Utility analyses of AVITI sequencing chemistry.

BACKGROUND: DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. RESULTS: Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. CONCLUSION: These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Power system fault diagnosis with quantum computing and efficient gate decomposition.

Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers. However, most classical methods suffer from significant time-consuming, memory overhead, and computational complexity issues as the scale of the power system concerned increases. With rapid development of quantum computing technology, the combinatorial optimization method based on quantum computing has shown certain advantages in computational time over existing methods. Given this background, this paper proposes a quantum computing based power system fault diagnosis method with the quantum approximate optimization algorithm. The proposed method reformulates the fault diagnosis problem as a Hamiltonian by using Ising model, which completely preserves the coupling relationship between faulty components and various operations of protective relays and circuit breakers. Additionally, to enhance problem-solving efficiency under current equipment limitations, the symmetric equivalent decomposition method of multi-z-rotation gate is utilized. Furthermore, the small probability characteristics of power system events is utilized to reduce the number of qubits. Simulation results based on the test system show that the proposed methods can achieve the same optimal results with a faster speed compared with the classical higher-order solver provided by D-Wave.

Advances and Prospects in Liquid Biopsy Techniques for Malignant Tumor Diagnosis and Surveillance.

Liquid biopsy technology provides invaluable support for the early diagnosis of tumors and surveillance of disease course by detecting tumor-related biomarkers in bodily fluids. Currently, liquid biopsy techniques are mainly divided into two categories: biomarker and label-free. Biomarker liquid biopsy techniques utilize specific antibodies or probes to identify and isolate target cells, exosomes, or molecules, and these techniques are widely used in clinical practice. However, they have certain limitations including dependence on tumor markers, alterations in cell biological properties, and high cost. In contrast, label-free liquid biopsy techniques directly utilize physical or chemical properties of cells, exosomes, or molecules for detection and isolation. These techniques have the advantage of not needing labeling, not impacting downstream analysis, and low detection cost. However, most are still in the research stage and not yet mature. This review first discusses recent advances in liquid biopsy techniques for early tumor diagnosis and disease surveillance. Several current techniques are described in detail. These techniques exploit differences in biomarkers, size, density, deformability, electrical properties, and chemical composition in tumor components to achieve highly sensitive tumor component identification and separation. Finally, the current research progress is summarized and the future research directions of the field are discussed.

When You Think of and Identify Yourself as a Nurse, You Will Become More Deontological and Less Utilitarian.

This study aims to examine how the activation of the role of nursee and professional identification as a nurse can influence moral judgments in terms of deontological and utilitarian inclinations. In Study 1, a priming technique was used to assess the impact of activating the nursing concept on moral reasoning. Participants were randomly assigned to either a nursing prime or neutral prime condition. By using a scrambled-sentence task, participants were prompted to think about nursing-related or neutral thoughts. Following the priming task, participants were asked to respond to 20 moral dilemmas. The process dissociation approach was employed to measure the degree of deontological and utilitarian tendencies in their moral reasoning. In Study 2, participants completed the nursing profession identification scale and the moral orientation scale before engaging in moral judgments similar to those in Study 1. The findings revealed that priming the concept of being a nursee resulted in an increase in deontological clinical inclinations while having no significant effect on utilitarian inclinations. Additionally, a positive correlation was observed between identification with the nursing profession and deontological clinical inclinations, whereas a negative correlation was found with utilitarian inclinations. Deliberation orientation acted as a complete mediator in the relationship between nursing professional identification and deontological tendencies and as a partial mediator for utilitarian tendencies.

Effects of Sadness and Fear on Moral Judgments in Public Emergency Events.

