AQRNA-seq for Quantifying Small RNAs.

AQRNA-seq provides a direct linear relationship between sequencing read counts and small RNA copy numbers in a biological sample, thus enabling accurate quantification of the pool of small RNAs. The AQRNA-seq library preparation procedure described here involves the use of custom-designed sequencing linkers and a step for reducing methylation RNA modifications that block reverse transcription processivity, which results in an increased yield of full-length cDNAs. In addition, a detailed implementation of the accompanying bioinformatics pipeline is presented. This demonstration of AQRNA-seq was conducted through a quantitative analysis of the 45 tRNAs in Mycobacterium bovis BCG harvested on 5 selected days across a 20-day time course of nutrient deprivation and 6 days of resuscitation. Ongoing efforts to improve the efficiency and rigor of AQRNA-seq will also be discussed here. This includes exploring methods to obviate gel purification for mitigating primer dimer issues after PCR amplification and to increase the proportion of full-length reads to enable more accurate read mapping. Future enhancements to AQRNA-seq will be focused on facilitating automation and high-throughput implementation of this technology for quantifying all small RNA species in cell and tissue samples from diverse organisms.

Leveraging Charge-Transfer Interactions in Through-Space-Coupled Pentacene Dendritic Oligomer for Singlet Exciton Fission.

Singlet exciton fission in organic chromophores has received much attention during the past decade. Inspired by numerous spectroscopic studies in the solid state, there have been vigorous efforts to study singlet exciton fission dynamics in covalently bonded oligomers, which aims to investigate underlying mechanisms of this intriguing process in simplified model systems. In terms of through-space orbital interactions, however, most of covalently bonded pentacene oligomers studied so far fall into weakly interacting systems since they manifest chain-like structures based on various (non)conjugated linkers. Therefore, it remains as a compelling question to answer how through-space interactions in the solid state intervene this photophysical process since it is hypersensitive to displacements and orientations between neighboring chromophores. Herein, as one of experimental studies to answer this question, we introduced a tight-packing dendritic structure whose mesityl-pentacene constituents are coupled via moderate through-space orbital interactions. Based on the comparison with a suitably controlled dendritic structure, which is in a weak coupling regime, important mechanistic viewpoints are tackled such as configurational mixings between singlet, charge-transfer, and triplet pair states and the role of chromophore multiplication. We underscore that our through-space-coupled dendritic oligomer in a quasi-intermediate coupling regime provides a hint on the interplay of multiconfigurational excited-states, which might have drawn complexity in singlet exciton fission kinetics throughout numerous solid-state morphologies.

Theoretical Protocol Based on Long-Range Corrected Density Functional Theory and Tuning of Range-Split Parameter for Two-Electron Two-Proton Reduction of Phenylazocarboxylates.

A theoretical protocol based on long-range corrected density functional theory is suggested for a highly accurate estimation of the two-electron two-proton (2e2p) reduction potential of ethyl 2-phenylazocarboxylate derivatives. Geometry optimization and single-point energy refinement with ωB97X-D are recommended. The impact of polarization and diffusion functions in the basis sets on the 2e2p reduction potential is discussed. Further improvements can be achieved by tuning the range-split parameter based on the linear relationship between the Hammett constant of phenyl substituents and the optimal ω value that most accurately reproduces the experiments. The suggested protocol can accurately predict the 2e2p reduction potential of five ethyl 2-phenylazocarboxylate derivatives. Based on these findings, 22 additional candidates are suggested to enlarge the electrochemical window and to increase the selectivity of 2e2p reactions. This study contributes to the development of a theoretical approach to accurately estimate the 2e2p reduction potential of azo groups.

Barriers in establishing systematic diabetic retinopathy screening through telemedicine in low- and middle-income countries.

Vision-threatening diabetic retinopathy (VTDR) is one of the leading causes of impaired vision in the working-age population. Early identification, timely diagnosis, and prompt treatment of VTDR have to be tackled simultaneously to reduce the rate of blindness due to this condition. Considerable emphasis has been placed globally on establishing diabetic retinopathy screening (DRS) programs to enable early identification and referral of VTDR for treatment. However, there is an urgent need to shift from the common practice of opportunistic screening to a systematic DRS pathway to ensure that individuals with diabetes are screened at regular intervals and treated appropriately. While systematic DRS programs have been successfully established in countries such as the United Kingdom (UK), it continues to be a challenge to initiate and sustain such programs in low- and middle-income countries (LMIC), home to approximately 80% of people with diabetes. Telemedicine is widely recognized as an ideal DRS screening program. Although it has resulted in an upsurge of opportunistic screening, systematic recall of screened patients remains a challenge. In addition, the link between referred patients from the telemedicine programs to treatment centers is often not established or has failed to deliver; so, there is minimal impact of these telemedicine programs on VTDR blindness at present. This review covers the various barriers of establishing and sustaining systematic telemedicine DRS programs, especially in resource-constrained settings, and the challenges in aligning telemedicine to VTDR treatment pathways to ensure patients with VTDR are treated promptly and effectively.

