bluuebunny/crossref_metadata_2025 huggingface dataset:
The long-term effects of genomic selection: 2. Changes in allele frequencies of causal loci and new mutations
Authors: Wientjes Yvonne C J , Bijma Piter , van den Heuvel Joost , Zwaan Bas J , Vitezica Zulma G , Calus Mario P L
Published: July 2023

Genetic selection has been applied for many generations in animal, plant, and experimental populations. Selection changes the allelic architecture of traits to create genetic gain. It remains unknown whether the changes in allelic architecture are different for the recently introduced technique of genomic selection compared to traditional selection methods and whether they depend on the genetic architectures of traits. Here, we investigate the allele frequency changes of old and new causal loci under 50 generations of phenotypic, pedigree, and genomic selection, for a trait controlled by either additive, additive and dominance, or additive, dominance, and epistatic effects. Genomic selection resulted in slightly larger and faster changes in allele frequencies of causal loci than pedigree selection. For each locus, allele frequency change per generation was not only influenced by its statistical additive effect but also to a large extent by the linkage phase with other loci and its allele frequency. Selection fixed a large number of loci, and 5 times more unfavorable alleles became fixed with genomic and pedigree selection than with phenotypic selection. For pedigree selection, this was mainly a result of increased genetic drift, while genetic hitchhiking had a larger effect on genomic selection. When epistasis was present, the average allele frequency change was smaller (∼15% lower), and a lower number of loci became fixed for all selection methods. We conclude that for long-term genetic improvement using genomic selection, it is important to consider hitchhiking and to limit the loss of favorable alleles.
Testing Geology with Biology: Plate Tectonics and the Diversification of Microhylid Frogs in the Papuan Region
Authors: Hill Ethan C , Gao Diana F , Polhemus Dan A , Fraser Claire J , Iova Bulisa , Allison Allen , Butler Marguerite A
Published: July 2023

Synopsis

Studies of the Papuan region have provided fundamental insights into the evolutionary processes generating its exceptional biodiversity, but the influence of geological processes merits further study. Lying at the junction of five tectonic plates, this region has experienced a turbulent geological history that has not only produced towering mountains allowing elevational specialization and island archipelagos with varying degrees of isolation promoting vicariance, but also active margins where land masses have collided and been subsequently rifted apart creating a mosaic of intermixed terranes with vastly different geological histories. Asterophryine frogs are a hyperdiverse clade representing half the world’s microhylid diversity (over 360 species) centered on New Guinea and its satellite islands. We show that vicariance facilitated by geological history explains this far and wide distribution of a clade that should have poor dispersal abilities. We recovered a mainland tectonic unit, the East Papua Composite Terrane (EPCT), as the center of origin for Asterophryinae and no fewer than 71 instances of what appear to be long-distance dispersal events, 29 of which are between mainland regions, with 42 from the mainland to the islands, some presently as far as 200 km away from source populations over open ocean. Furthermore, we find strong support for a “Slow and Steady” hypothesis for the formation of the northern margin of New Guinea by many separate accretion events during the Miocene, over other major geological alternatives, consistent with the 20 M year age of the clade and arrival via the EPCT. In addition, the historical biogeography of our frogs strongly supports an affiliation of the Louisiade Archipelago and Woodlark Island with the Owen Stanley Range on the EPCT, and the recent proximity of the large New Britain Island. Our results show that Asterophryinae did not have to repeatedly and independently disperse across large ocean barriers to the offshore islands, against the predictions of island biogeography theory, but that the current distribution can be explained through vicariance and short-distance oceanic dispersal as historical land connections disappeared and islands slowly became separated from each other. We show that islands have a life history, changing in distance from other land masses, with consequent opportunities for dispersal, isolation, and cladogenesis of their biotas. More broadly, we can begin to see how the geological history of the Papuan region can result in the rapid accumulation and staggering number of extant species.
Microbiology of street food: understanding risks to improve safety
Authors: Andrade Anderson Assunção , Paiva Aline Dias , Machado Alessandra Barbosa Ferreira
Published: July 2023

Street foods play important socioeconomic and cultural roles and are popular worldwide. In addition to providing convenient and low-cost meals for urban populations, street food offers an essential source of income for vendors, especially women, and it can reflect traditional local culture, which is an important attraction for tourists. Despite these benefits, the microbiological safety of street food has become a worldwide concern because it is often prepared and sold under inadequate safety conditions, without legal control and sanitary surveillance. Consequently, high counts of fecal indicator bacteria and several foodborne pathogens have been detected in street foods. This review provides insight into the microbiology of street food, focus on the associated microbiological safety aspects and main pathogens, and the global status of this important economic activity. Furthermore, the need to apply molecular detection rather than traditional culture-based methods is discussed to better understand the actual risks of microbial infection associated with street foods. Recognition is always the first step toward addressing a problem.
Utilizing standardized nursing terminologies in implementing an AI-powered fall-prevention tool to improve patient outcomes: a multihospital study
Authors: Cho Insook , Cho Jiseon , Hong Jeong Hee , Choe Wha Suk , Shin HyeKyeong
Published: July 2023

Objectives

Standardized nursing terminologies (SNTs) are necessary to ensure consistent knowledge expression and compare the effectiveness of nursing practice across settings. This study investigated whether SNTs can support semantic interoperability and outcoming tracking over time by implementing an AI-powered CDS tool for fall prevention across multiple EMR systems.

