Establishing a blockchain-enabled Indigenous data sovereignty framework for genomic data.

Technological advances have enabled the rapid generation of health and genomic data, though rarely do these technologies account for the values and priorities of marginalized communities. In this commentary, we conceptualize a blockchain genomics data framework built out of the concept of Indigenous Data Sovereignty.

A Bright Future for Antibiotics?

Multidrug resistance is a global threat as the clinically available potent antibiotic drugs are becoming exceedingly scarce. For example, increasing drug resistance among gram-positive bacteria is responsible for approximately one-third of nosocomial infections. As ribosomes are a major target for these drugs, they may serve as suitable objects for novel development of next-generation antibiotics. Three-dimensional structures of ribosomal particles from Staphylococcus aureus obtained by X-ray crystallography have shed light on fine details of drug binding sites and have revealed unique structural motifs specific for this pathogenic strain, which may be used for the design of novel degradable pathogen-specific, and hence, environmentally friendly drugs.

Ubiquitin-independent proteasomal degradation driven by C-degron pathways.

Although most eukaryotic proteins are targeted for proteasomal degradation by ubiquitination, a subset have been demonstrated to undergo ubiquitin-independent proteasomal degradation (UbInPD). However, little is known about the molecular mechanisms driving UbInPD and the degrons involved. Utilizing the GPS-peptidome approach, a systematic method for degron discovery, we found thousands of sequences that promote UbInPD; thus, UbInPD is more prevalent than currently appreciated. Furthermore, mutagenesis experiments revealed specific C-terminal degrons required for UbInPD. Stability profiling of a genome-wide collection of human open reading frames identified 69 full-length proteins subject to UbInPD. These included REC8 and CDCA4, proteins which control proliferation and survival, as well as mislocalized secretory proteins, suggesting that UbInPD performs both regulatory and protein quality control functions. In the context of full-length proteins, C termini also play a role in promoting UbInPD. Finally, we found that Ubiquilin family proteins mediate the proteasomal targeting of a subset of UbInPD substrates.

Current Status of and Perspectives on the Application of Marmosets in Neurobiology.

The common marmoset (Callithrix jacchus), a small New World primate, is receiving substantial attention in the neuroscience and biomedical science fields because its anatomical features, functional and behavioral characteristics, and reproductive features and its amenability to available genetic modification technologies make it an attractive experimental subject. In this review, I outline the progress of marmoset neuroscience research and summarize both the current status (opportunities and limitations) of and the future perspectives on the application of marmosets in neuroscience and disease modeling.

POINT technology illuminates the processing of polymerase-associated intact nascent transcripts.

Mammalian chromatin is the site of both RNA polymerase II (Pol II) transcription and coupled RNA processing. However, molecular details of such co-transcriptional mechanisms remain obscure, partly because of technical limitations in purifying authentic nascent transcripts. We present a new approach to characterize nascent RNA, called polymerase intact nascent transcript (POINT) technology. This three-pronged methodology maps nascent RNA 5' ends (POINT-5), establishes the kinetics of co-transcriptional splicing patterns (POINT-nano), and profiles whole transcription units (POINT-seq). In particular, we show by depletion of the nuclear exonuclease Xrn2 that this activity acts selectively on cleaved 5' P-RNA at polyadenylation sites. Furthermore, POINT-nano reveals that co-transcriptional splicing either occurs immediately after splice site transcription or is delayed until Pol II transcribes downstream sequences. Finally, we connect RNA cleavage and splicing with either premature or full-length transcript termination. We anticipate that POINT technology will afford full dissection of the complexity of co-transcriptional RNA processing.

Human Fetal TNF-α-Cytokine-Producing CD4+ Effector Memory T Cells Promote Intestinal Development and Mediate Inflammation Early in Life.