With the rapid development of society and the deteriorating natural environment, there has been an increase in public emergencies. This study aimed to explore how sadness and fear in the context of public emergencies influence moral judgments. This research first induced feelings of sadness and fear by using videos about public emergencies and music, and then used moral scenarios from the CNI model (C parameter: sensitivity to consequences; N parameter: sensitivity to norms; I parameter: general preference for inaction) to assess participants' moral thinking. In Study 1, participants were divided into a sadness group and a neutral group, while in Study 2, participants were divided into a fear group and a neutral group. During the experiment, participants were exposed to different videos related to public emergencies to induce the corresponding emotions, and emotional music was continuously played throughout the entire experiment. Participants were then asked to answer questions requiring moral judgments. The results showed that based on the CNI model, sadness induced in the context of public emergencies significantly increased the C parameter, without affecting the N or I parameters. Fear increased the I parameter, without affecting the C or I parameters. That is, sadness and fear induced in the context of a public emergency can influence moral judgments. Specifically, sadness increases individuals' sensitivity to consequences and fear increases the general preference for inaction in moral judgments.

Efficient small fragment sequencing of human, cow, and bison miRNA, small RNA or csRNA-seq libraries using AVITI.

Next-Generation Sequencing (NGS) catalyzed breakthroughs across various scientific domains. Illumina's sequencing by synthesis method has long been essential for NGS but emerging technologies like Element Biosciences' sequencing by avidity (AVITI) represent a novel approach. It has been reported that AVITI offers improved signal-to-noise ratios and cost reductions. However, the method relies on rolling circle amplification which can be impacted by polymer size, raising questions about its efficacy sequencing small RNAs (sRNA) molecules including microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and others that are crucial regulators of gene expression and involved in various biological processes. In addition, capturing capped small RNAs (csRNA-seq) has emerged as a powerful method to map active or "nascent" RNA polymerase II transcription initiation in tissues and clinical samples. Here, we report a new protocol for seamlessly sequencing short DNA fragments on the AVITI and demonstrate that AVITI and Illumina sequencing technologies equivalently capture human, cattle (Bos taurus) and the bison (Bison bison) sRNA or csRNA sequencing libraries, augmenting the confidence in both approaches. Additionally, analysis of generated nascent transcription start sites (TSSs) data for cattle and bison revealed inaccuracies in their current genome annotations and highlighted the possibility and need to translate small RNA sequencing methodologies to livestock. Our accelerated and optimized protocol therefore bridges the advantages of AVITI sequencing and critical methods that rely on sequencing short DNA fragments.

Longitudinal multi-omics analysis of host microbiome architecture and immune responses during short-term spaceflight.

Maintenance of astronaut health during spaceflight will require monitoring and potentially modulating their microbiomes. However, documenting microbial shifts during spaceflight has been difficult due to mission constraints that lead to limited sampling and profiling. Here we executed a six-month longitudinal study to quantify the high-resolution human microbiome response to three days in orbit for four individuals. Using paired metagenomics and metatranscriptomics alongside single-nuclei immune cell profiling, we characterized time-dependent, multikingdom microbiome changes across 750 samples and 10 body sites before, during and after spaceflight at eight timepoints. We found that most alterations were transient across body sites; for example, viruses increased in skin sites mostly during flight. However, longer-term shifts were observed in the oral microbiome, including increased plaque-associated bacteria (for example, Fusobacteriota), which correlated with immune cell gene expression. Further, microbial genes associated with phage activity, toxin-antitoxin systems and stress response were enriched across multiple body sites. In total, this study reveals in-depth characterization of microbiome and immune response shifts experienced by astronauts during short-term spaceflight and the associated changes to the living environment, which can help guide future missions, spacecraft design and space habitat planning.

Self-Assembly Behavior, Aggregation Structure, and the Charge Carrier Transport Properties of S-Heterocyclic Annulated Perylene Diimide Derivatives.