Materials and Methods

The study involved 3 tertiary academic hospitals and 1 public hospital with different EMR systems and nursing terms, and employed an AI-powered CDS tool that determines the fall risk within the next hour (prediction model) and recommends tailored care plans (CDS functions; represented by SNTs). The prediction model was mapped to local data elements and optimized using local data sets. The local nursing statements in CDS functions were mapped using an ICNP-based inpatient fall-prevention catalog. Four implementation models were compared, and patient outcomes and nursing activities were observed longitudinally at one site.

Results

The postimplementation approach was practical for disseminating the AI-powered CDS tool for nursing. The 4 hospitals successfully implemented prediction models with little performance variation; the AUROCs were 0.8051–0.9581. The nursing process data contributed markedly to fall-risk predictions. The local nursing statements on preventing falls covered 48.0%–86.7% of statements. There was no significant longitudinal decrease in the fall rate (P = .160, 95% CI = −1.21 to 0.21 per 1000 hospital days), but rates of interventions provided by nurses were notably increased.

Conclusion

SNTs contributed to achieving semantic interoperability among multiple EMR systems to disseminate AI-powered CDS tools and automatically track nursing and patient outcomes.
Sleep Problems in Pediatric Disorders of Gut–Brain Interaction: A Systematic Review
Authors: Robbertz Abigail S , Shneider Caitlin , Cohen Lindsey L , Reed Bonney
Published: July 2023

Objective

Disorders of gut–brain interaction (DGBIs) are common, and findings are mixed on rates of sleep problems (e.g., sleep quality) in pediatric populations. A clear understanding of sleep problems in pediatric DGBIs is needed as sleep challenges might negatively impact symptoms and prognoses. The aims of this systematic review are to (1) describe the prevalence and types of sleep problems in pediatric patients with DGBIs and examine differences by DGBI diagnosis and (2) examine the relationship among sleep problems and pain, mood, and functional outcomes in pediatric patients with DGBIs.

Methods

We searched PubMed, PsycInfo, CINAHL, and Medline in June 2022; articles were included if they enrolled ≤19 years old with a DGBI, used a quantitative assessment of sleep problems, and were available in English. The Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies was used to assess study quality. We used a protocol to systematically pull and tabulate data across articles with quality assessment ratings.

Results

Twenty-four articles with 110,864 participants across 9 countries were included, with most studies being of moderate to weak quality. Patients with DGBIs reported more sleep problems than healthy peers, and some research reviewed found that patients with IBS had more sleep problems than other DGBI diagnoses. Sleep problems in DGBIs were related to worse mood, pain, and functional outcomes.

Conclusion

Pediatric patients with DGBIs are experiencing sleep problems that can impact outcomes. Screening for sleep problems and targeted treatment is needed to best support these patients.
Spectrum of kinetic-Alfvén-wave turbulence: intermittency or tearing mediation?
Authors: Zhou Muni , Liu Zhuo , Loureiro Nuno F
Published: July 2023

We investigate the spectral properties of the electromagnetic fluctuations of sub-ion scale turbulence in weakly collisional, low-beta plasmas using a two-field isothermal gyrofluid model. The numerical results strongly support a description of the turbulence as a critically balanced Kolmogorov-like cascade of kinetic Alfvén wave fluctuations, as amended by previous studies to include intermittency effects. The measured universal index of the energy spectra from systems with different flux-unfreezing mechanisms excludes the role of tearing mediation in determining the spectra. The fluctuations remain isotropic in the plane perpendicular to the strong background magnetic fields as they cascade to smaller scales, which explains the absence of tearing mediation. The calculation of high-order, multipoint structure functions of magnetic fluctuations suggests that the intermittent structures have a quasi-2D, sheet-type morphology. These results are useful for explaining recent observations of the spectrum and structure of magnetic and density fluctuations in the solar wind at sub-proton scales, and are relevant for modelling the energy dissipation in a broad range of astrophysical systems.
Closure relations of synchrotron self-compton in afterglow-stratified medium and Fermi-LAT detected gamma-ray bursts
Authors: Fraija Nissim , Dainotti Maria G , Kamenetskaia B Betancourt , Levine D , Galvan-Gamez A
Published: July 2023

