Circular RNAs: Characterization, cellular roles, and applications.

Most circular RNAs are produced from the back-splicing of exons of precursor mRNAs. Recent technological advances have in part overcome problems with their circular conformation and sequence overlap with linear cognate mRNAs, allowing a better understanding of their cellular roles. Depending on their localization and specific interactions with DNA, RNA, and proteins, circular RNAs can modulate transcription and splicing, regulate stability and translation of cytoplasmic mRNAs, interfere with signaling pathways, and serve as templates for translation in different biological and pathophysiological contexts. Emerging applications of RNA circles to interfere with cellular processes, modulate immune responses, and direct translation into proteins shed new light on biomedical research. In this review, we discuss approaches used in circular RNA studies and the current understanding of their regulatory roles and potential applications.

Elements of successful NIH grant applications.

Is there a formula for a competitive NIH grant application? The Serenity Prayer may provide one: "Grant me the serenity to accept the things I cannot change, the ability to change the things I can, and the wisdom to know the difference." But how to tell the difference? In this Perspective, we provide an inclusive roadmap-elements of NIH funding. Collectively, we have over 30 y of peer review experience as NIH Scientific Review Officers in addition to over 30 y of program experience as NIH Program Officers. This article distills our NIH experience. We use Euclid's 13-book landmark, The Elements, as our template to humbly share what we learned. We have three specific aims: inform, guide, and motivate prospective applicants. We also address ways that support diversity and inclusion among applicants and young investigators in biomedical research. The elements we describe come from a wide range of sources. Some themes will be general. Some will be specific. All will be candid. The ultimate goal is a competitive application, serenity, and hopefully both.

Web-accessible application for identifying pathogenic transcripts with RNA-seq: Increased sensitivity in diagnosis of neurodevelopmental disorders.

For neurodevelopmental disorders (NDDs), a molecular diagnosis is key for management, predicting outcome, and counseling. Often, routine DNA-based tests fail to establish a genetic diagnosis in NDDs. Transcriptome analysis (RNA sequencing [RNA-seq]) promises to improve the diagnostic yield but has not been applied to NDDs in routine diagnostics. Here, we explored the diagnostic potential of RNA-seq in 96 individuals including 67 undiagnosed subjects with NDDs. We performed RNA-seq on single individuals' cultured skin fibroblasts, with and without cycloheximide treatment, and used modified OUTRIDER Z scores to detect gene expression outliers and mis-splicing by exonic and intronic outliers. Analysis was performed by a user-friendly web application, and candidate pathogenic transcriptional events were confirmed by secondary assays. We identified intragenic deletions, monoallelic expression, and pseudoexonic insertions but also synonymous and non-synonymous variants with deleterious effects on transcription, increasing the diagnostic yield for NDDs by 13%. We found that cycloheximide treatment and exonic/intronic Z score analysis increased detection and resolution of aberrant splicing. Importantly, in one individual mis-splicing was found in a candidate gene nearly matching the individual's specific phenotype. However, pathogenic splicing occurred in another neuronal-expressed gene and provided a molecular diagnosis, stressing the need to customize RNA-seq. Lastly, our web browser application allowed custom analysis settings that facilitate diagnostic application and ranked pathogenic transcripts as top candidates. Our results demonstrate that RNA-seq is a complementary method in the genomic diagnosis of NDDs and, by providing accessible analysis with improved sensitivity, our transcriptome analysis approach facilitates wider implementation of RNA-seq in routine genome diagnostics.

Haxe as a Swiss knife for bioinformatic applications: the SeqPHASE case story.

Haxe is a general purpose, object-oriented programming language supporting syntactic macros. The Haxe compiler is well known for its ability to translate the source code of Haxe programs into the source code of a variety of other programming languages including Java, C++, JavaScript, and Python. Although Haxe is more and more used for a variety of purposes, including games, it has not yet attracted much attention from bioinformaticians. This is surprising, as Haxe allows generating different versions of the same program (e.g. a graphical user interface version in JavaScript running in a web browser for beginners and a command-line version in C++ or Python for increased performance) while maintaining a single code, a feature that should be of interest for many bioinformatic applications. To demonstrate the usefulness of Haxe in bioinformatics, we present here the case story of the program SeqPHASE, written originally in Perl (with a CGI version running on a server) and published in 2010. As Perl+CGI is not desirable anymore for security purposes, we decided to rewrite the SeqPHASE program in Haxe and to host it at Github Pages (https://eeg-ebe.github.io/SeqPHASE), thereby alleviating the need to configure and maintain a dedicated server. Using SeqPHASE as an example, we discuss the advantages and disadvantages of Haxe's source code conversion functionality when it comes to implementing bioinformatic software.

epidecodeR: a functional exploration tool for epigenetic and epitranscriptomic regulation.