The construction of high-performance n-type semiconductors is crucial for the advancement of organic electronics. As an attractive n-type semiconductor, molecular systems based on perylene diimide derivatives (PDIs) have been extensively investigated over recent years. Owing to the fascinating aggregated structure and high performance, S-heterocyclic annulated PDIs (SPDIs) are receiving increasing attention. However, the relationship between the structure and the electrical properties of SPDIs has not been deeply revealed, restricting the progress of PDI-based organic electronics. Here, we developed two novel SPDIs with linear and dendronized substituents in the imide position, named linear SPDI and dendronized SPDI, respectively. A series of structural and property characterizations indicated that linear SPDI formed a long-range-ordered crystalline structure based on helical supramolecular columns, while dendronized SPDI, with longer alkyl side chains, formed a 3D-ordered crystalline structure at a low temperature, which transformed into a hexagonal columnar liquid crystal structure at a high temperature. Moreover, no significant charge carrier transport signal was examined for linear SPDI, while dendronized SPDI had a charge carrier mobility of 3.5 × 10-3 cm2 V-1 s-1 and 2.1 × 10-3 cm2 V-1 s-1 in the crystalline and liquid crystalline state, respectively. These findings highlight the importance of the structure-function relationship in PDIs, and also offer useful roadmaps for the design of high-performance organic electronics for down-to-earth applications.

Utility Analyses of AVITI Sequencing Chemistry.

Background: DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. Results: Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. Conclusion: These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Highly Sensitive Weaving Sensor of Hybrid Graphene Nanoribbons and Carbon Nanotubes for Enhanced Pressure Sensing Function.

Carbon nanotubes (CNTs) hold great promise in next-generation sensors because of their remarkable physical properties. Yet, maintaining precise stacking configurations of CNTs to make full use of their remarkable properties is challenging because of their susceptibility to spontaneous reconstruction. Inspired by the weaving technology, we propose a CNT-graphene nanoribbon hybrid woven model that can maintain the specific structure of CNTs to achieve their elaborately designed function. In this study, comprehensive molecular dynamics simulations are carried out to investigate the thermal stability of the CNT-graphene hybrid woven model, as well as their potential for pressure sensing applications by utilizing the unique response of thermal transport to mechanical deformation at heterojunctions. The thermal stability is sensitive to the size of the graphene nanoribbon, and the woven structure remains stable from 200-500 K when its width is greater than 2.0 nm. Moreover, it is exciting that the sensors are effective at predicting the shapes of externally loaded objects through the analysis of the thermal conductivity distribution, which can be derived from the relationship between the thermal conduction and the pressure. Our findings shed light on the bottom-up functional design of nanomaterials and expand wider applications of high-performance nanosensors in other related fields.

Genome and clonal hematopoiesis stability contrasts with immune, cfDNA, mitochondrial, and telomere length changes during short duration spaceflight.

Background: The Inspiration4 (I4) mission, the first all-civilian orbital flight mission, investigated the physiological effects of short-duration spaceflight through a multi-omic approach. Despite advances, there remains much to learn about human adaptation to spaceflight's unique challenges, including microgravity, immune system perturbations, and radiation exposure. Methods: To provide a detailed genetics analysis of the mission, we collected dried blood spots pre-, during, and post-flight for DNA extraction. Telomere length was measured by quantitative PCR, while whole genome and cfDNA sequencing provided insight into genomic stability and immune adaptations. A robust bioinformatic pipeline was used for data analysis, including variant calling to assess mutational burden. Result: Telomere elongation occurred during spaceflight and shortened after return to Earth. Cell-free DNA analysis revealed increased immune cell signatures post-flight. No significant clonal hematopoiesis of indeterminate potential (CHIP) or whole-genome instability was observed. The long-term gene expression changes across immune cells suggested cellular adaptations to the space environment persisting months post-flight. Conclusion: Our findings provide valuable insights into the physiological consequences of short-duration spaceflight, with telomere dynamics and immune cell gene expression adapting to spaceflight and persisting after return to Earth. CHIP sequencing data will serve as a reference point for studying the early development of CHIP in astronauts, an understudied phenomenon as previous studies have focused on career astronauts. This study will serve as a reference point for future commercial and non-commercial spaceflight, low Earth orbit (LEO) missions, and deep-space exploration.

Photothermal CO2 Catalysis toward the Synthesis of Solar Fuel: From Material and Reactor Engineering to Techno-Economic Analysis.