Molecular docking-aided identification of small molecule inhibitors targeting ß-catenin-TCF4 interaction.

Here we report a molecular docking-based approach to identify small molecules that can target the ß-catenin (ß-cat)-TCF4 protein-protein interaction (PPI), a key effector complex for nuclear Wnt signaling activity. Specifically, we developed and optimized a computational model of ß-cat using publicly available ß-cat protein crystal structures, and existing ß-cat-TCF4 interaction inhibitors as the training set. Using our computational model to an in silico screen predicted 27 compounds as good binders to ß-cat, of which 3 were identified to be effective against a Wnt-responsive luciferase reporter. In vitro functional validation experiments revealed GB1874 as an inhibitor of the Wnt pathway that targets the ß-cat-TCF4 PPI. GB1874 also affected the proliferation and stemness of Wnt-addicted colorectal cancer (CRC) cells in vitro. Encouragingly, GB1874 inhibited the growth of CRC tumor xenografts in vivo, thus demonstrating its potential for further development into therapeutics against Wnt-associated cancer indications.

Faster, reduced cost calibration method development methods for the analysis of fermentation product using near-infrared spectroscopy (NIRS).

Recent innovations in synthetic biology, fermentation, and process development have decreased time to market by reducing strain construction cycle time and effort. Faster analytical methods are required to keep pace with these innovations, but current methods of measuring fermentation titers often involve manual intervention and are slow, time-consuming, and difficult to scale. Spectroscopic methods like near-infrared (NIR) spectroscopy address this shortcoming; however, NIR methods require calibration model development that is often costly and time-consuming. Here, we introduce two approaches that speed up calibration model development. First, generalized calibration modeling (GCM) or sibling modeling, which reduces calibration modeling time and cost by up to 50% by reducing the number of samples required. Instead of constructing analyte-specific models, GCM combines a reduced number of spectra from several individual analytes to produce a large pool of spectra for a generalized model predicting all analyte levels. Second, randomized multicomponent multivariate modeling (RMMM) reduces modeling time by mixing multiple analytes into one sample matrix and then taking the spectral measurements. Afterward, individual calibration methods are developed for the various components in the mixture. Time saved from the use of RMMM is proportional to the number of components or analytes in the mixture. When combined, the two methods effectively reduce the associated cost and time for calibration model development by a factor of 10.

Quantitative mapping of the cellular small RNA landscape with AQRNA-seq.

Current next-generation RNA-sequencing (RNA-seq) methods do not provide accurate quantification of small RNAs within a sample, due to sequence-dependent biases in capture, ligation and amplification during library preparation. We present a method, absolute quantification RNA-sequencing (AQRNA-seq), that minimizes biases and provides a direct, linear correlation between sequencing read count and copy number for all small RNAs in a sample. Library preparation and data processing were optimized and validated using a 963-member microRNA reference library, oligonucleotide standards of varying length, and RNA blots. Application of AQRNA-seq to a panel of human cancer cells revealed >800 detectable miRNAs that varied during cancer progression, while application to bacterial transfer RNA pools, with the challenges of secondary structure and abundant modifications, revealed 80-fold variation in tRNA isoacceptor levels, stress-induced site-specific tRNA fragmentation, quantitative modification maps, and evidence for stress-induced, tRNA-driven, codon-biased translation. AQRNA-seq thus provides a versatile means to quantitatively map the small RNA landscape in cells.

COVID-19 and literature evidence: should we publish anything and everything?

COVID-19 first presented in Wuhan, Hubei Province, China in December 2019. Since then, it has rapidly spread across the world, and is now formally considered a pandemic. As of 4th of May more than 3.2 million people have been infected and over 250,000 people has died. Since the very start, scientists and researchers have tried to utilize this case to publish academic experiences and suggestions toward fighting this virus, which is lethal in some cases. To date, more than 9,000 academic papers have been published since December 2019. The quality of publications varies from a plane letter to editor to randomized studies. This review aims to analyse the current published literature related to COVID-19 and assess the quality of such articles.

Internal mammary harvesting: Techniques and evidence from the literature.

