Generating and using real-world data: A worthwhile uphill battle.

The precision oncology paradigm challenges the feasibility and data generalizability of traditional clinical trials. Consequently, an unmet need exists for practical approaches to test many subgroups, evaluate real-world drug value, and gather comprehensive, accessible datasets to validate novel biomarkers. Real-world data (RWD) are increasingly recognized to have the potential to fill this gap in research methodology. Established applications of RWD include informing disease epidemiology, pharmacovigilance, and healthcare quality assessment. Currently, concerns regarding RWD quality and comprehensiveness, privacy, and biases hamper their broader application. Nonetheless, RWD may play a pivotal role in supplementing clinical trials, enabling conditional reimbursement and accelerated drug access, and innovating trial conduct. Moreover, purpose-built RWD repositories may support the extension or refinement of drug indications and facilitate the discovery and validation of new biomarkers. This perspective explores the potential of leveraging RWD to advance oncology, highlights its benefits and challenges, and suggests a path forward in this evolving field.

The Master Observational Trial: A New Class of Master Protocol to Advance Precision Medicine.

This commentary introduces a new clinical trial construct, the Master Observational Trial (MOT), which hybridizes the power of molecularly based master interventional protocols with the breadth of real-world data. The MOT provides a clinical venue to allow molecular medicine to rapidly advance, answers questions that traditional interventional trials generally do not address, and seamlessly integrates with interventional trials in both diagnostic and therapeutic arenas. The result is a more comprehensive data collection ecosystem in precision medicine.

Genomic Epidemiology of SARS-CoV-2 in Guangdong Province, China.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2 infection and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, China's most populous province, during early 2020 resulted in 1,388 reported RNA-positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China, we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain because of low virus genetic variation early in the pandemic. Our results illustrate how the timing, size, and duration of putative local transmission chains were constrained by national travel restrictions and by the province's large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required, because the number of cases imported from other countries has increased.

Characterizing the Major Structural Variant Alleles of the Human Genome.

In order to provide a comprehensive resource for human structural variants (SVs), we generated long-read sequence data and analyzed SVs for fifteen human genomes. We sequence resolved 99,604 insertions, deletions, and inversions including 2,238 (1.6 Mbp) that are shared among all discovery genomes with an additional 13,053 (6.9 Mbp) present in the majority, indicating minor alleles or errors in the reference. Genotyping in 440 additional genomes confirms the most common SVs in unique euchromatin are now sequence resolved. We report a ninefold SV bias toward the last 5 Mbp of human chromosomes with nearly 55% of all VNTRs (variable number of tandem repeats) mapping to this portion of the genome. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity.

An overview of real-world data sources for oncology and considerations for research.

Generating evidence on the use, effectiveness, and safety of new cancer therapies is a priority for researchers, health care providers, payers, and regulators given the rapid pace of change in cancer diagnosis and treatments. The use of real-world data (RWD) is integral to understanding the utilization patterns and outcomes of these new treatments among patients with cancer who are treated in clinical practice and community settings. An initial step in the use of RWD is careful study design to assess the suitability of an RWD source. This pivotal process can be guided by using a conceptual model that encourages predesign conceptualization. The primary types of RWD included are electronic health records, administrative claims data, cancer registries, and specialty data providers and networks. Careful consideration of each data type is necessary because they are collected for a specific purpose, capturing a set of data elements within a certain population for that purpose, and they vary by population coverage and longitudinality. In this review, the authors provide a high-level assessment of the strengths and limitations of each data category to inform data source selection appropriate to the study question. Overall, the development and accessibility of RWD sources for cancer research are rapidly increasing, and the use of these data requires careful consideration of composition and utility to assess important questions in understanding the use and effectiveness of new therapies.

Heterotrimeric G Protein Subunit Gαq Is a Master Switch for Gßγ-Mediated Calcium Mobilization by Gi-Coupled GPCRs.