Although the fetal immune system is considered tolerogenic, preterm infants can suffer from severe intestinal inflammation, including necrotizing enterocolitis (NEC). Here, we demonstrate that human fetal intestines predominantly contain tumor necrosis factor-α (TNF-α)+CD4+CD69+ T effector memory (Tem) cells. Single-cell RNA sequencing of fetal intestinal CD4+ T cells showed a T helper 1 phenotype and expression of genes mediating epithelial growth and cell cycling. Organoid co-cultures revealed a dose-dependent, TNF-α-mediated effect of fetal intestinal CD4+ T cells on intestinal stem cell (ISC) development, in which low T cell numbers supported epithelial development, whereas high numbers abrogated ISC proliferation. CD4+ Tem cell frequencies were higher in inflamed intestines from preterm infants with NEC than in healthy infant intestines and showed enhanced TNF signaling. These findings reveal a distinct population of TNF-α-producing CD4+ T cells that promote mucosal development in fetal intestines but can also mediate inflammation upon preterm birth.

Enhancing Fc-mediated effector functions of monoclonal antibodies: The example of HexaBodies.

Since the approval of the CD20-targeting monoclonal antibody (mAb) rituximab for the treatment of lymphoma in 1997, mAb therapy has significantly transformed cancer treatment. With over 90 FDA-approved mAbs for the treatment of various hematological and solid cancers, modern cancer treatment relies heavily on these therapies. The overwhelming success of mAbs as cancer therapeutics is attributed to their broad applicability, high safety profile, and precise targeting of cancer-associated surface antigens. Furthermore, mAbs can induce various anti-tumor cytotoxic effector mechanisms including antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and complement-dependent cytotoxicity (CDC), all of which are mediated via their fragment crystallizable (Fc) domain. Over the past decades, these effector mechanisms have been substantially improved through Fc domain engineering. In this review, we will outline the different approaches to enhance Fc effector functions via Fc engineering of mAbs, with a specific emphasis on the so-called "HexaBody" technology, which is designed to enhance the hexamerization of mAbs on the target cell surface, thereby inducing greater complement activation, CDC, and receptor clustering. The review will summarize the development, preclinical, and clinical testing of several HexaBodies designed for the treatment of B-cell malignancies, as well as the potential use of the HexaBody technology beyond Fc-mediated effector functions.

The wooden artifacts from Schöningen's Spear Horizon and their place in human evolution.

Ethnographic records show that wooden tools played a pivotal role in the daily lives of hunter-gatherers including food procurement tools used in hunting (e.g., spears, throwing sticks) and gathering (e.g. digging sticks, bark peelers), as well as, domestic tools (e.g., handles, vessels). However, wood rarely survives in the archeological record, especially in Pleistocene contexts and knowledge of prehistoric hunter-gatherer lifeways is strongly biased by the survivorship of more resilient materials such as lithics and bones. Consequently, very few Paleolithic sites have produced wooden artifacts and among them, the site of Schöningen stands out due to its number and variety of wooden tools. The recovery of complete wooden spears and throwing sticks at this 300,000-y-old site (MIS 9) led to a paradigm shift in the hunter vs. scavenger debate. For the first time and almost 30 y after their discovery, this study introduces the complete wooden assemblage from Schöningen 13 II-4 known as the Spear Horizon. In total, 187 wooden artifacts could be identified from the Spear Horizon demonstrating a broad spectrum of wood-working techniques, including the splitting technique. A minimum of 20 hunting weapons is now recognized and two newly identified artifact types comprise 35 tools made on split woods, which were likely used in domestic activities. Schöningen 13 II-4 represents the largest Pleistocene wooden artifact assemblage worldwide and demonstrates the key role woodworking had in human evolution. Finally, our results considerably change the interpretation of the Pleistocene lakeshore site of Schöningen.

Earliest Prepared core technology in Eurasia from Nihewan (China): Implications for early human abilities and dispersals in East Asia.

