. The performance analysis of the proposed algorithm is demonstrated by comparing it with some well-known variants of the particle swarm optimization (PSO) and ABC algorithms, including standard binary PSO, new velocity based binary PSO, quantum inspired binary PSO, discrete ABC, modification rate based ABC, angle modulated ABC, and genetic algorithms on 10 benchmark datasets. The results show that the proposed algorithm can obtain higher classification performance in both training and test sets, and can eliminate irrelevant and redundant features more effectively than the other approaches. Note that all the algorithms used in this paper except for standard binary PSO and GA are employed for the first time in feature selection.

A binary ABC algorithm based on advanced similarity scheme for feature selection

© 2015 Elsevier B.V. All rights reserved. Feature selection is the basic pre-processing task of eliminating irrelevant or redundant features through investigating complicated interactions among features in a feature set. Due to its critical role in classification and computational time, it has attracted researchers' attention for the last five decades. However, it still remains a challenge. This paper proposes a binary artificial bee colony (ABC) algorithm for the feature selection problems, which is developed by integrating evolutionary based similarity search mechanisms into an existing binary ABC variant. The performance analysis of the proposed algorithm is demonstrated by comparing it with some well-known variants of the particle swarm optimization (PSO) and ABC algorithms, including standard binary PSO, new velocity based binary PSO, quantum inspired binary PSO, discrete ABC, modification rate based ABC, angle modulated ABC, and genetic algorithms on 10 benchmark datasets. The results show that the proposed algorithm can obtain higher classification performance in both training and test sets, and can eliminate irrelevant and redundant features more effectively than the other approaches. Note that all the algorithms used in this paper except for standard binary PSO and GA are employed for the first time in feature selection.

Bioresorbable Composites and Implant

Different biomaterials in the form of ceramics, metal alloys, composites, glasses, polymers, etc. have gained wide-range acceptance in the realm of medical sciences. Bioimplants from such biomaterials have been constructed and used widely for different clinical applications. With the continual progress, biomaterials that may be resorbed inside the body have been developed. These have done away with the major challenge of removal of an implant after it has served its intended function. Important factors are taken into consideration in design and development of implants from such biomaterials are mechanical properties, degradation rate, surface modification, rate of corrosion, biocompatibility, and non-toxicity. Given the importance of such materials in clinical applications, the chapter presents an overview of the bioresorable composites and their implants. The related properties and the functions served have been outlined briefly. Further, the challenges associated and the remedies to overcome them have also been delineated.

CIGAR-seq, a CRISPR/Cas-based method for unbiased screening of novel mRNA modification regulators

Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6A and m5C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high-throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR-seq). Using CIGAR-seq, we discovered NSUN6 as a novel mRNA m5C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non-overlapping subsets of mRNA m5C sites, and together contributed to almost all the m5C modification in mRNA. Finally, using m1A as an example, we demonstrated that CIGAR-seq can be easily adapted for identifying regulators of other mRNA modification.

Detection of differential RNA modifications from direct RNA sequencing of human cell lines

Differences in RNA expression can provide insights into the molecular identity of a cell, pathways involved in human diseases, and variation in RNA levels across patients associated with clinical phenotypes. RNA modifications such as m6A have been found to contribute to molecular functions of RNAs. However, quantification of differences in RNA modifications has been challenging. Here we develop a computational method (xPore) to identify differential RNA modifications from direct RNA sequencing data. We evaluate our method on transcriptome-wide m6A profiling data, demonstrating that xPore identifies positions of m6A sites at single base resolution, estimates the fraction of modified RNAs in the cell, and quantifies the differential modification rate across conditions. We apply the method to direct RNA-Sequencing data from 6 cell lines and find that many m6A sites are preserved, while a subset of m6A sites show significant differences in their modification rates across cell types. Together, we show that RNA modifications can be identified from direct RNA-sequencing with high accuracy, enabling the analysis of differential modifications and expression from a single high throughput experiment.AvailabilityxPore is available as open source software (https://github.com/GoekeLab/xpore)

An improved ACS algorithm for data clustering

<span lang="EN-GB">Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. Each object in every cluster exhibits sufficient similarity to its neighbourhood, whereas objects with insufficient similarity are found in other clusters. Data clustering techniques minimise intra-cluster similarity in each cluster and maximise inter-cluster dissimilarity amongst different clusters. Ant colony optimisation for clustering (ACOC) is a swarm algorithm inspired by the foraging behaviour of ants. This algorithm minimises deterministic imperfections in which clustering is considered an optimisation problem. However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms. </span>

Effect of Uneven Electrostatic Forces on the Dynamic Characteristics of Capacitive Hemispherical Resonator Gyroscopes

The hemispherical resonator gyroscope (HRG) is a typical capacitive Coriolis vibratory gyroscope whose performance is inevitably influenced by the uneven electrostatic forces caused by the uneven excitation capacitance gap between the resonator and outer base. First, the mechanism of uneven electrostatic forces due to the significantly uneven capacitance gap in that the non-uniformity of the electrostatic forces can cause irregular deformation of the resonator and further affect the performance and precision of the HRG, was analyzed. According to the analyzed influence mechanism, the dynamic output error model of the HRG was established. In this work, the effect of the first four harmonics of the uneven capacitance gap on the HRG was investigated. It turns out that the zero bias and output error, caused by the first harmonic that dominates mainly the amplitude of the uneven capacitance gap, increase approximately linearly with the increase of the amplitude, and periodically vary with the increase of the phase. The effect of the other three harmonics follows the same law, but their amplitudes are one order of magnitude smaller than that of the first one, thus their effects on the HRG can be neglected. The effect of uneven electrostatic forces caused by the first harmonic on the scale factor is that its nonlinearity increases approximately linearly with the increase of the harmonic amplitude, which was analyzed in depth. Considering comprehensively the zero bias, the modification rate of output error, and scale factor nonlinearity, the tolerance towards the uneven excitation capacitance gap was obtained.

The microenvironment surrounding FAD mediates its conversion to 8-formyl-FAD in Aspergillus oryzae RIB40 formate oxidase

Aspergillus oryzae RIB40 formate oxidase has Arg87 and Arg554 near the formyl group and O(4) atom of 8-formyl-flavin adenine dinucleotide (FAD), respectively, with Asp396 neighbouring Arg554. Herein, we probed the roles of these three residues in modification of FAD to 8-formyl-FAD. Replacement of Arg87 or Arg554 with Lys or Ala decreased and abolished the modification, respectively. Replacement of Asp396 with Ala or Asn lowered the modification rate. The observation of unusual effects of maintaining pH 7.0 on the modification in R87K, R554K and D396 variants indicates initial and subsequent processes with different pH dependencies. Comparison of the initial process at pH 4.5 and 7.0 suggests that the microenvironment around Arg87 and the protonation state of Asp396 affect the initial process in the native enzyme. Comparison of the crystal structures of native and R554 variants showed that the replacements had minimal effect on catalytic site structure. The positively charged Arg87 might contribute to the formation of an anionic quinone-methide tautomer intermediate, while the positively charged Arg554, in collaboration with the negatively charged Asp396, might stabilize this intermediate and form a hydrogen bonding network with the N(5)/O(4) region, thereby facilitating efficient FAD modification.