Mechanisms that control mobilization of cytosolic calcium [Ca2+]i are key for regulation of numerous eukaryotic cell functions. One such paradigmatic mechanism involves activation of phospholipase Cß (PLCß) enzymes by G protein ßγ subunits from activated Gαi-Gßγ heterotrimers. Here, we report identification of a master switch to enable this control for PLCß enzymes in living cells. We find that the Gαi-Gßγ-PLCß-Ca2+ signaling module is entirely dependent on the presence of active Gαq. If Gαq is pharmacologically inhibited or genetically ablated, Gßγ can bind to PLCß but does not elicit Ca2+ signals. Removal of an auto-inhibitory linker that occludes the active site of the enzyme is required and sufficient to empower "stand-alone control" of PLCß by Gßγ. This dependence of Gi-Gßγ-Ca2+ on Gαq places an entire signaling branch of G-protein-coupled receptors (GPCRs) under hierarchical control of Gq and changes our understanding of how Gi-GPCRs trigger [Ca2+]i via PLCß enzymes.

Foundations of reasoning with uncertainty via real-valued logics.

Interest in logics with some notion of real-valued truths has existed since at least Boole and has been increasing in AI due to the emergence of neuro-symbolic approaches, though often their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of such systems. We introduce a rich class of multidimensional sentences, with a sound and complete axiomatization that can be parameterized to cover many real-valued logics, including all the common fuzzy logics, and extend these to weighted versions, and to the case where the truth values are probabilities. Our multidimensional sentences form a very rich class. Each of our multidimensional sentences describes a set of possible truth values for a collection of formulas of the real-valued logic, including which combinations of truth values are possible. Our completeness result is strong, in the sense that it allows us to derive exactly what information can be inferred about the combinations of truth values of a collection of formulas given information about the combinations of truth values of a finite number of other collections of formulas. We give a decision procedure based on linear programming for deciding, for certain real-valued logics and under certain natural assumptions, whether a set of our sentences logically implies another of our sentences. The generality of this work, compared to many previous works on special cases, may provide insights for both existing and new real-valued logics whose inference properties have never been characterized. This work may also provide insights into the reasoning capabilities of deep learning models.

Genomics in the long-read sequencing era.

Long-read sequencing (LRS) technologies have provided extremely powerful tools to explore genomes. While in the early years these methods suffered technical limitations, they have recently made significant progress in terms of read length, throughput, and accuracy and bioinformatics tools have strongly improved. Here, we aim to review the current status of LRS technologies, the development of novel methods, and the impact on genomics research. We will explore the most impactful recent findings made possible by these technologies focusing on high-resolution sequencing of genomes and transcriptomes and the direct detection of DNA and RNA modifications. We will also discuss how LRS methods promise a more comprehensive understanding of human genetic variation, transcriptomics, and epigenetics for the coming years.

Quantification of tRNA m1A modification by templated-ligation qPCR.

N1-methyladenosine (m1A) is a widespread modification in all eukaryotic, many archaeal, and some bacterial tRNAs. m1A is generally located in the T loop of cytosolic tRNA and between the acceptor and D stems of mitochondrial tRNAs; it is involved in the tertiary interaction that stabilizes tRNA. Human tRNA m1A levels are dynamically regulated that fine-tune translation and can also serve as biomarkers for infectious disease. Although many methods have been used to measure m1A, a PCR method to assess m1A levels quantitatively in specific tRNAs has been lacking. Here we develop a templated-ligation followed by a qPCR method (TL-qPCR) that measures m1A levels in target tRNAs. Our method uses the SplintR ligase that efficiently ligates two tRNA complementary DNA oligonucleotides using tRNA as the template, followed by qPCR using the ligation product as the template. m1A interferes with the ligation in specific ways, allowing for the quantitative assessment of m1A levels using subnanogram amounts of total RNA. We identify the features of specificity and quantitation for m1A-modified model RNAs and apply these to total RNA samples from human cells. Our method enables easy access to study the dynamics and function of this pervasive tRNA modification.

The gender gap in the ownership of promising land.

