Revisiting mechanics of ice–skate friction : from experiments at a skating rink to a unified hypothesis

The mechanics underlying ice–skate friction remain uncertain despite over a century of study. In the 1930s, the theory of self-lubrication from frictional heat supplanted an earlier hypothesis that pressure melting governed skate friction. More recently, researchers have suggested that a layer of abraded wear particles or the presence of quasi-liquid molecular layers on the surface of ice could account for its slipperiness. Here, we assess the dominant hypotheses proposed to govern ice– skate friction and describe experiments conducted in an indoor skating rink aimed to provide observations to test these hypotheses. Our results indicate that the brittle failure of ice under rapid compression plays a strong role. Our observations did not confirm the presence of full contact water films and are more consistent with the presence of lubricating ice-rich slurries at discontinuous high-pressure zones (HPZs). The presence of ice-rich slurries supporting skates through HPZs merges pressure-melting, abrasion and lubricating films as a unified hypothesis for why skates are so slippery across broad ranges of speeds, temperatures and normal loads. We suggest tribometer experiments to overcome the difficulties of investigating these processes during actual skating trials.

Coupling miR/isomiR and mRNA Expression Signatures Unveils New Molecular Layers of Endometrial Receptivity

Embryo implantation depends on endometrial receptivity (ER). To achieve ER, the preparation of the uterine lining requires controlled priming by ovarian hormones and the expression of numerous genes in the endometrial tissue. microRNAs (miRs) have emerged as critical genetic regulators of ER in fertility and of the diseases that are associated with infertility. With the rapid development of next-generation sequencing technologies, it has become clear that miR genes can produce canonical miRs and variants—isomiRs. Here, we describe miR/isomiR expression dynamics across the four time points of natural chorionic gonadotropin (hCG)-administered cycles. Sequencing of the small RNAs (sRNA-seq) revealed that the most significant expression changes during the transition from the pre-receptive to the receptive phase occurred in the isomiR families of miR-125a, miR-125b, miR-10a, miR-10b, miR-449c, miR-92a, miR-92b, and miR-99a. Pairing the analysis of the differentially expressed (DE) miRs/isomiRs and their predicted DE mRNA targets uncovered 280 negatively correlating pairs. In the receptive endometrium, the 5’3’-isomiRs of miR-449c, which were among the most highly up-regulated isomiRs, showed a negative correlation with their target, transcription factor (TF) MYCN, which was down-regulated. Joint analysis of the miR/isomiR and TF expression identified several regulatory interactions. Based on these data, a regulatory TF-miR/isomiR gene-target circuit including let7g-5p and miR-345; the isomiR families of miR-10a, miR-10b, miR-92a, and miR-449c; and MYCN and TWIST1 was proposed to play a key role in the establishment of ER. Our work uncovers the complexity and dynamics of the endometrial isomiRs that can act cooperatively with miRs to control the functionally important genes that are critical to ER. Further studies of miR/isomiR expression patterns that are paired with those of their target mRNAs may provide a more in-depth picture of the endometrial pathologies that are associated with implantation failure.

Underestimation of Heritability across the Molecular Layers of the Gene Expression Process

We investigated the extent of the heritability underestimation for molecules from an infinitesimal model in mixed model analysis. To this end, we estimated the heritability of transcription, ribosome occupancy, and translation in lymphoblastoid cell lines from Yoruba individuals. Upon considering all genome-wide nucleotide variants, a considerable underestimation in heritability was observed for mRNA transcription (−0.52), ribosome occupancy (−0.48), and protein abundance (−0.47). We employed a mixed model with an optimal number of nucleotide variants, which maximized heritability, and identified two novel expression quantitative trait loci (eQTLs; p < 1.0 × 10−5): rs11016815 on chromosome 10 that influences the transcription of SCP2, a trans-eGene on chromosome 1—whose expression increases in response to MGMT downregulation-induced apoptosis, the cis-eGene of rs11016815—and rs1041872 on chromosome 11 that influences the ribosome occupancy of CCDC25 on chromosome 8 and whose cis-eGene encodes ZNF215, a transcription factor that potentially regulates the translation speed of CCDC25. Our results suggest that an optimal number of nucleotide variants should be used in a mixed model analysis to accurately estimate heritability and identify eQTLs. Moreover, a heterogeneous covariance structure based on gene identity and the molecular layers of the gene expression process should be constructed to better explain polygenic effects and reduce errors in identifying eQTLs.