Carbon dioxide (CO2), a member of greenhouse gases, contributes significantly to maintaining a tolerable environment for all living species. However, with the development of modern society and the utilization of fossil fuels, the concentration of atmospheric CO2 has increased to 400 ppm, resulting in a serious greenhouse effect. Thus, converting CO2 into valuable chemicals is highly desired, especially with renewable solar energy, which shows great potential with the manner of photothermal catalysis. In this review, recent advancements in photothermal CO2 conversion are discussed, including the design of catalysts, analysis of mechanisms, engineering of reactors, and the corresponding techno-economic analysis. A guideline for future investigation and the anthropogenic carbon cycle are provided.

ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation.

MOTIVATION: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH. RESULTS: Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches. AVAILABILITY AND IMPLEMENTATION: The code for this workflow is available at: https://github.com/kbolton-lab/ArCH.

Nanomechanical Analysis of Living Small Extracellular Vesicles to Identify Gastric Cancer Cell Malignancy Based on a Biomimetic Peritoneum.

Gastric cancer is one of the most prevalent digestive malignancies. The lack of effective in vitro peritoneal models has hindered the exploration of the potential mechanisms behind gastric cancer's peritoneal metastasis. An accumulating body of research indicates that small extracellular vesicles (sEVs) play an indispensable role in peritoneal metastasis of gastric cancer cells. In this study, a biomimetic peritoneum was constructed. The biomimetic model is similar to real peritoneum in internal microstructure, composition, and primary function, and it enables the recurrence of peritoneal metastasis process in vitro. Based on this model, the association between the mechanical properties of sEVs and the invasiveness of gastric cancer was identified. By performing nanomechanical analysis on sEVs, we found that the Young's modulus of sEVs can be utilized to differentiate between malignant clinical samples (ascites) and nonmalignant clinical samples (peritoneal lavage). Furthermore, patients' ascites-derived sEVs were verified to stimulate the mesothelial-to-mesenchymal transition, thereby promoting peritoneal metastasis. In summary, nanomechanical analysis of living sEVs could be utilized for the noninvasive diagnosis of malignant degree and peritoneal metastasis of gastric cancer. This finding is expected to contribute future treatments.

Thermal Property of Fullerene Fibers: One-Dimensional Material with Exceptional Thermal Performance.

The recent groundbreaking achievement in the synthesis of large-sized single crystal C60 monolayer, which is covalently bonded in a plane using C60 as building blocks. The asymmetric lattice structure endows it with anisotropic phonon modes and conductivity. If these C60 are arranged in form of 1D fiber, the improved manipulation of phonon conduction along the fiber axis could be anticipated. Here, thermal properties of C60-fiber, including thermal transfer along the C60-fiber axis and across the interlayer interface are investigated using molecular dynamic simulations. Taking advantage of the distinctively hollow spherical structure of C60 building blocks, the spherical structure deformation and encapsulation induced thermal reduction can be up to 56% and 80%, respectively. By applying external electronic fields in H2O@C60 model, its thermal conductivity decreases up to 60%, which realizes the contactless thermal regulation. ln particular, the thermal rectification phenomenon is discovered by inserting atoms/molecules in C60 with a rational designed mass-gradient, and its maximum thermal rectification factor is predicted to ≈45%. These investigations aim to achieve effective regulation of the thermal conductivity of C60-fibers. This work showcases the potential of C60-fiber in the realms of thermal management and thermal sensing, paving the way to C60-based functional materials.

Low-pass sequencing plus imputation using avidity sequencing displays comparable imputation accuracy to sequencing by synthesis while reducing duplicates.

Low-pass sequencing with genotype imputation has been adopted as a cost-effective method for genotyping. The most widely used method of short-read sequencing uses sequencing by synthesis (SBS). Here we perform a study of a novel sequencing technology-avidity sequencing. In this short note, we compare the performance of imputation from low-pass libraries sequenced on an Element AVITI system (which utilizes avidity sequencing) to those sequenced on an Illumina NovaSeq 6000 (which utilizes SBS) with an SP flow cell for the same set of biological samples across a range of genetic ancestries. We observed dramatically lower optical duplication rates in the data deriving from the AVITI system compared to the NovaSeq 6000, resulting in higher effective coverage given a fixed number of sequenced bases, and comparable imputation accuracy performance between sequencing chemistries across ancestries. This study demonstrates that avidity sequencing is a viable alternative to the standard SBS chemistries for applications involving low-pass sequencing plus imputation.