The Second Gamma-ray Burst Catalogue (2FLGC) was announced by the Fermi Large Area Telescope (Fermi-LAT) Collaboration. It includes 29 bursts with photon energy higher than 10 GeV. Gamma-ray burst (GRB) afterglow observations have been adequately explained by the classic synchrotron forward-shock model, however, photon energies greater than 10 GeV from these transient events are challenging, if not impossible, to characterize using this afterglow model. Recently, the closure relations (CRs) of the synchrotron self-Compton (SSC) forward-shock model evolving in a stellar wind and homogeneous medium was presented to analyse the evolution of the spectral and temporal indexes of those bursts reported in 2FLGC. In this work, we provide the CRs of the same afterglow model, but evolving in an intermediate density profile (∝r−k) with 0 ≤ k ≤ 2.5, taking into account the adiabatic/radiative regime and with/without energy injection for any value of the electron spectral index. The results show that the current model accounts for a considerable subset of GRBs that cannot be interpreted in either stellar-wind or homogeneous afterglow SSC model. The analysis indicates that the best-stratified scenario is most consistent with k = 0.5 for no-energy injection and k = 2.5 for energy injection.
Big flares from small stars: detecting flares from faint low-mass stars with NGTS full-frame images
Authors: Jackman James A G , Wheatley Peter J , West Richard G , Gill Sam , Jenkins James S
Published: July 2023

High-cadence observations of high-energy stellar flares from cool and ultracool dwarfs are often limited by the faint nature of their host stars. Many low-mass sources cannot be detected in quiescence by photometric surveys, meaning they are not targeted for high-cadence observations. This reduces the chances of detecting the rarest high-energy flare events. We used the 13-s cadence full-frame images of Next-Generation Transit Survey (NGTS) to search for flares from M and L dwarfs. This included stars that were too faint to detect in quiescence. We detect 160 flares from 135 stars, with spectral types ranging from M3 to L2.5. We use our sample to study the energies, amplitudes and durations of flares from M and L dwarfs. We measure bolometric flare energies up to 4.5 × 1034 erg for ultracool dwarfs, but conclude that we have not reached a maximum limit to the energy released during white-light flares. We use our results to study the incidence rate of flares of mid- and late-M stars, not accounting for age or binarity, and find that 1.4 ± 0.4 and $9^{+16}_{-3}$ per cent of mid- and late-M stars, respectively, exhibit flares with amplitudes above 1 mag in the NGTS bandpass. Future studies with greater numbers of NGTS fields will expand upon this work.
Long-lasting activity of asteroid (248370) 2005 QN173
Authors: Ivanova Oleksandra , Licandro Javier , Moreno Fernando , Luk’yanyk Igor , Markkanen Johannes , Tomko Dušan , Husárik Marek , Cabrera-Lavers Antonio , Popescu Marcel , Shablovinskaya Elena , Shubina Olena
Published: July 2023

We present the results of observations of asteroid (248370) QN173 obtained during July 2021–January 2022 with three telescopes. Our analysis revealed the presence of the dust tail for about half of a year. The direct images of the asteroid were obtained with broad-band filters. No emissions were revealed in the spectra, and the spectrum of the asteroid closely matched that of a C-type asteroid. Created colour and linear polarization variations along the tail were analysed. The asteroid demonstrated a redder colour compared to the Sun. Dramatic changes in dust productivity obtained in different filters were not detected. The g − r colour changes from 0.2m to 0.7m over the coma, and the linear polarization degree varies from about 1.2 per cent to 0.2 per cent and from −0.2 per cent to −1.5 per cent at the phase angle of 23.2° and 8.16°. The total dust mass ejected until the latest observation on October 10 is 4.2 × 107 kg, with a maximum rate of 2.6 kg s−1 based on the Monte Carlo modelling of the dust tail. The estimated asteroid size is 1.3 km. It is shown that large particles are concentrated around the nucleus, whereas smaller ones dominate in the tail. The evolution of (248370) QN173 orbit and the orbits of the sample of the 464 short-periodic comets were followed. Ten of them approached the asteroid’s orbit. These objects are not genetically related, despite very close distance of their orbits for a relatively long time.
Revised orbits of the two nearest Jupiters
Authors: Feng Fabo , Butler R Paul , Vogt Steven S , Holden Bradford , Rui Yicheng
Published: July 2023

With its near-to-mid-infrared high-contrast imaging capabilities, JWST is ushering us into a golden age of directly imaging Jupiter-like planets. As the two closest cold Jupiters, ε Ind A b and ε Eridani b have sufficiently wide orbits and adequate infrared emissions to be detected by JWST. To detect more Jupiter-like planets for direct imaging, we develop a gost-based method to analyse radial velocity data and multiple Gaia data releases simultaneously. Without approximating instantaneous astrometry by catalogue astrometry, this approach enables the use of multiple Gaia data releases for detection of both short-period and long-period planets. We determine a mass of $2.96_{-0.38}^{+0.41}$ MJup and a period of $42.92_{-4.09}^{+6.38}$ yr for ε Ind A b. We also find a mass of $0.76_{-0.11}^{+0.14}$ MJup , a period of $7.36_{-0.05}^{+0.04}$ yr, and an eccentricity of 0.26$_{-0.04}^{+0.04}$ MJup, for ε Eridani b. The eccentricity differs from that given by some previous solutions, probably due to the sensitivity of orbital eccentricity to noise modelling. Our work refines the constraints on orbits and masses of the two nearest Jupiters and demonstrate the feasibility of using multiple Gaia data releases to constrain Jupiter-like planets.
How difficult is it to interpret subjective well-being questions during crises? Evidence from the onset of conflict in Yemen
Authors: Tandon Sharad
Published: July 2023