Organized flaking techniques to obtain predetermined stone tools have been traced back to the early Acheulean (also known as mode 2) in Africa and are seen as indicative of the emergence of advanced technical abilities and in-depth planning skills among early humans. Here, we report one of the earliest known examples of prepared core technology in the archaeological record, at the Cenjiawan (CJW) site in the Nihewan basin of China, dated 1.1 Mya. The operational schemes reconstructed from the CJW refit sets, together with shaping patterns observed in the retouched tools, suggest that Nihewan basin toolmakers had the technical abilities of mode 2 hominins, and developed different survival strategies to adapt to local raw materials and environments. This finding predates the previously earliest known prepared core technology from Eurasia by 0.3 My, and the earliest known mode 2 sites in East Asia by a similar amount of time, thus suggesting that hominins with advanced technologies may have migrated into high latitude East Asia as early as 1.1 Mya.

Evolution of system connectivity to support food production in the Indus Basin in Pakistan.

Sustainability challenges related to food production arise from multiple nature-society interactions occurring over long time periods. Traditional methods of quantitative analysis do not represent long-term changes in the networks of system components, including institutions and knowledge that affect system behavior. Here, we develop an approach to study system structure and evolution by combining a qualitative framework that represents sustainability-relevant human, technological, and environmental components, and their interactions, mediated by knowledge and institutions, with network modeling that enables quantitative metrics. We use this approach to examine the water and food system in the Punjab province of the Indus River Basin in Pakistan, exploring how food production has been sustained, despite high population growth, periodic floods, and frequent political and economic disruptions. Using network models of five periods spanning 75 y (1947 to 2022), we examine how quantitative metrics of network structure relate to observed sustainability-relevant outcomes and how potential interventions in the system affect these quantitative metrics. We find that the persistent centrality of some and evolving centrality of other key nodes, coupled with the increasing number and length of pathways connecting them, are associated with sustaining food production in the system over time. Our assessment of potential interventions shows that regulating groundwater pumping and phasing out fossil fuels alters network pathways, and helps identify potential vulnerabilities for future food production.

Promoting sustainable smallholder farming via multistakeholder collaboration.

Transforming smallholder farms is critical to global food security and environmental sustainability. The science and technology backyard (STB) platform has proved to be a viable approach in China. However, STB has traditionally focused on empowering smallholder farmers by transferring knowledge, and wide-scale adoption of more sustainable practices and technologies remains a challenge. Here, we report on a long-term project focused on technology scale-up for smallholder farmers by expanding and upgrading the original STB platform (STB 2.0). We created a formalized and standardized process by which to engage and collaborate with farmers, including integrating their feedback via equal dialogues in the process of designing and promoting technologies. Based on 288 site-year of field trials in three regions in the North China Plain over 5 y, we find that technologies cocreated through this process were more easily accepted by farmers and increased their crop yields and nitrogen factor productivity by 7.2% and 28.1% in wheat production and by 11.4% and 27.0% in maize production, respectively. In promoting these technologies more broadly, we created a "one-stop" multistakeholder program involving local government agencies, enterprises, universities, and farmers. The program was shown to be much more effective than the traditional extension methods applied at the STB, yielding substantial environmental and economic benefits. Our study contributes an important case study for technology scale-up for smallholder agriculture. The STB 2.0 platform being explored emphasizes equal dialogue with farmers, multistakeholder collaboration, and long-term investment. These lessons may provide value for the global smallholder research and practitioners.

Modular binder technology by NGS-aided, high-resolution selection in yeast of designed armadillo modules.