At the dawn: cell-free DNA fragmentomics and gene regulation

Epigenetic mechanisms play instrumental roles in gene regulation during embryonic development and disease progression. However, it is challenging to non-invasively monitor the dynamics of epigenomes and related gene regulation at inaccessible human tissues, such as tumours, fetuses and transplanted organs. Circulating cell-free DNA (cfDNA) in peripheral blood provides a promising opportunity to non-invasively monitor the genomes from these inaccessible tissues. The fragmentation patterns of plasma cfDNA are unevenly distributed in the genome and reflect the in vivo gene-regulation status across multiple molecular layers, such as nucleosome positioning and gene expression. In this review, we revisited the computational and experimental approaches that have been recently developed to measure the cfDNA fragmentomics across different resolutions comprehensively. Moreover, cfDNA in peripheral blood is released following cell death, after apoptosis or necrosis, mainly from haematopoietic cells in healthy people and diseased tissues in patients. Several cfDNA-fragmentomics approaches showed the potential to identify the tissues-of-origin in cfDNA from cancer patients and healthy individuals. Overall, these studies paved the road for cfDNA fragmentomics to non-invasively monitor the in vivo gene-regulatory dynamics in both peripheral immune cells and diseased tissues.

Self-Propelled Motion Sensitive to the Chemical Structure of Amphiphilic Molecular Layer on an Aqueous Phase

Two novel amphiphiles, N-(3-nitrophenyl)stearamide (MANA) and N,N′-(4-nitro-1,3-phenylene)distearamide (OPANA), were synthesized by reacting nitroanilines with one or two equivalents of stearic acid. We investigated how the molecular structures of these compounds influenced the characteristics of a self-propelled camphor disk placed on a monolayer of the synthesized amphiphiles. Three types of motion were observed at different surface pressures (Π): continuous motion (Π < 4 mN m−1), deceleration (4 mN ≤ Π ≤ 20 mN m−1), and no motion (Π > 20 mN m−1). The speed of the motion of the camphor disks was inversely related to Π for both MANA and OPANA at the temperatures tested, when Π increased in the respective molecular layers under compression. The spectroscopic evidence from UV-Vis, NMR, and ESI-TOF-MS revealed that the dependence of the speed of the motion on Π originates from the intermolecular interactions that are present in the monolayers. This study suggests that it is possible to control the self-propelled motion by manipulating contributing factors at the molecular level.

Adsorption of Binary Solvents on Chiral Stationary Phases with Grafted Macrocyclic Antibiotics

A study is performed of the adsorption of water–methanol and water–acetonitrile mixtures on chiral stationary phases (CSPs) Chirobiotic R, Chirobiotic T, and Nautilus-E with grafted macrocyclic antibiotics ristocetin A, teicoplanin, and eremomycin, respectively. The patterns of adsorption on the indicated CSPs are qualitatively the same, and differ only by quantitative indicators. Adsorption isotherms of excess water from binary solvents have adsorption azeotrope points and show the preferred absorption of water in the range of pure organic component to an azeotrope point in the range of 60–75 mol % for H2О–МеОН and 80–90 mol % for H2O–MeCN systems. It is shown that the thickness of the adsorption phase in the first case is less than one nominal molecular layer (0.10–0.13 nm). For H2O–MeCN, it is 3–4 molecular layers (0.88–1.05 nm). Activity coefficients are calculated for the components of solutions in surface layers. The coefficients indicate the systems deviate considerably from the properties of an ideal adsorption solution. Reasons for this behavior are discussed.

Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

Background: The majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes. Results: We collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in the Bioconductor Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within the Bioconductor ecosystem of hundreds of packages for single-cell and multimodal data. Conclusions: We provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.

The molecular pathophysiology of mood disorders: from the analysis of single molecular layers to multi-omic integration.

Next-generation sequencing now enables the rapid and affordable production of reliable biological data at multiple molecular levels, collectively referred to as “omics”. To maximize the potential for discovery, computational biologists have created and adapted integrative multiomic analytical methods. When applied to diseases with traceable pathophysiology such as cancer, these new algorithms and statistical approaches have enabled the discovery of clinically relevant molecular mechanisms and biomarkers. In contrast, these methods have been much less applied to the field of molecular psychiatry, although diagnostic and prognosticbiomarkers are similarly needed. In the present review, we first briefly summarize main findings from two decades of studies that investigated single molecular processes in relation to mood disorders. Then, we conduct a systematic review of multi-omic strategies that have been proposed and used more recently. We also list databases and types of data available to researchers for future work. Finally, we present the newest methodologies that have been employed for multi-omics integration in other medical fields, and discuss their potential for molecular psychiatry studies.