Subjective well-being (SWB) measures, such as satisfaction with income, are increasingly being used to measure changes in well-being in response to policy changes and shocks. However, large policy changes or shocks themselves might cause individuals to change how they answer SWB questions in ways that have little to do with changes in objective well-being measures. For example, respondent-specific scales that individuals use to respond to SWB questions (e.g. threshold of income required to be satisfied) might change at the same time that income is changing following a shock. We illustrate the importance of this concern following the onset of conflict in Yemen, where households reported a large improvement in SWB across a range of different dimensions despite large declines in nearly all traditional and objective measures of well-being.
Improving the Regional Innovation Scoreboard for policy: how about innovation efficiency?
Authors: Teirlinck Peter , Spithoven André
Published: July 2023

This paper aims to improve the Regional Innovation Scoreboard as an instrument for policy-making. Dynamic slack–based models of data envelopment analysis to measure innovation output efficiency in 207 European regions demonstrate that the scale-based performance classification of the Scoreboard into ‘leader’, ‘strong’, ‘moderate’, and ‘modest’ innovator regions inadequately reflects differences in efficiency in transforming knowledge inputs into innovation outputs. We reveal a non-monotonic relation between scale-based and efficiency-based performance and substantial heterogeneity among the reasons for inefficiency among regions within each of the four scale-based performance classes of regions. Our findings argue for an extension of the current scale-based use of the Scoreboard by adding an efficiency-based measurement of the innovation process. Doing so addresses the tendency in policy design towards an increased focus on the efficient use of scarce resources in place-based policy approaches and strengthens the application of the Scoreboard as an informative decision-making tool.
Malignant Proliferating Pilar Tumor
Authors: Moran Jakob M.T. , DeSimone Mia S. , Mariño-Enríquez Adrián , Russell-Goldman Eleanor E. , Fletcher Christopher D.M. , Mochel Mark C. , Hoang Mai P.
Published: July 2023

Proliferating pilar tumors are rare neoplasms that differentiate toward the outer sheath near the isthmus and can rarely undergo malignant transformation. We performed histopathologic evaluation on 26 benign proliferating pilar tumor (BPPT) and 17 malignant proliferating pilar tumor (MPPT). Ki-67 and p53 immunostains were performed on 13 BPPT and 10 MPPT. Six MPPT cases were successfully analyzed by a next-generation sequencing platform which surveyed exonic DNA sequences of 447 cancer genes and 191 regions across 60 genes for rearrangement detection. Patient demographics and clinical characteristics were similar between the BPPT and MPPT groups. Follow-up data of 16 of 17 MPPT (median, 25 mo) showed metastasis in 1 MPPT. The histologic features associated with MPPT include size >2.5 cm, adjacent desmoplastic stroma, small nests or cords of atypical epithelium in surrounding stroma, irregular infiltration or borders, abnormal keratinization, large hyperchromatic nuclei, prominent nucleoli, severe cytologic atypia, nuclear pleomorphism, necrosis, and increased mitotic figures. MPPT harbors copy number gains of 15q and losses of 6p and 6q, findings previously reported in BPPT. However, MPPT harbors frequent TP53 mutations as molecular markers of progression. Different from cutaneous squamous cell carcinoma, MPPT more frequently demonstrates low tumor mutational burden and typically lacks a UV signature, suggestive of a different etiologic pathway than squamous cell carcinoma. In summary, with a median follow-up of 25 months, this study shows that MPPT is a biologically indolent carcinoma with rare metastasis. Molecular analyses suggest a non–UV-related pathogenesis with frequent TP53 aberration.
Disease exacerbation by fibroblast inclusion in Duchenne Muscular Dystrophy MYOrganoids reveals limitations of microdystrophin therapeutic efficacy
Authors: Palmieri Laura , Pili Louna , Jaber Abbass , Hong Ai Vu , Marcello Matteo , El-Khoury Riyad , Brochier Guy , Bigot Anne , Israeli David , Richard Isabelle , Albini Sonia
Published: July 2023