Using millions of observations compiled from the public administrative data of Taiwan, we find a surprising gender inequity in terms of real estate: Men own more land than women, and the annual rate of return (ROR) of men's land outperform women's by almost 1% per year. The latter finding of gender-based ROR difference is in sharp contrast to prior evidence that women outperform men in security investment, and also suggests a quantity-and-quality double jeopardy in female land ownership which, given the heavy weight of real estate in individual wealth, has important implications for wealth inequality among men and women. Our statistical analyses suggest that such a gender-based difference in land ROR cannot be attributed to individual-level factors such as liquidity preferences, risk attitudes, investment experience, and behavioral biases, as described in the literature. Rather, we hypothesize parental gender bias-a phenomenon that is still prevalent today-to be the key macrolevel factor. To test our hypothesis, we partition our observations into two groups: an experimental group in which parents can exercise gender discretion, and a control group in which parents cannot exercise such discretion. Our empirical evidence shows that the gender difference with respect to land ROR only exists in the experimental group. For many societies with long-lasting patriarchal traditions, our analysis provides a perspective to help explain gender differences in wealth distribution and social mobility.

Synchronization of the circadian clock to the environment tracked in real time.

The circadian system of the cyanobacterium Synechococcus elongatus PCC 7942 relies on a three-protein nanomachine (KaiA, KaiB, and KaiC) that undergoes an oscillatory phosphorylation cycle with a period of ~24 h. This core oscillator can be reconstituted in vitro and is used to study the molecular mechanisms of circadian timekeeping and entrainment. Previous studies showed that two key metabolic changes that occur in cells during the transition into darkness, changes in the ATP/ADP ratio and redox status of the quinone pool, are cues that entrain the circadian clock. By changing the ATP/ADP ratio or adding oxidized quinone, one can shift the phase of the phosphorylation cycle of the core oscillator in vitro. However, the in vitro oscillator cannot explain gene expression patterns because the simple mixture lacks the output components that connect the clock to genes. Recently, a high-throughput in vitro system termed the in vitro clock (IVC) that contains both the core oscillator and the output components was developed. Here, we used IVC reactions and performed massively parallel experiments to study entrainment, the synchronization of the clock with the environment, in the presence of output components. Our results indicate that the IVC better explains the in vivo clock-resetting phenotypes of wild-type and mutant strains and that the output components are deeply engaged with the core oscillator, affecting the way input signals entrain the core pacemaker. These findings blur the line between input and output pathways and support our previous demonstration that key output components are fundamental parts of the clock.

Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback.

Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use.

Earthquake alerting based on spatial geodetic data by spatiotemporal information transformation learning.

Alerting for imminent earthquakes is particularly challenging due to the high nonlinearity and nonstationarity of geodynamical phenomena. In this study, based on spatiotemporal information (STI) transformation for high-dimensional real-time data, we developed a model-free framework, i.e., real-time spatiotemporal information transformation learning (RSIT), for extending the nonlinear and nonstationary time series. Specifically, by transforming high-dimensional information of the global navigation satellite system into one-dimensional dynamics via the STI strategy, RSIT efficiently utilizes two criteria of the transformed one-dimensional dynamics, i.e., unpredictability and instability. Such two criteria contemporaneously signal a potential critical transition of the geodynamical system, thereby providing early-warning signals of possible upcoming earthquakes. RSIT explores both the spatial and temporal dynamics of real-world data on the basis of a solid theoretical background in nonlinear dynamics and delay-embedding theory. The effectiveness of RSIT was demonstrated on geodynamical data of recent earthquakes from a number of regions across at least 4 y and through further comparison with existing methods.

Ultrafast many-body bright-dark exciton transition in anatase TiO2.

The momentum-forbidden dark excitons can have a pivotal role in quantum information processing, Bose-Einstein condensation, and light-energy harvesting. Anatase TiO2 with an indirect band gap is a prototypical platform to study bright to momentum-forbidden dark exciton transition. Here, we examine, by GW plus the real-time Bethe-Salpeter equation combined with the nonadiabatic molecular dynamics (GW + rtBSE-NAMD), the many-body transition that occurs within 100 fs from the optically excited bright to the strongly bound momentum-forbidden dark excitons in anatase TiO2. Comparing with the single-particle picture in which the exciton transition is considered to occur through electron-phonon scattering, within the GW + rtBSE-NAMD framework, the many-body electron-hole Coulomb interaction activates additional exciton relaxation channels to notably accelerate the exciton transition in competition with other radiative and nonradiative processes. The existence of dark excitons and ultrafast bright-dark exciton transitions sheds insights into applications of anatase TiO2 in optoelectronic devices and light-energy harvesting as well as the formation process of dark excitons in semiconductors.

