The Brain-Gut Axis, an Important Player in Alzheimer and Parkinson Disease: A Narrative Review.

Neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), are severe age-related disorders with complex and multifactorial causes. Recent research suggests a critical link between neurodegeneration and the gut microbiome, via the gut-brain communication pathway. This review examines the role of trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, in the development of AD and PD, and investigates its interaction with microRNAs (miRNAs) along this bidirectional pathway.

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

Objectives: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power and sensitivity. Deep learning-based AI relies on training data sets, which should be sufficiently large and diverse to effectively adjust network parameters, avoid biases, and enable generalization of the outcome. However, large sets of diagnostic images acquired at doses of CA outside the standard-of-care are not commonly available.

PCR cloning of partial nbs sequences from grape (Vitis aestivalis Michx).

Plants defend themselves against pathogens via the expressions of disease resistance (R) genes. Many plant R gene products contain the characteristic nucleotide-binding site (NBS) and leucine-rich repeat (LRR) domains. There are highly conserved motifs within the NBS domain which could be targeted for polymerase chain reaction (PCR) cloning of R genes.

New, improved, and practical k-stem sequence similarity measures for probe design.

We define new measures of sequence similarity for oligonucleotide probe design. These new measures incorporate the nearest neighbor k-stem motifs in their definition, but can be efficiently computed by means of a bit-vector method. They are not as computationally costly as algorithms that predict nearest neighbor hybridization potential.

Free energy gap and statistical thermodynamic fidelity of DNA codes.

DNA nanotechnology often requires collections of oligonucleotides called "DNA free energy gap codes" that do not produce erroneous crosshybridizations in a competitive muliplexing environment. This paper addresses the question of how to design these codes to accomplish a desired amount of work within an acceptable error rate. Using a statistical thermodynamic and probabilistic model of DNA code fidelity and mathematical random coding theory methods, theoretical lower bounds on the size of DNA codes are given.

Group testing to annihilate pairs applied to DNA cross-hybridization elimination using SYBR Green I.

A group testing (or pooling) method for DNA strands that identifies at least one strand in a pair of cross-hybridized oligonucleotides is given. This pooling method can be extended to any population of objects where certain pairs together produce an observable function or signal. Pairs of objects may work together to produce an undesirable result or a detrimental function.

Network structure, and vaccination strategy and effort interact to affect the dynamics of influenza epidemics.

There is growing interest in understanding and controlling the spread of diseases through realistically structured host populations. We investigate how network structures, ranging from circulant, through small-world networks, to random networks, and vaccination strategy and effort interact to influence the proportion of the population infected, the size and timing of the epidemic peak, and the duration of the epidemic. We found these three factors, and their higher-order interactions, significantly influenced epidemic development and extent.

New t-gap insertion-deletion-like metrics for DNA hybridization thermodynamic modeling.

We discuss the concept of t-gap block isomorphic subsequences and use it to describe new abstract string metrics that are similar to the Levenshtein insertion-deletion metric. Some of the metrics that we define can be used to model a thermodynamic distance function on single-stranded DNA sequences. Our model captures a key aspect of the nearest neighbor thermodynamic model for hybridized DNA duplexes.

A construction of pooling designs with some happy surprises.

The screening of data sets for "positive data objects" is essential to modern technology. A (group) test that indicates whether a positive data object is in a specific subset or pool of the dataset can greatly facilitate the identification of all the positive data objects. A collection of tested pools is called a pooling design.

Preliminary implementation of new data mining techniques for the analysis of simulation data from Genetic Analysis Workshop 12: problem 2.

We introduce a new data mining method applicable to complex disease genetics. Our approach is suited to a broad spectrum of diseases, identifying the noteworthy sharing of combinations of alleles in unrelated affected individuals. Furthermore, this approach may be extended to comprise the common types of genotype data, including single-nucleotide polymorphisms, candidate-gene sequences, etc.