Current gene therapy approaches for Duchenne muscular dystrophy (DMD) using AAV-mediated delivery of microdystrophin (µDys) have shown limited efficacy in patients, contrasting with the favorable outcomes observed in animal models. This discrepancy is partly due to the lack of models that replicate key pathogenic features associated with the severity of the human disease, such as fibrosis and muscle dysfunction. To tackle the translational gap, we develop a human disease model that recapitulates these critical hallmarks of DMD for a more predictive therapeutic investigation. Using a muscle engineering approach, we generate MYOrganoids from iPSC-derived muscle cells co-cultured with fibroblasts that enable functional maturation for muscle force analysis upon contractions. Incorporation of DMD fibroblasts within DMD iPSC-derived muscle cells allows phenotypic exacerbation by unraveling of fibrotic signature and fatiguability through cell-contact-dependent communication. Although µDys gene transfer partially restores muscle resistance, it fails to fully restore membrane stability and reduce profibrotic signaling. These findings highlight the persistence of fibrotic activity post-gene therapy in our human DMD system, an unparalleled aspect in existing DMD models, and provide the opportunity to explore the underlying mechanisms of dysregulated cellular communication to identify anti-fibrotic strategies empowering gene therapy efficacy.
Chronic BCR signaling generates and maintains age-associated B cells from anergic B cells
Authors: Imabayashi Keisuke , Yada Yutaro , Ushijima Miho , Yoshimura Motoki , Iwasaki Takeshi , Akashi Koichi , Niiro Hiroaki , Baba Yoshihiro
Published: July 2023

Accumulation of age-associated B cells (ABCs) with autoreactive properties contributes to the pathogenesis of autoimmune diseases1–5. However, the mechanisms whereby ABCs are generated and maintained are not understood1, 2, 4. Here, we show that continuous stimulation of the B-cell receptor (BCR) with self-antigens plays a crucial role in ABC generation from anergic B cells and that this signal is vital for sustaining ABCs during aging and autoimmunity. In ABCs, BCR signaling was constitutively activated and the surface BCR was internalizedin vivo, as occurs in autoreactive B cells chronically exposed to self-antigens6. With aging, ABCs were generated from autoreactive anergic B cells, but not from B cells expressing non-self-reactive BCR.In vitrostimulation of anergic B cells with self-antigen, interleukin-21, and Toll-like receptor 7/9 agonists promoted their differentiation to ABCs. Furthermore, the cellular phenotype of ABCs in Bm12-induced lupus mice7, 8resembled that of ABCs in aged mice, showing activation of BCR signaling, expression of activation markers, and BCR internalization. Importantly, Btk was persistently activated in ABCs of aged/autoimmune mice and humans with lupus. Pharmacological Btk inhibition resulted in a marked reduction in the number of ABCs and pathogenicity in lupus mice. Our findings have implications for accumulating ABCs and developing therapies for autoimmune diseases.
Automatic design of gene regulatory mechanisms for spatial pattern formation
Authors: Mousavi Reza , Lobo Daniel
Published: July 2023

Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms—including the number of genes necessary for the formation of the target pattern—we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover pattern-producing genetic circuits.
A comprehensive experimental comparison between federated and centralized learning
Authors: Garst Swier , Dekker Julian , Reinders Marcel
Published: July 2023

Purpose

Federated learning is an upcoming machine learning paradigm which allows data from multiple sources to be used for training of classifiers without the data leaving the source it originally resides. This can be highly valuable for use cases such as medical research, where gathering data at a central location can be quite complicated due to privacy and legal concerns of the data. In such cases, federated learning has the potential to vastly speed up the research cycle. Although federated and central learning have been compared from a theoretical perspective, an extensive experimental comparison of performances and learning behavior still lacks.

Methods

We have performed a comprehensive experimental comparison between federated and centralized learning. We evaluated various classifiers on various datasets exploring influences of different sample distributions as well as different class distributions across the clients.

Results

The results show similar performances under a wide variety of settings between the federated and central learning strategies. Federated learning is able to deal with various imbalances in the data distributions. It is sensitive to batch effects between different datasets when they coincide with location, similar as with central learning, but this setting might go unobserved more easily.

Conclusion

Federated learning seems robust to various challenges such as skewed data distributions, high data dimensionality, multiclass problems and complex models. Taken together, the insights from our comparison gives much promise for applying federated learning as an alternative to sharing data.
Ribosome subunit attrition and activation of the p53–MDM4 axis dominate the response of MLL-rearranged cancer cells to WDR5 WIN site inhibition
Authors: Howard Gregory C. , Wang Jing , Rose Kristie Lindsey , Jones Camden , Patel Purvi , Tsui Tina , Florian Andrea C. , Vlach Logan , Lorey Shelly L. , Grieb Brian C. , Smith Brianna N. , Slota Macey J. , Reynolds Elizabeth M. , Goswami Soumita , Savona Michael R. , Mason Frank M. , Lee Taekyu , Fesik Stephen W. , Liu Qi , Tansey William P.
Published: July 2023

