Literature-Based Discovery Predicts Antihistamines Are a Promising Repurposed Adjuvant Therapy for Parkinson's Disease.

Parkinson's disease (PD) is a movement disorder caused by a dopamine deficit in the brain. Current therapies primarily focus on dopamine modulators or replacements, such as levodopa. Although dopamine replacement can help alleviate PD symptoms, therapies targeting the underlying neurodegenerative process are limited. The study objective was to use artificial intelligence to rank the most promising repurposed drug candidates for PD. Natural language processing (NLP) techniques were used to extract text relationships from 33+ million biomedical journal articles from PubMed and map relationships between genes, proteins, drugs, diseases, etc., into a knowledge graph. Cross-domain text mining, hub network analysis, and unsupervised learning rank aggregation were performed in SemNet 2.0 to predict the most relevant drug candidates to levodopa and PD using relevance-based HeteSim scores. The top predicted adjuvant PD therapies included ebastine, an antihistamine for perennial allergic rhinitis; levocetirizine, another antihistamine; vancomycin, a powerful antibiotic; captopril, an angiotensin-converting enzyme (ACE) inhibitor; and neramexane, an N-methyl-D-aspartate (NMDA) receptor agonist. Cross-domain text mining predicted that antihistamines exhibit the capacity to synergistically alleviate Parkinsonian symptoms when used with dopamine modulators like levodopa or levodopa-carbidopa. The relationship patterns among the identified adjuvant candidates suggest that the likely therapeutic mechanism(s) of action of antihistamines for combatting the multi-factorial PD pathology include counteracting oxidative stress, amending the balance of neurotransmitters, and decreasing the proliferation of inflammatory mediators. Finally, cross-domain text mining interestingly predicted a strong relationship between PD and liver disease.

Polysynthetic twinned TiAl single crystals for high-temperature applications.

TiAl alloys are lightweight, show decent corrosion resistance and have good mechanical properties at elevated temperatures, making them appealing for high-temperature applications. However, polysynthetic twinned TiAl single crystals fabricated by crystal-seeding methods face substantial challenges, and their service temperatures cannot be raised further. Here we report that Ti-45Al-8Nb single crystals with controlled lamellar orientations can be fabricated by directional solidification without the use of complex seeding methods. Samples with 0° lamellar orientation exhibit an average room temperature tensile ductility of 6.9% and a yield strength of 708 MPa, with a failure strength of 978 MPa due to the formation of extensive nanotwins during plastic deformation. At 900 °C yield strength remains high at 637 MPa, with 8.1% ductility and superior creep resistance. Thus, this TiAl single-crystal alloy could provide expanded opportunities for higher-temperature applications, such as in aeronautics and aerospace.

Objectively quantifying subjective phenomena: Measuring the flashed face distortion effect.

Objectively quantifying subjective phenomena like visual illusions is challenging. We address this issue in the context of the Flashed Face Distortion Effect (FFDE), where faces presented in succession appear distorted and grotesque. We first show that the traditional method of quantifying FFDE - via subjective ratings of the level of distortion - is subject to substantial biases. Motivated by this finding, we develop an objective method for quantifying FFDE by introducing two design innovations. First, we create artificially distorted faces and ask subjects to discriminate between undistorted and objectively distorted faces. Second, we employ both an illusion condition, which includes a succession of 15 face flashes, and a control condition, which includes a single face flash and does not induce an illusion. Using these innovations, we quantify the strength of the face distortion illusion by comparing the response bias for identifying distorted faces between the illusion and control conditions. We find that our method successfully quantifies the face distortion, with subjects exhibiting a more liberal response bias in the illusion condition. Finally, we apply our new method to evaluate how the face distortion illusion is modulated by face eccentricity, face inversion, the temporal frequency of the face flashes, and presence of temporal gaps between consecutive faces. Our results demonstrate the utility of our objective method in quantifying the subjective illusion of face distortion. Critically, the method is general and can be applied to other phenomena that are inherently subjective.

Serum metabolic signatures of four types of human arthritis.

Similar symptoms of the different types of arthritis have continued to confound the clinical diagnosis and represent a clinical dilemma making treatment choices with a more personalized or generalized approach. Here we report a mass spectrometry-based metabolic phenotyping study to identify the global metabolic defects associated with arthritis as well as metabolic signatures of four major types of arthritis--rheumatoid arthritis (n = 27), osteoarthritis (n = 27), ankylosing spondylitis (n = 27), and gout (n = 33)--compared with healthy control subjects (n = 60). A total of 196 metabolites were identified from serum samples using a combined gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF MS) and ultraperformance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-QTOF MS). A global metabolic profile is identified from all arthritic patients, suggesting that there are common metabolic defects resulting from joint inflammation and lesion. Meanwhile, differentially expressed serum metabolites are identified constituting an unique metabolic signature of each type of arthritis that can be used as biomarkers for diagnosis and patient stratification. The results highlight the applicability of metabonomic phenotyping as a novel diagnostic tool for arthritis complementary to existing clinical modalities.