Sequencing by avidity enables high accuracy with low reagent consumption.

We present avidity sequencing, a sequencing chemistry that separately optimizes the processes of stepping along a DNA template and that of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase-polymer-nucleotide complexes bound to clonal copies of DNA targets. These polymer-nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar and yield negligible dissociation rates. Avidity sequencing achieves high accuracy, with 96.2% and 85.4% of base calls having an average of one error per 1,000 and 10,000 base pairs, respectively. We show that the average error rate of avidity sequencing remained stable following a long homopolymer.

Viral activation and ecological restructuring characterize a microbiome axis of spaceflight-associated immune activation.

Maintenance of astronaut health during spaceflight will require monitoring and potentially modulating their microbiomes, which play a role in some space-derived health disorders. However, documenting the response of microbiota to spaceflight has been difficult thus far due to mission constraints that lead to limited sampling. Here, we executed a six-month longitudinal study centered on a three-day flight to quantify the high-resolution microbiome response to spaceflight. Via paired metagenomics and metatranscriptomics alongside single immune profiling, we resolved a microbiome "architecture" of spaceflight characterized by time-dependent and taxonomically divergent microbiome alterations across 750 samples and ten body sites. We observed pan-phyletic viral activation and signs of persistent changes that, in the oral microbiome, yielded plaque-associated pathobionts with strong associations to immune cell gene expression. Further, we found enrichments of microbial genes associated with antibiotic production, toxin-antitoxin systems, and stress response enriched universally across the body sites. We also used strain-level tracking to measure the potential propagation of microbial species from the crew members to each other and the environment, identifying microbes that were prone to seed the capsule surface and move between the crew. Finally, we identified associations between microbiome and host immune cell shifts, proposing both a microbiome axis of immune changes during flight as well as the sources of some of those changes. In summary, these datasets and methods reveal connections between crew immunology, the microbiome, and their likely drivers and lay the groundwork for future microbiome studies of spaceflight.

EWELD: A Large-Scale Industrial and Commercial Load Dataset in Extreme Weather Events.

Load forecasting is crucial for the economic and secure operation of power systems. Extreme weather events, such as extreme heat and typhoons, can lead to more significant fluctuations in power consumption, making load forecasting more difficult. At present, due to the lack of relevant public data, the research on load forecasting under extreme weather events is still blank, so it is necessary to release a large-scale load dataset containing extreme weather events. The dataset includes electricity consumption data of industrial and commercial users under extreme weather events such as typhoons and extreme heat, which are collected at 15-minute intervals. The data is collected over six years from smart meters installed at the power entry points of users in southern China. The dataset consists of electricity consumption data from 386 industrial and commercial users in 17 industries, with more than 50 million records. During the recording period, extreme weather events such as typhoons and extreme heat are marked to form a total of 5,741 event records.

A novel diagnostic signature of circulating tsRNAs and miRNAs in esophageal squamous cell carcinoma detected with a microfluidic platform.

Small non-coding RNAs (sncRNAs) consisting of tRNA-derived small RNAs (tsRNAs) and miRNAs can be released by cancer cells and detected in blood, offering great potential for diagnosis of malignant tumors such as squamous cell carcinoma of the esophagus (ESCC). One of the major challenges for the clinical application of blood-based sncRNAs biomarkers is the difficulty of detection because of their small sncRNA size and low abundance. The deferentially expressed tsRNAs and miRNAs in plasma were studied with high-throughput sequencing and polymerase chain reaction in ESCC cohorts. A novel signature containing tRF-55:74-chrM.Phe-GAA, tRF-56:75-Ala-CGC-1-M4 and miR-4488 was identified with diagnostic potential. The signature was further confirmed by an attomolar-level ultrasensitive and rapid microfluidic biochip, which can achieve a multiplex, simple and low-cost detection. Our results indicated that a combination of tsRNAs and miRNAs has high diagnostic efficiency and tremendous potential to act as specific biomarkers through a reliable, highly sensitive, fast, and economic microfluidic biochip for ESCC diagnosis.