The chromatin-associated protein WD Repeat Domain 5 (WDR5) is a promising target for cancer drug discovery, with most efforts blocking an arginine-binding cavity on the protein called the "WIN" site that tethers WDR5 to chromatin. WIN site inhibitors (WINi) are active against multiple cancer cell types in vitro, the most notable of which are those derived from MLL-rearranged (MLLr) leukemias. Peptidomimetic WINi were originally proposed to inhibit MLLr cells via dysregulation of genes connected to hematopoietic stem cell expansion. Our discovery and interrogation of small molecule WIN site inhibitors, however, revealed that they act in MLLr cell lines to suppress ribosome protein gene (RPG) transcription, induce nucleolar stress, and activate p53. Because there is no precedent for an anti-cancer strategy that specifically targets RPG expression, we took an integrated multi-omics approach to further interrogate the mechanism of action of WINi in MLLr cancer cells. We show that WINi induce depletion of the stock of ribosomes, accompanied by a broad yet modest translational choke and changes in alternative mRNA splicing that inactivate the p53 antagonist MDM4. We also show that WINi are synergistic with agents including venetoclax and BET-bromodomain inhibitors. Together, these studies reinforce the concept that WINi are a novel type of ribosome-directed anti-cancer therapy and provide a resource to support their clinical implementation in MLLr leukemias and other malignancies.
Soft robotics-enabled large animal model of HFpEF hemodynamics for device testing
Authors: Rosalia Luca , Ozturk Caglar , Wang Sophie X. , Quevedo-Moreno Diego , Saeed Mossab Y. , Mauskapf Adam , Roche Ellen T.
Published: July 2023

Heart failure with preserved ejection fraction (HFpEF) is a major challenge in cardiovascular medicine, accounting for approximately 50% of all cases of heart failure. Due to the lack of effective therapies for this condition, the mortality associated with HFpEF remains higher than that of most cancers. Despite the ongoing efforts, no medical device has yet received FDA approval. This is largely due to the lack of an in vivo model of the HFpEF hemodynamics, resulting in the inability to evaluate device effectiveness in vivo prior to clinical trials. Here, we describe the development of a highly tunable porcine model of HFpEF hemodynamics using implantable soft robotic sleeves, where controlled actuation of a left ventricular and an aortic sleeve can recapitulate changes in ventricular compliance and afterload associated with a broad spectrum of HFpEF hemodynamic phenotypes. We demonstrate the feasibility of the proposed model in preclinical testing by evaluating the hemodynamic response of the model post-implantation of an interatrial shunt device, which was found to be consistent with findings from in silico studies and clinical trials. This work addresses several of the limitations associated with previous models of HFpEF, such as their limited hemodynamic fidelity, elevated costs, lengthy development time, and low throughput. By showcasing exceptional versatility and tunability, the proposed platform has the potential to revolutionize the current approach for HFpEF device development and selection, with the goal of improving the quality of life for the 32 million people affected by HFpEF worldwide.
Eyes on nature: Embedded vision cameras for multidisciplinary biodiversity monitoring
Authors: Darras Kevin F.A. , Balle Marcel , Xu Wenxiu , Yan Yang , Zakka Vincent G. , Toledo-Hernández Manuel , Sheng Dong , Lin Wei , Zhang Boyu , Lan Zhenzhong , Fupeng Li , Wanger Thomas C.
Published: July 2023

Global environmental challenges require comprehensive data to manage and protect biodiversity. Currently, vision-based biodiversity monitoring efforts are mixed, incomplete, human-dependent, and passive. To tackle these issues, we present a portable, modular, low-power device with embedded vision for biodiversity monitoring. Our camera uses interchangeable lenses to resolve barely visible and remote subjects, as well as customisable algorithms for blob detection, region-of-interest classification, and object detection to identify targets. We showcase our system in six case studies from the ethology, landscape ecology, agronomy, pollination ecology, conservation biology, and phenology disciplines. Using the same devices, we discovered bats feeding on durian tree flowers, monitored flying bats and their insect prey, identified nocturnal insect pests in paddy fields, detected bees visiting rapeseed crop flowers, triggered real-time alerts for waterbirds, and tracked flower phenology over months. We measured classification accuracies between 55% and 96% in our field surveys and used them to standardise observations over highly-resolved time scales. The cameras are amenable to situations where automated vision-based monitoring is required off the grid, in natural and agricultural ecosystems, and in particular for quantifying species interactions. Embedded vision devices such as this will help addressing global biodiversity challenges and facilitate a technology-aided global food systems transformation.
Grow now, pay later: when should a bacterium go into debt?
Authors: Lopez Jaime G. , Erez Amir
Published: July 2023

Microbes grow in a wide variety of environments and must balance growth and stress resistance. Despite the prevalence of such trade-offs, understanding of their role in non-steady environments is limited. In this study, we introduce a mathematical model of “growth debt”, where microbes grow rapidly initially, paying later with slower growth or heightened mortality. We first compare our model to a classical chemostat experiment, validating our proposed dynamics and quantifyingEscherichia coli’s stress resistance dynamics. Extending the chemostat theory to include serial-dilution cultures, we derive phase diagrams for the persistence of “debtor” microbes. We find that debtors cannot coexist with non-debtors if “payment” is increased mortality but can coexist if it lowers enzyme affinity. Surprisingly, weak noise considerably extends the persistence of resistance elements, pertinent for antibiotic resistance management. Our microbial debt theory, broadly applicable across many environments, bridges the gap between chemostat and serial dilution systems.