Molecular Geometries and Vibrational Contributions to Reaction Thermochemistry Are Surprisingly Insensitive to the Choice of Basis Sets.

Calculation of molecular geometries and harmonic vibrational frequencies are pre-requisites for thermochemistry calculations. Contrary to conventional wisdom, this paper demonstrates that quantum chemical predictions of the thermochemistry of many gas and solution phase chemical reactions appear to be very insensitive to the choice of basis sets. For a large test set of 80 diverse organic and transition-metal-containing reactions, variations in reaction free energy based on geometries and frequencies calculated using a variety of double and triple-zeta basis sets from the Pople, Jensen, Ahlrichs, and Dunning families are typically less than 4 kJ mol-1, especially when the quasiharmonic oscillator correction is applied to mitigate the effects of low-frequency modes. Our analysis indicates that for many organic molecules and their transition states, high-level revDSD-PBEP86-D4 and DLPNO-CCSD(T)/(aug-)cc-pVTZ single-point energies usually vary by less than 2 kJ mol-1 on density functional theory geometries optimized using basis sets ranging from 6-31+G(d) to aug-pcseg-2 and aug-cc-pVTZ. In cases where these single-point energies vary significantly, indicating sensitivity of molecular geometries to the choice of basis set, there is often substantial cancellation of errors when the reaction energy or barrier is calculated. The study concludes that the choice of basis set for molecular geometry and frequencies, particularly those considered in this study, is not critical for the accuracy of thermochemistry calculations in the gas or solution phase.

Rheumatoid arthritis with deficiency pattern in traditional chinese medicine shows correlation with cold and hot patterns in gene expression profiles.

In our precious study, the correlation between cold and hot patterns in traditional Chinese medicine (TCM) and gene expression profiles in rheumatoid arthritis (RA) has been explored. Based on TCM theory, deficiency pattern is another key pattern diagnosis among RA patients, which leads to a specific treatment principle in clinical management. Therefore, a further analysis was performed aiming at exploring the characteristic gene expression profile of deficiency pattern and its correlation with cold and hot patterns in RA patients by bioinformatics analysis approach based on gene expression profiles data detected with microarray technology. The TCM deficiency pattern-related genes network comprises 7 significantly, highly connected regions which are mainly involved in protein transcription processes, protein ubiquitination, toll-like receptor activated NF- κ B regulated gene transcription and apoptosis, RNA clipping, NF- κ B signal, nucleotide metabolism-related apoptosis, and immune response processes. Toll-like receptor activated NF- κ B regulated gene transcription and apoptosis pathways are potential specific pathways related to TCM deficiency patterns in RA patients; TCM deficiency pattern is probably related to immune response. Network analysis can be used as a powerful tool for detecting the characteristic mechanism related to specific TCM pattern and the correlations between different patterns.

TiC nanoparticles-chitosan composite film for the direct electron transfer of myoglobin and its application in biosensing.

We report on the direct electrochemistry of myoglobin (Mb) immobilized on a composite matrix based on chitosan (CHIT) and titanium carbide nanoparticles (TiC NPs) underlying on glassy carbon electrode (GCE). The cyclic voltammetry and electrochemical impedance spectroscopy were used to characterize the modified electrode. In deaerated buffer solutions, the cyclic voltammetry of the composite films of Mb-TiC NPs-CHIT showed a pair of well-behaved redox peaks that are assigned to the redox reaction of Mb, confirming the effective immobilization of Mb on the composite film. The electron transfer rate constant was estimated to be 3.8 (±0.2)·s(-1), suggested that the interaction between the protein and certain electrode surfaces may mimic some physiological situations and may elucidate the relationship between the protein structures and biological functions. The linear dynamic range for the detection of hydrogen peroxide was 0.5-50 µM with a correlation coefficient of 0.999 and the detection limit was estimated at about 0.2 µM (S/N=3). The calculated apparent Michaelis-Menten constant was 0.07 (±0.01) mM, which suggested a high affinity of the redox protein-substrate. The immobilized Mb in the TiC NPs-CHIT composite film retained its bioactivity. Furthermore, the method presented here can be easily extended to immobilize and obtain the direct electrochemistry of other redox enzymes or proteins.