Recent technological advances in sequencing DNA and RNA modifications using high-throughput platforms have generated vast epigenomic and epitranscriptomic datasets whose power in transforming life science is yet fully unleashed. Currently available in silico methods have facilitated the identification, positioning and quantitative comparisons of individual modification sites. However, the essential challenge to link specific 'epi-marks' to gene expression in the particular context of cellular and biological processes is unmet. To fast-track exploration, we generated epidecodeR implemented in R, which allows biologists to quickly survey whether an epigenomic or epitranscriptomic status of their interest potentially influences gene expression responses. The evaluation is based on the cumulative distribution function and the statistical significance in differential expression of genes grouped by the number of 'epi-marks'. This tool proves useful in predicting the role of H3K9ac and H3K27ac in associated gene expression after knocking down deacetylases FAM60A and SDS3 and N6-methyl-adenosine-associated gene expression after knocking out the reader proteins. We further used epidecodeR to explore the effectiveness of demethylase FTO inhibitors and histone-associated modifications in drug abuse in animals. epidecodeR is available for downloading as an R package at https://bioconductor.riken.jp/packages/3.13/bioc/html/epidecodeR.html.

Robust ring-opening reaction via asymmetrically coordinated Fe single atoms scaffolded by spoke-like mesoporous carbon nanospheres.

The ability to construct metal single-atom catalysts (SACs) asymmetrically coordinated with organic heteroatoms represents an important endeavor toward developing high-performance catalysts over symmetrically coordinated counterparts. Moreover, it is of key importance in creating supporting matrix with porous architecture for situating SACs as it greatly impacts the mass diffusion and transport of electrolyte. Herein, we report the crafting of Fe single atoms with asymmetrically coordinated nitrogen (N) and phosphorus (P) atoms scaffolded by rationally designed mesoporous carbon nanospheres (MCNs) with spoke-like nanochannels for boosting ring-opening reaction of epoxide to produce an array of pharmacologically important ß-amino alcohols. Notably, interfacial defects in MCN derived from the use of sacrificial template create abundant unpaired electrons, thereby stably anchoring N and P atoms and in turn Fe atoms on MCN. Importantly, the introduction of P atom promotes the symmetry-breaking of common four N-coordinated Fe sites, resulting in the Fe-N3P sites on MCN (denoted Fe-N3P-MCN) with an asymmetric electronic configuration and thus superior catalytic capability. As such, the Fe-N3P-MCN catalysts manifest a high catalytic activity for ring-opening reaction of epoxide (97% yield) over the Fe-N3P docked on nonporous carbon surface (91%) as well as the sole Fe-N4 SACs grounded on the same MCN support (89%). Density functional theory calculations reveal that Fe-N3P SAC lowers the activation barrier for the C-O bond cleavage and the C-N bond formation, thus accelerating the ring-opening of epoxide. Our study provides fundamental and practical insights into developing advanced catalysts in a simple and controllable manner for multistep organic reactions.

The discovery of a catalytic RNA within RNase P and its legacy.

Sidney Altman's discovery of the processing of one RNA by another RNA that acts like an enzyme was revolutionary in biology and the basis for his sharing the 1989 Nobel Prize in Chemistry with Thomas Cech. These breakthrough findings support the key role of RNA in molecular evolution, where replicating RNAs (and similar chemical derivatives) either with or without peptides functioned in protocells during the early stages of life on Earth, an era referred to as the RNA world. Here, we cover the historical background highlighting the work of Altman and his colleagues and the subsequent efforts of other researchers to understand the biological function of RNase P and its catalytic RNA subunit and to employ it as a tool to downregulate gene expression. We primarily discuss bacterial RNase P-related studies but acknowledge that many groups have significantly contributed to our understanding of archaeal and eukaryotic RNase P, as reviewed in this special issue and elsewhere.

Emerging concepts of migrasome: An up-and-coming organelle from biology to the clinic.

Since the migrasome concept was first proposed in 2015, extensive research has been conducted on these novel organelles, which grow on retracted fibers at the posterior end of migrating cells. Recently, molecular markers, biological functions, and clinical values based on the initial formation mechanism of migrasomes have emerged. Additionally, researchers are recognizing the significant role that migrasomes play in the pathological and diagnostic processes of clinical diseases. In this review, we summarize recent advances in the biology and clinical application of migrasomes and provide a comprehensive view of the prospective challenges surrounding their clinical application.