Teaser

Microbes can sacrifice future growth for immediate gains, how does this trade-off shape the structure of microbial communities?
Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data
Authors: Lee GaRyoung , Lee Sang Mi , Lee Sungyoung , Jeong Chang Wook , Song Hyojin , Lee Sang Yup , Yun Hongseok , Koh Youngil , Kim Hyun Uk
Published: July 2023

Background

Oncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to a large number of metabolites in a cell and the presence of multiple genes associated with cancer development.

Results

Here we report the development of a computational workflow that predicts metabolite-gene-pathway sets (MGPs). MGPs present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate MGPs. A GEM is a computational model that predicts reaction fluxes at a genome scale, and can be constructed in a cell-specific manner by using omics data (e.g., RNA-seq). The computational workflow is first validated by comparing the resulting metabolite-gene (MG) pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from 17 acute myeloid leukemia samples and 21 renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the MGPs predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting MGPs is also discussed.

Conclusions

Validation of the MGP-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting MGPs will help identify novel oncometabolites, and also suggest cancer treatment strategies.
Dynamic Structure-based Pharmacophore Models for Virtual Screening of Small Molecule Libraries Targeting the YB-1
Authors: Oktay Lalehan , Sayyah Ehsan , Durdağı Serdar
Published: July 2023

In drug discovery, ligand-based techniques offer rapid screening, whereas structure-based approaches provide deeper insights but are time-consuming. Hybrid methods like structure-based pharmacophore models combine advantages for accurate screening of large ligand libraries. However, there are substantial limits to build structure-based pharmacophore models. Static models relying on a single co-crystallized structure or docking pose often fall short in capturing the dynamic nature of binding interactions. In this study, we present dynamic structure-based pharmacophore models, aimed at better representing physiological conditions and addressing these challenges. The urgent need for improved cancer treatment has led to the search for new chemotherapeutic strategies. Y box binding protein 1 (YB-1) is a multifunctional protein associated with tumor progression and treatment resistance in various cancers. For the first time in the literature, our study utilizes a known small molecule YB-1 inhibitor (SU056) bound to the active regions of the RNA-binding sites to develop dynamic structure-based pharmacophores. These models were then used in the screening of large ligand libraries.
An improved epigenetic counter to track mitotic age in normal and precancerous tissues
Authors: Zhu Tianyu , Tong Huige , Du Zhaozhen , Beck Stephan , Teschendorff Andrew E.
Published: July 2023

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC’s mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.
A Hypothesis-Based Hop Microbiology Laboratory Module Testing the Plausibility of the Mythical Origin of the India Pale Ale (IPA)
Authors: Pineda Julio Molina , Scholes Amanda N. , Lewis Jeffrey A.
Published: July 2023

As one of the most famous fermented drinks in the world, beer is an especially relatable topic for microbiology courses. Here, we describe a short and easily adaptable module based on the antibacterial properties of hops used in brewing. By the 15thcentury, beer recipes included hops (the flower of theHumulus lupulusplant) as a bittering agent and antimicrobial. By the 19thcentury, the highly-hopped Indian Pale Ale (IPA) became popular, and a modern myth has emerged that IPAs were invented to survive long ocean voyages such as from Britain to India. With that myth in mind, we designed a hypothesis-driven microbiology lab module that tests the plausibility of this brewing myth— namely that highly-hopped beers possess enough antibacterial activity to prevent spoilage, while lowly-hopped beers do not. The overall design of the module is to test the antimicrobial properties of hops using petri plates containing varying concentrations of hop extract. The module includes hypothesis generation and testing related to bacterial physiology and morphology (hops are not equally effective against gram-positive and gram-negative bacteria), and to mechanisms of antimicrobial resistance (as beer spoilage bacteria have repeatedly evolved hop resistance). Pre and post assessment showed that students made significant gains in the learning objectives for the module, which encourages critical thinking and hypothesis testing by linking microbial physiology and antimicrobial resistance to an important and topical real-world application.
Neuronal NPR-15 modulates molecular and behavioral immune responses via the amphid sensory neuron-intestinal axis inC. elegans
Authors: Otarigho Benson , Butts Anna Frances , Aballay Alejandro
Published: July 2023