Establishing modular binders as diagnostic detection agents represents a cost- and time-efficient alternative to the commonly used binders that are generated one molecule at a time. In contrast to these conventional approaches, a modular binder can be designed in silico from individual modules to, in principle, recognize any desired linear epitope without going through a selection and hit-validation process, given a set of preexisting, amino acid-specific modules. Designed armadillo repeat proteins (dArmRP) have been developed as modular binder scaffolds, and we report here the generation of highly specific dArmRP modules by yeast surface display selection, performed on a rationally designed dArmRP library. A selection strategy was developed to distinguish the binding difference resulting from a single amino acid mutation in the target peptide. Our reverse-competitor strategy introduced here employs the designated target as a competitor to increase the sensitivity when separating specific from cross-reactive binders that show similar affinities for the target peptide. With this switch in selection focus from affinity to specificity, we found that the enrichment during this specificity sort is indicative of the desired phenotype, regardless of the binder abundance. Hence, deep sequencing of the selection pools allows retrieval of phenotypic hits with only 0.1% abundance in the selectivity sort pool from the next-generation sequencing data alone. In a proof-of-principle study, a binder was created by replacing all corresponding wild-type modules with a newly selected module, yielding a binder with very high affinity for the designated target that has been successfully validated as a detection agent in western blot analysis.

Flow-electrode capacitive separation of organic acid products and recovery of alkali cations after acidic CO2 electrolysis.

Acidic CO2 electrolysis, enhanced by the introduction of alkali cations, presents a strategic approach for improving carbon efficiency compared to processes conducted in neutral and alkaline environments. However, a significant challenge arises from the dissolution of both organic acids and alkali cations in a strongly acidic feed stream, resulting in a considerable energy penalty for downstream separation. In this study, we investigate the feasibility of using flow-electrode capacitive deionization (FCDI) technology to separate organic acids and recover alkali cations from a strongly acidic feed stream (pH ~ 1). We show that organic acids, such as formic acid and acetic acid, are retained in molecular form in the separation chamber, achieving a rejection rate of over 90% under all conditions. Alkali cations, such as K+ and Cs+, migrate to the cathode chamber in ionic form, with their removal and recovery significantly influenced by their concentration and the pH of the feed stream, but responding differently to the types and concentrations of organic acids. The energy consumption for the removal and recovery of K+ is 4 to 8 times higher than for Cs+, and the charge efficiency is significantly influenced by the types of organic acid products and alkali cations. We conduct a series of electrochemical measurements and analyze the impedance spectroscopy, identifying that hindered mass transfer governed the electrode process. Our findings underscore the potential of FCDI as an advanced downstream separation technology for acidic electrocatalysis processes.

Tools for editing the mammalian mitochondrial genome.

The manipulation of animal mitochondrial genomes has long been a challenge due to the lack of an effective transformation method. With the discovery of specific gene editing enzymes, designed to target pathogenic mitochondrial DNA mutations (often heteroplasmic), the selective removal or modification of mutant variants has become a reality. Because mitochondria cannot efficiently import RNAs, CRISPR has not been the first choice for editing mitochondrial genes. However, the last few years witnessed an explosion in novel and optimized non-CRISPR approaches to promote double-strand breaks or base-edit of mtDNA in vivo. Engineered forms of specific nucleases and cytidine/adenine deaminases form the basis for these techniques. I will review the newest developments that constitute the current toolbox for animal mtDNA gene editing in vivo, bringing these approaches not only to the exploration of mitochondrial function, but also closer to clinical use.

miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data.

Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.

From tradition to innovation: conventional and deep learning frameworks in genome annotation.

Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the emergence of numerous novel technologies, accompanied by the provision of vast amounts of whole-genome sequences, high-throughput data such as ChIP-Seq and RNA-Seq. Extracting biologically meaningful information from this massive dataset has become a critical aspect of many recent studies, particularly in annotating and predicting the functions of unknown genes. The core idea behind genome annotation is to identify genes and various functional elements within the genome sequence and infer their biological functions. Traditional wet-lab experimental methods still rely on extensive efforts for functional verification. However, early bioinformatics algorithms and software primarily employed shallow learning techniques; thus, the ability to characterize data and features learning was limited. With the widespread adoption of RNA-Seq technology, scientists from the biological community began to harness the potential of machine learning and deep learning approaches for gene structure prediction and functional annotation. In this context, we reviewed both conventional methods and contemporary deep learning frameworks, and highlighted novel perspectives on the challenges arising during annotation underscoring the dynamic nature of this evolving scientific landscape.