Lactate and Lactylation: Clinical Applications of Routine Carbon Source and Novel Modification in Human Diseases.

Cell metabolism generates numerous intermediate metabolites that could serve as feedback and feed-forward regulation substances for posttranslational modification. Lactate, a metabolic product of glycolysis, has recently been conceptualized to play a pleiotropic role in shaping cell identities through metabolic rewiring and epigenetic modifications. Lactate-derived carbons, sourced from glucose, mediate the crosstalk among glycolysis, lactate, and lactylation. Furthermore, the multiple metabolic fates of lactate make it an ideal substrate for metabolic imaging in clinical application. Several studies have identified the crucial role of protein lactylation in human diseases associated with cell fate determination, embryonic development, inflammation, neoplasm, and neuropsychiatric disorders. Herein, this review will focus on the metabolic fate of lactate-derived carbon to provide useful information for further research and therapeutic approaches in human diseases. We comprehensively discuss its role in reprogramming and modification during the regulation of glycolysis, the clinical translation prospects of the hyperpolarized lactate signal, lactyl modification in human diseases, and its application with other techniques and omics.

PtPd Atomic Layer Shelled PdCu Hollow Nanoparticles on Partially Unzipped Carbon Nanotubes for Breaking the Activity-Stability Trade-Off toward the Hydrogen Oxidation Reaction in Alkaline Media.

Developing highly active yet stable catalysts for the hydrogen oxidation reaction (HOR) in alkaline media remains a significant challenge. Herein, we designed a novel catalyst of atomic PtPd-layer shelled ultrasmall PdCu hollow nanoparticles (HPdCu NPs) on partially unzipped carbon nanotubes (PtPd@HPdCu/W-CNTs), which can achieve a high mass activity, 5 times that of the benchmark Pt/C, and show exceptional stability with negligible decay after 20,000 cycles of accelerated degradation test. The atomically thin PtPd shell serves as the primary active site for the HOR and a protective layer that prevents Cu leaching. Additionally, the HPdCu substrate not only tunes the adsorption properties of the PtPd layer but also prevents corrosive Pt from reaching the interface between NPs and the carbon support, thereby mitigating carbon corrosion. This work introduces a new strategy that leverages the distinct advantages of multiple components to address the challenges associated with slow kinetics and poor durability toward the HOR.

Enhancing Sensitivity in Detecting Severe Fever With Thrombocytopenia Syndrome Virus: Development of a Reverse Transcription-Droplet Digital Polymerase Chain Reaction.

Severe fever with thrombocytopenia syndrome (SFTS) is a highly fatal disease. Droplet digital polymerase chain reaction (ddPCR) presents unparalleled sensitivity and enables absolute quantification of viral load. In this prospective study, we enrolled 111 patients with SFTS and collected 259 continuous samples. Our findings unveil a robust reverse transcription (RT)-ddPCR method for SFTS with a limit of detection of 2.46 copies/µL (95% CI, 1.50-11.05), surpassing the sensitivity of RT-quantitative polymerase chain reaction at 103.29 copies/µL (95% CI, 79.69-216.35). Longitudinal cohort analysis revealed significantly higher RT-ddPCR detection rates at days 10 to 11, 13 to 14, and ≥15 of the disease course as compared with RT-quantitative polymerase chain reaction (P < .05). Positive RT-ddPCR results were associated with declined platelet and elevated aspartate aminotransferase and lactate dehydrogenase on the same day vs negative RT-ddPCR samples. RT-ddPCR exhibits commendable diagnostic efficacy in SFTS, and it remains detectable in blood samples from patients with an extended disease course. Furthermore, RT-ddPCR correlates with clinical laboratory tests, furnishing valuable reference data for clinical diagnosis.

PyChelator: a Python-based Colab and web application for metal chelator calculations.