The survival of hosts during infections relies on their ability to mount effective molecular and behavioral immune responses. Despite extensive research on these defense strategies in various species, including the model organismCaenorhabditis elegans, the neural mechanisms underlying their interaction remain poorly understood. Previous studies have highlighted the role of neural G protein-coupled receptors (GPCRs) in regulating both immunity and pathogen avoidance, which is particularly dependent on aerotaxis. To address this knowledge gap, we conducted a screen of mutants in neuropeptide receptor family genes. We found that loss-of-function mutations innpr-15activated immunity while suppressing pathogen avoidance behavior. Through further analysis, NPR-15 was found to regulate immunity by modulating the activity of key transcription factors, namely GATA/ELT-2 and TFEB/HLH-30. Surprisingly, the lack of pathogen avoidance ofnpr-15mutant animals was not influenced by oxygen levels. Moreover, our studies revealed that the amphid sensory neuron ASJ is involved in mediating the immune and behavioral responses orchestrated by NPR-15. Additionally, NPR-15 was found to regulate avoidance behavior via the TRPM gene, GON-2, which may sense the intestinal distension caused by bacterial colonization to elicit pathogen avoidance. Our study contributes to a broader understanding of host defense strategies and mechanisms underlining the interaction between molecular and behavioral immune responses.
Spatial profiling of ovarian clear cell carcinoma reveals immune-hot features
Authors: Tai Ya-Ting , Lin Wei-Chou , Wang Duncan Yi-Te , Ye Jieru , Tan Tuan Zea , Wei Lin-Hung , Huang Ruby Yun-Ju
Published: July 2023

Introduction

OCCC has high incidence in Asia with frequent occurrence at early stage but without sufficient data on molecular stratification for high-risk patients. Recently, immune-hot features have been proposed as an indicator for poor prognosis for early-stage OCCC. Specific patterns of intra-tumoral heterogeneity (ITH) associated with immune-hot features need to be defined.

Methods

Formalin-fixed paraffine embedded (FFPE) tumor sections from 10 early-stage OCCC patients were included. Digital Spatial Profiling (DSP) of 18 protein targets was conducted by using the nanoString GeoMx system to profile selected regions of interest (ROIs) based on the reference H&E staining morphology. Areas of illumination (AOIs) were defined according to ROI segmentation by the fluorescence signals of visualization markers pan-cytokeratin (PanCK), CD45, or DNA.

Results

Unsupervised hierarchical clustering of 252 AOIs from 229 ROIs showed that PanCK segments expressed different combinations of immune markers suggestive of immune mimicry features. Three immune-hot clusters were identified: granzyme B high (C1-a), immune signal high (C1-b) and immune-like cells (C1-c); two immune-cold clusters were identified: fibronectin-high (C2-a) and signal-cold (C2-b). Immune cells around C1-b and C1-c PanCK+ AOIs were tumor infiltrating immune cells (TIIs) with higher expression of CD68, while those around C1-a, C2-a and C2-b PanCK+ AOIs were non-TIIs with higher expression of SMA. C1-c and C2-a PanCK+ AOIs were associated with OCCC recurrence. TIIs had higher frequencies in C1-b and C1-c PanCK+ AOIs and were associated with OCCC recurrence. Correlating with morphology, tumor samples with recurrence showed higher frequency of papillary pattern. Plus, ROIs with papillary pattern had extremely high frequency of PanCK segments of C1-c feature, higher frequency of TIIs, and macrophage lineage immune mimicry with high intensity of CD68.

Conclusions

Spatial profiling of early-stage OCCC tumors revealed that immune mimicry of tumor cells, the presence of TIIs, and papillary pattern in morphology were associated with recurrence.
MethyLasso: a segmentation approach to analyze DNA methylation patterns and identify differentially methylation regions from whole-genome datasets
Authors: Balaramane Delphine , Spill Yannick G. , Weber Michaël , Bardet Anaïs Flore
Published: July 2023

DNA methylation is an epigenetic mark involved in the regulation of gene expression and patterns of DNA methylation anticorrelates with chromatin accessibility and transcription factor binding. DNA methylation can be profiled at the single cytosine resolution in the whole genome and has been performed in many cell types and conditions. Computational approaches are then essential to study DNA methylation patterns in a single condition or capture dynamic changes of DNA methylation levels across conditions. Towards this goal, we developed MethyLasso, a new approach based on the segmentation of DNA methylation data, that enables the identification of low-methylated regions (LMRs), unmethylated regions (UMRs), DNA methylation valleys (DMVs) and partially methylated domains (PMDs) in a single condition as well as differentially methylated regions (DMRs) between two conditions. We performed a rigorous benchmarking comparing existing approaches by evaluating the number, size, level of DNA methylation, boundaries, CpG content and coverage of the regions using several real datasets as well as the sensitivity and precision of the approaches using simulated data and show that MethyLasso performs best overall. MethyLasso is freely available athttps://github.com/abardet/methylasso.