Intermediate-range order governs dynamics in dense colloidal liquids.

The conventional wisdom is that liquids are completely disordered and lack nontrivial structure beyond nearest-neighbor distances. Recent observations have upended this view and demonstrated that the microstructure in liquids is surprisingly rich and plays a critical role in numerous physical, biological, and industrial processes. However, approaches to uncover this structure are either system-specific or yield results that are not physically intuitive. Here, through single-particle resolved three-dimensional confocal microscope imaging and the use of a recently introduced four-point correlation function, we show that bidisperse colloidal liquids have a highly nontrivial structure comprising alternating layers with icosahedral and dodecahedral order, which extends well beyond nearest-neighbor distances and grows with supercooling. By quantifying the dynamics of the system on the particle level, we establish that it is this intermediate-range order, and not the short-range order, which has a one-to-one correlation with dynamical heterogeneities, a property directly related to the relaxation dynamics of glassy liquids. Our experimental findings provide a direct and much sought-after link between the structure and dynamics of liquids and pave the way for probing the consequences of this intermediate-range order in other liquid state processes.

The Volitional Control of Individual Motor Units Is Constrained within Low-Dimensional Neural Manifolds by Common Inputs.

The implementation of low-dimensional movement control by the central nervous system has been debated for decades. In this study, we investigated the dimensionality of the control signals received by spinal motor neurons when controlling either the ankle or knee joint torque. We first identified the low-dimensional latent factors underlying motor unit activity during torque-matched isometric contractions in male participants. Subsequently, we evaluated the extent to which motor units could be independently controlled. To this aim, we used an online control paradigm in which participants received the corresponding motor unit firing rates as visual feedback. We identified two main latent factors, regardless of the muscle group (vastus lateralis-medialis and gastrocnemius lateralis-medialis). The motor units of the gastrocnemius lateralis could be controlled largely independently from those of the gastrocnemius medialis during ankle plantarflexion. This dissociation of motor unit activity imposed similar behavior to the motor units that were not displayed in the feedback. Conversely, it was not possible to dissociate the activity of the motor units between the vastus lateralis and medialis muscles during the knee extension tasks. These results demonstrate that the number of latent factors estimated from linear dimensionality reduction algorithms does not necessarily reflect the dimensionality of volitional control of motor units. Overall, individual motor units were never controlled independently of all others but rather belonged to synergistic groups. Together, these findings provide evidence for a low-dimensional control of motor units constrained by common inputs, with notable differences between muscle groups.

The Effects of Free Breathing on Cerebral Venous Flow: A Real-Time Phase Contrast MRI Study in Healthy Adults.

Quantifying the effects of free breathing on cerebral venous flow is crucial for understanding cerebral circulation mechanisms and clinical applications. Unlike conventional cine phase-contrast MRI sequences (CINE-PC), real-time phase-contrast MRI sequences (RT-PC) can provide a continuous beat-to-beat flow signal that makes it possible to quantify the effect of breathing on cerebral venous flow. In this study, we examined 28 healthy human participants, comprising of 14 males and 14 females. Blood flows in the right/left internal jugular veins in the extracranial plane and the superior sagittal sinus (SSS) and straight sinus in the intercranial plane were quantified using CINE-PC and RT-PC. The first objective of this study was to determine the accuracy of RT-PC in quantifying cerebral venous flow, relative to CINE-PC. The second, and main objective, was to quantify the effect of free breathing on cerebral venous flow, using a time-domain multiparameter analysis method. Our results showed that RT-PC can accurately quantify cerebral venous flow with a 2 × 2 mm2 spatial resolution and 75 ms/image time resolution. The mean flow rate, amplitude, stroke volume, and cardiac period of cerebral veins were significantly higher from the mid-end phase of expiration to the mid-end phase of inspiration. Breathing affected the mean flow rates in the jugular veins more than those in the SSS and straight sinus. Furthermore, the effects of free breathing on the flow rate of the left and right jugular veins were not synchronous. These new findings provide a useful reference for better understanding the mechanisms of cerebral circulation.