BACKGROUND: Metal ions play vital roles in regulating various biological systems, making it essential to control the concentration of free metal ions in solutions during experimental procedures. Several software applications exist for estimating the concentration of free metals in the presence of chelators, with MaxChelator being the easily accessible choice in this domain. This work aimed at developing a Python version of the software with arbitrary precision calculations, extensive new features, and a user-friendly interface to calculate the free metal ions. RESULTS: We introduce the open-source PyChelator web application and the Python-based Google Colaboratory notebook, PyChelator Colab. Key features aim to improve the user experience of metal chelator calculations including input in smaller units, selection among stability constants, input of user-defined constants, and convenient download of all results in Excel format. These features were implemented in Python language by employing Google Colab, facilitating the incorporation of the calculator into other Python-based pipelines and inviting the contributions from the community of Python-using scientists for further enhancements. Arbitrary-precision arithmetic was employed by using the built-in Decimal module to obtain the most accurate results and to avoid rounding errors. No notable differences were observed compared to the results obtained from the PyChelator web application. However, comparison of different sources of stability constants showed substantial differences among them. CONCLUSIONS: PyChelator is a user-friendly metal and chelator calculator that provides a platform for further development. It is provided as an interactive web application, freely available for use at https://amrutelab.github.io/PyChelator , and as a Python-based Google Colaboratory notebook at https://colab. RESEARCH: google.com/github/AmruteLab/PyChelator/blob/main/PyChelator_Colab.ipynb .

SimplySmart_v1, a new tool for the analysis of DNA damage optimized in primary neuronal cultures.

BACKGROUND: The increased interest in research on DNA damage in neurodegeneration has created a need for the development of tools dedicated to the analysis of DNA damage in neurons. Double-stranded breaks (DSBs) are among the most detrimental types of DNA damage and have become a subject of intensive research. DSBs result in DNA damage foci, which are detectable with the marker γH2AX. Manual counting of DNA damage foci is challenging and biased, and there is a lack of open-source programs optimized specifically in neurons. Thus, we developed a new, fully automated application, SimplySmart_v1, for DNA damage quantification and optimized its performance specifically in primary neurons cultured in vitro. RESULTS: Compared with control neurons, SimplySmart_v1 accurately identifies the induction of DNA damage with etoposide in primary neurons. It also accurately quantifies DNA damage in the desired fraction of cells and processes a batch of images within a few seconds. SimplySmart_v1 was also capable of quantifying DNA damage effectively regardless of the cell type (neuron or NSC-34). The comparative analysis of SimplySmart_v1 with other open-source tools, such as Fiji, CellProfiler and a focinator, revealed that SimplySmart_v1 is the most 'user-friendly' and the quickest tool among others and provides highly accurate results free of variability between measurements. In the context of neurodegenerative research, SimplySmart_v1 revealed an increase in DNA damage in primary neurons expressing abnormal TAR DNA/RNA binding protein (TDP-43). CONCLUSIONS: These findings showed that SimplySmart_v1 is a new and effective tool for research on DNA damage and can successfully replace other available software.

Dashing Growth Curves: a web application for rapid and interactive analysis of microbial growth curves.

BACKGROUND: Recording and analyzing microbial growth is a routine task in the life sciences. Microplate readers that record dozens to hundreds of growth curves simultaneously are increasingly used for this task raising the demand for their rapid and reliable analysis. RESULTS: Here, we present Dashing Growth Curves, an interactive web application ( http://dashing-growth-curves.ethz.ch/ ) that enables researchers to quickly visualize and analyze growth curves without the requirement for coding knowledge and independent of operating system. Growth curves can be fitted with parametric and non-parametric models or manually. The application extracts maximum growth rates as well as other features such as lag time, length of exponential growth phase and maximum population size among others. Furthermore, Dashing Growth Curves automatically groups replicate samples and generates downloadable summary plots for of all growth parameters. CONCLUSIONS: Dashing Growth Curves is an open-source web application that reduces the time required to analyze microbial growth curves from hours to minutes.

Holomics - a user-friendly R shiny application for multi-omics data integration and analysis.

An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics. Since the genomics era, several other 'omics' disciplines have emerged, and recent advances in high-throughput technologies have facilitated the generation of additional omics datasets. While traditionally analyzed individually, the last decade has seen an increase in multi-omics data integration and analysis strategies aimed at achieving a holistic understanding of interactions across different biological layers. Despite these advances, the analysis of multi-omics data is still challenging due to their scale, complexity, high dimensionality and multimodality. To address these challenges, a number of analytical tools and strategies have been developed, including clustering and differential equations, which require advanced knowledge in bioinformatics and statistics. Therefore, this study recognizes the need for user-friendly tools by introducing Holomics, an accessible and easy-to-use R shiny application with multi-omics functions tailored for scientists with limited bioinformatics knowledge. Holomics provides a well-defined workflow, starting with the upload and pre-filtering of single-omics data, which are then further refined by single-omics analysis focusing on key features. Subsequently, these reduced datasets are subjected to multi-omics analyses to unveil correlations between 2-n datasets. This paper concludes with a real-world case study where microbiomics, transcriptomics and metabolomics data from previous studies that elucidate factors associated with improved sugar beet storability are integrated using Holomics. The results are discussed in the context of the biological background, underscoring the importance of multi-omics insights. This example not only highlights the versatility of Holomics in handling different types of omics data, but also validates its consistency by reproducing findings from preceding single-omics studies.