The One Hour Human Proteome.

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

The effects of local interventions on global technological change through spillovers: A modeling framework and application to the road-freight sector.

To address global sustainability challenges, (public) policy interventions are needed to induce or accelerate technological change. While most policy interventions occur on the local level, their innovation effects can spill over to other jurisdictions, potentially having global impact. These spillovers can increase or reduce the incentive for interventions. Lacking to date are computational models that capture these spillover dynamics. Here, we devise a conceptual and methodological approach to quantify ex ante the effects of local demand-side interventions on global competition between incumbent and novel technologies. We introduce two factors that moderate global spillovers-relative size of selection environments and relative innovation potential of competing technologies. Our approach incorporates both factors in a techno-economic discrete choice model that evaluates technology competition over time through endogenized technological learning. We apply this modeling framework to the case of road freight. Different demand-pull interventions and shocks are modeled to assess spillover effects. In the case of road freight, electric vehicles experience growth in most application segments but can still be accelerated substantially through public policy intervention-spillovers occur if strong public interventions are introduced in large regions or in multiple combined regions under club policy interventions. These findings are discussed in the context of club policy interventions and a modeled geopolitical shock in China. A full sensitivity analysis of model input parameters and intervention or shock dynamics reveals high model robustness. Finally, we discuss the implications of the road-freight case study as it might inform the progress of other niche technologies in transitioning sectors.

Science, evidence, law, and justice.

For nearly 25 y, the Committee on Science, Technology, and Law (CSTL), of the National Academies of Sciences, Engineering, and Medicine, has brought together distinguished members of the science and law communities to stimulate discussions that would lead to a better understanding of the role of science in legal decisions and government policies and to a better understanding of the legal and regulatory frameworks that govern the conduct of science. Under the leadership of recent CSTL co-chairs David Baltimore and David Tatel, and CSTL director Anne-Marie Mazza, the committee has overseen many interdisciplinary discussions and workshops, such as the international summits on human genome editing and the science of implicit bias, and has delivered advisory consensus reports focusing on topics of broad societal importance, such as dual use research in the life sciences, voting systems, and advances in neural science research using organoids and chimeras. One of the most influential CSTL activities concerns the use of forensic evidence by law enforcement and the courts, with emphasis on the scientific validity of forensic methods and the role of forensic testimony in bringing about justice. As coeditors of this Special Feature, CSTL alumni Tom Albright and Jennifer Mnookin have recruited articles at the intersection of science and law that reveal an emerging scientific revolution of forensic practice, which we hope will engage a broad community of scientists, legal scholars, and members of the public with interest in science-based legal policy and justice reform.

Comparison of copper and graphene-assembled films in 5G wireless communication and THz electromagnetic-interference shielding.

Since first developed, the conducting materials in wireless communication and electromagnetic interference (EMI) shielding devices have been primarily made of metal-based structures. Here, we present a graphene-assembled film (GAF) that can be used to replace copper in such practical electronics. The GAF-based antennas present strong anticorrosive behavior. The GAF ultra-wideband antenna covers the frequency range of 3.7 GHz to 67 GHz with the bandwidth (BW) of 63.3 GHz, which exceed ~110% than the copper foil-based antenna. The GAF Fifth Generation (5G) antenna array features a wider BW and lower sidelobe level compared with that of copper antennas. EMI shielding effectiveness (SE) of GAF also outperforms copper, reaching up to 127 dB in the frequency range of 2.6 GHz to 0.32 THz, with a SE per unit thickness of 6,966 dB/mm. We also confirm that GAF metamaterials exhibit promising frequency selection characteristics and angular stability as flexible frequency selective surfaces.