A real-time biochemical assay for quantitative analyses of APOBEC-catalyzed DNA deamination.

Over the past decade, the connection between APOBEC3 cytosine deaminases and cancer mutagenesis has become increasingly apparent. This growing awareness has created a need for biochemical tools that can be used to identify and characterize potential inhibitors of this enzyme family. In response to this challenge, we have developed a Real-time APOBEC3-mediated DNA Deamination assay. This assay offers a single-step set-up and real-time fluorescent read-out, and it is capable of providing insights into enzyme kinetics. The assay also offers a high-sensitivity and easily scalable method for identifying APOBEC3 inhibitors. This assay serves as a crucial addition to the existing APOBEC3 biochemical and cellular toolkit and possesses the versatility to be readily adapted into a high-throughput format for inhibitor discovery.

Integrating Evidence to Guide Use of Biologics and Small Molecules for Inflammatory Bowel Diseases.

Advances in science have led to the development of multiple biologics and small molecules for the treatment of inflammatory bowel diseases (IBDs). This growth in advanced medical therapies has been accompanied by an increase in methodological innovation to study and compare therapies. Guidelines provide an evidence-based approach to integrating therapies into routine practice, but they are often unable to provide timely recommendations as new therapies come to market, and they have limited incorporation of real-world evidence when making recommendations. This limits the scope and usability of guidelines, and a gap remains in defining how best to position and integrate advanced medical therapies for IBD. In this review, we provide a framework for clinicians and researchers to understand key differences in sources of evidence, how different methodologies are applied to study the comparative effectiveness of advanced medical therapies in IBD, and considerations for how these sources of evidence can be used to better integrate current guideline recommendations. Over time, we anticipate this framework will allow for a transition to living guidelines and/or practice recommendations.

Association of GLP-1 Receptor Agonists and Hepatocellular Carcinoma Incidence and Hepatic Decompensation in Patients With Type 2 Diabetes.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a leading cause of cancer death. HCC is preventable with about 70% of HCC attributable to modifiable risk factors. Glucagon-like peptide-1 receptor agonists (GLP-1RAs), Food and Drug Administration-approved medications for treating type 2 diabetes mellitus (T2DM), have pleiotropic effects on counteracting risk factors for HCC. Here we evaluate the association of GLP-1RAs with incident HCC risk in a real-world population. METHODS: This retrospective cohort included 1,890,020 patients with a diagnosis of T2DM who were prescribed GLP-1RAs or other non-GLP-1RA anti-diabetes medications and had no prior diagnosis of HCC. Incident (first-time) diagnosis of HCC and hepatic decompensating events during a 5-year follow-up was compared between cohorts of patients prescribed GLP-1 RAs vs other anti-diabetes medications. Time-to-first-event analysis was performed using Kaplan-Meier survival analysis with hazard ratio and 95% confidence interval calculated. RESULTS: GLP-1RAs were associated with a lower risk of incident HCC with hazard ratio of 0.20 [0.14-0.31], 0.39 [0.21-0.69], 0.63 [0.26-1.50] compared with insulin, sulfonylureas, and metformin, respectively. GLP-1RAs were associated with a significantly lower risk of hepatic decompensation compared with 6 other anti-diabetes medications. Reduced risks were observed in patients without and with different stages of fatty liver diseases, with more profound effects in patients without liver diseases. Similar findings were observed in patients with and without obesity and alcohol or tobacco use disorders. GLP-1RA combination therapies were associated with decreased risk for HCC and hepatic decompensations compared with monotherapies. CONCLUSIONS: GLP-1RAs were associated with a reduced risk of incident HCC and hepatic decompensation compared with other anti-diabetes medications in patients with T2DM. These findings provide supporting evidence for future studies to investigate the underlying mechanisms and their clinical use.