Counter-intuitive discovery in the formulation of poorly water-soluble drugs: Amorphous small-molecule gels.

Amorphous strategies have been extensively used in improving the dissolution of insoluble drugs for decades due to their high free energy. However, the formation of amorphous small-molecule gels (ASMGs) presents a counter-intuitive discovery that significantly limits their practical application. Recently, ASMGs have garnered attention because of their noncovalent structures, excellent biodegradability, and significant potential in various drug delivery systems in the pharmaceutical field. Hence, a comprehensive review is necessary to contribute to a better understanding of recent advances in ASMGs. This review aimed to introduce the main formation mechanisms, summarize possible influencing factors, generalize unique properties, outline elimination strategies, and discuss clinical application potential with preclinical cases of ASMGs. Moreover, few ASMGs are advanced to clinical stages. Intensive clinical research is needed for further development. We hope that this review can provide more efficient and rational guidance for exploring further clinical applications of ASMGs.

The Impact of Infectious Diseases Scholarly Mentorship on Subsequent Infectious Disease Fellowship Application.

INTRODUCTION: Infectious diseases physicians invest significant time mentoring medical students and internal medicine residents through research projects as well as case reports. While having an infectious diseases mentor has been shown to be associated with subsequent infectious diseases fellowship application, the impact of specific scholarly activities on future application to infectious diseases fellowship is unknown. METHODS: All research and case reports published or presented from Brooke Army Medical Center between 2014-2022 with an infectious diseases senior author and a medical student or internal medicine resident first author were evaluated. The presentations and publications that resulted from each project as well as whether the trainee applied to infectious diseases were recorded. RESULTS: During the study period, 16 faculty mentored 35 medical student and resident research projects and 26 case reports. Research and case reports were primarily performed by residents (88% and 96% respectively). Compared to case reports, research projects were more likely to be presented at national meetings (77% vs 32%, p=0.0009). Of the 55 projects performed by trainees who completed training, research was associated with greater rates of infectious disease fellowship application as compared to case reports (41% vs. 4%, p=0.0012). CONCLUSION: Internal medicine resident and medical student involvement in research mentored by an infectious disease physician was associated with a greater infectious diseases fellowship application rate as compared to those who were mentored for case reports. Investment in trainee research may be a strategy for recruiting the next generation of infectious diseases physicians.

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications.

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Chinese herbal medicine for the treatment of intestinal cancer: preclinical studies and potential clinical applications.

Intestinal cancer (IC) poses a significant global health challenge that drives continuous efforts to explore effective treatment modalities. Conventional treatments for IC are effective, but are associated with several limitations and drawbacks. Chinese herbal medicine (CHM) plays an important role in the overall cancer prevention and therapeutic strategies. Recent years have seen a growing body of research focus on the potential of CHM in IC treatment, showing promising results in managing IC and mitigating the adverse effects of radiotherapy and chemotherapy. This review provides updated information from preclinical research and clinical observation on CHM's role in treatment of IC, offering insights into its comprehensive management and guiding future prevention strategies and clinical practice.

Clinical application of liquid biopsy in colorectal cancer: detection, prediction, and treatment monitoring.

Colorectal cancer (CRC) is one of the most prevalent malignancies affecting the gastrointestinal tract and is ranked third among cancers with the highest incidence and second-highest mortality rate worldwide. CRC exhibits a slow progression providing a wide treatment window. The currently employed CRC screening methods have shown great potential to prevent CRC and reduce CRC-related morbidity and mortality. The diagnosis of CRC is achieved by colonoscopy and tissue biopsy, with studies showing that liquid biopsy is more effective in detecting and diagnosing early CRC patients. Increasing number of studies have shown that the tumor components shed into circulating blood can be detected in liquid form, and can be applied in the clinical management of CRC. Analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), or tumor-associated platelets (TEPs) in the blood can be used for early screening and diagnosis of CRC, aid tumor staging, treatment response monitoring, and prediction of CRC recurrence and metastasis in a minimally invasive manner. This chapter provides an updated review of CTCs, ctDNA, and TEPs as novel biomarkers for CRC, highlighting their strengths and limitations.