Coronary artery bypass graft (CABG) is one of the most commonly performed cardiac surgeries in the world. CABG using the internal mammary artery (IMA) remains the gold standard intervention for myocardial intervention in multivessel coronary artery disease. IMA harvesting can be performed with various techniques and approaches: pedicled vs skeletonized harvesting technique as well as approaches such as conventional sternotomy, robotic and endoscopic approaches. While each technique and approach have their respective advantages and disadvantages, evidence remains varied between cohorts. Traditionally, IMA has been used as an in situ conduit; however, IMA free grafts also provide satisfactory outcomes in certain situations. This literature review aims to explore the efficacy of different techniques and approaches of IMA harvesting and grafting. With evidence compiled, this will provide an overview of the complexity of CABG and locate gaps in current literature to direct future research.

Dynamic expression of tRNA-derived small RNAs define cellular states.

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) have recently emerged as important regulators of protein translation and shown to have diverse biological functions. However, the underlying cellular and molecular mechanisms of tsRNA function in the context of dynamic cell-state transitions remain unclear. Expression analysis of tsRNAs in distinct heterologous cell and tissue models of stem vs. differentiated states revealed a differentiation-dependent enrichment of 5'-tsRNAs. We report the identification of a set of 5'-tsRNAs that is upregulated in differentiating mouse embryonic stem cells (mESCs). Notably, interactome studies with differentially enriched 5'-tsRNAs revealed a switch in their association with "effector" RNPs and "target" mRNAs in different cell states. We demonstrate that specific 5'-tsRNAs can preferentially interact with the RNA-binding protein, Igf2bp1, in the RA-induced differentiated state. This association influences the transcript stability and thereby translation of the pluripotency-promoting factor, c-Myc, thus providing a mechanistic basis for how 5'-tsRNAs can modulate stem cell states in mESCs. Together our study highlights the role of 5'-tsRNAs in defining distinct cell states.

Unwinding the Wnt action of casein kinase 1.

The casein kinase 1 (CK1) family, a major intracellular serine/threonine kinase, is implicated in multiple pathways; however, understanding its regulation has proven challenging. A recent study published in Science identifying allosteric activation of CK1 by the DEAD-box RNA helicase DDX3 expands our understanding of the control of this abundant kinase family.

On the noninvasive optical monitoring and differentiation of methemoglobinemia and sulfhemoglobinemia.

There are several pathologies whose study and diagnosis is impaired by a relatively small number of documented cases. A practical approach to overcome this obstacle and advance the research in this area consists in employing computer simulations to perform controlled in silico experiments. The results of these experiments, in turn, may be incorporated in the design of differential protocols for these pathologies. Accordingly, in this paper, we investigate the spectral responses of human skin affected by the presence of abnormal amounts of two dysfunctional hemoglobins, methemoglobin and sulfhemoglobin, which are associated with two life-threatening medical conditions, methemoglobinemia and sulfhemoglobinemia, respectively. We analyze the results of our in silico experiments and discuss their potential applications to the development of more effective noninvasive monitoring and differentiation procedures for these medical conditions.

Structure of a novel phosphotyrosine-binding domain in Hakai that targets E-cadherin.

Phosphotyrosine-binding domains, typified by the SH2 (Src homology 2) and PTB domains, are critical upstream components of signal transduction pathways. The E3 ubiquitin ligase Hakai targets tyrosine-phosphorylated E-cadherin via an uncharacterized domain. In this study, the crystal structure of Hakai (amino acids 106-206) revealed that it forms an atypical, zinc-coordinated homodimer by utilizing residues from the phosphotyrosine-binding domain of two Hakai monomers. Hakai dimerization allows the formation of a phosphotyrosine-binding pocket that recognizes specific phosphorylated tyrosines and flanking acidic amino acids of Src substrates, such as E-cadherin, cortactin and DOK1. NMR and mutational analysis identified the Hakai residues required for target binding within the binding pocket, now named the HYB domain. ZNF645 also possesses a HYB domain but demonstrates different target specificities. The HYB domain is structurally different from other phosphotyrosine-binding domains and is a potential drug target due to its novel structural features.

Rapid dissemination of light transport models on the web.

Light transport models are employed in applications in such varied areas as realistic image synthesis, noninvasive treatment of diseases, and remote sensing of natural resources. Openly accessible research resources can lead to significant advances involving these applications by fostering the cross-fertilization of different scientific disciplines. However, few light transport models have their source code openly available for download. Moreover, simply making the code available might not be enough; these models' complexity usually prevents their use beyond the research groups that developed them. The NPSGD (Natural Phenomena Simulation Group Distributed) framework makes light transport models easily accessible for online use. NPSGD acts a front end, connecting model implementations to the Web. It lets researchers perform predictive and time-intensive light transport simulations in a user-friendly, fault-tolerant way. More important, as a proof of concept, NPSGD demonstrates that the reproducibility of research results through model transparency is feasible. Such reproducibility can result in fruitful collaborations between model developers and users, regardless of their field of expertise.