Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating morphological, molecular and cytogenetic data for F2 sea turtle hybrids diagnosis revealed balanced chromosomal sets

Hybridization could be considered part of the evolutionary history of many species. The hybridization among sea turtle species on the Brazilian coast is atypical and occurs where nesting areas and reproductive seasons overlap. Integrated analysis of morphology and genetics is still scarce, and there is no evidence of the parental chromosome set distribution in sea turtle interspecific hybrids. In this study, chromosome markers previously established for pure sea turtle species were combined with morphological and molecular analyses aiming to recognize genetic composition and chromosome sets in possible interspecific hybrids initially identified by mixed morphology. The data showed that one hybrid could be an F2 individual among Caretta caretta × Eretmochelys imbricata × Chelonia mydas, and another is resulting from backcross between C. caretta × Lepidochelys olivacea. Native alleles of different parental lineages were reported in the hybrids, and, despite this, it was verified that the hybrid chromosome sets were still balanced. Thus, how sea turtle hybridism can affect genetic features in the long term is a concern, as the implications of the crossing‐over in hybrid chromosomal sets and the effects on genetic function are still unpredictable.
Predicting Ophthalmic Clinic Non-attendance using Machine Learning

Background Ophthalmic clinic non-attendance in New Zealand is associated with poorer health outcomes, marked inequities and costs NZD$30m per annum. Initiatives to improve attendance typically involve expensive and ineffective brute-force strategies. Purpose To develop machine learning models to accurately predict ophthalmic clinic non-attendance.
Chemical and isotopic systematics of oceanic basalts: implications for mantle composition and processes

Summary Trace-element data for mid-ocean ridge basalts (MORBs) and ocean island basalts (OIB) are used to formulate chemical systematics for oceanic basalts. The data suggest that the order of trace-element incompatibility in oceanic basalts is Cs ≈ Rb ≈ (≈ Tl) ≈ Ba(≈ W) > Th > U ≈ Nb = Ta ≈ K > La > Ce ≈ Pb > Pr (≈ Mo) ≈ Sr > P ≈ Nd (> F) > Zr = Hf ≈ Sm > Eu ≈ Sn (≈ Sb) ≈ Ti > Dy ≈ (Li) > Ho = Y > Yb. This rule works in general and suggests that the overall fractionation processes operating during magma generation and evolution are relatively simple, involving no significant change in the environment of formation for MORBs and OIBs. In detail, minor differences in element ratios correlate with the isotopic characteristics of different types of OIB components (HIMU, EM, MORB). These systematics are interpreted in terms of partial-melting conditions, variations in residual mineralogy, involvement of subducted sediment, recycling of oceanic lithosphere and processes within the low velocity zone. Niobium data indicate that the mantle sources of MORB and OIB are not exact complementary reservoirs to the continental crust. Subduction of oceanic crust or separation of refractory eclogite material from the former oceanic crust into the lower mantle appears to be required. The negative europium anomalies observed in some EM-type OIBs and the systematics of their key element ratios suggest the addition of a small amount (⩽1% or less) of subducted sediment to their mantle sources. However, a general lack of a crustal signature in OIBs indicates that sediment recycling has not been an important process in the convecting mantle, at least not in more recent times (⩽2 Ga). Upward migration of silica-undersaturated melts from the low velocity zone can generate an enriched reservoir in the continental and oceanic lithospheric mantle. We propose that the HIMU type (eg St Helena) OIB component can be generated in this way. This enriched mantle can be re-introduced into the convective mantle by thermal erosion of the continental lithosphere and by the recycling of the enriched oceanic lithosphere back into the mantle.
Eflornithine as Postimmunotherapy Maintenance in High-Risk Neuroblastoma: Externally Controlled, Propensity Score–Matched Survival Outcome Comparisons

PURPOSE Long-term survival in high-risk neuroblastoma (HRNB) is approximately 50%, with mortality primarily driven by relapse. Eflornithine (DFMO) to reduce risk of relapse after completion of immunotherapy was investigated previously in a single-arm, phase II study (NMTRC003B; ClinicalTrials.gov identifier: NCT02395666) that suggested improved event-free survival (EFS) and overall survival (OS) compared with historical rates in a phase III trial (Children Oncology Group ANBL0032; ClinicalTrials.gov identifier: NCT00026312). Using patient-level data from ANBL0032 as an external control, we present new analyses to further evaluate DFMO as HRNB postimmunotherapy maintenance. PATIENTS AND METHODS NMTRC003B (2012-2016) enrolled patients with HRNB (N = 141) after standard up-front or refractory/relapse treatment who received up to 2 years of continuous treatment with oral DFMO (750 ± 250 mg/m2 twice a day). ANBL0032 (2001-2015) enrolled patients with HRNB postconsolidation, 1,328 of whom were assigned to dinutuximab (ch.14.18) treatment. Selection rules identified 92 NMTRC003B patients who participated in (n = 87) or received up-front treatment consistent with (n = 5) ANBL0032 (the DFMO/treated group) and 852 patients from ANBL0032 who could have been eligible for NMTRC003B after immunotherapy, but did not enroll (the NO-DFMO/control group). The median follow-up time for DFMO/treated patients was 6.1 years (IQR, 5.2-7.2) versus 5.0 years (IQR, 3.5-7.0) for NO-DFMO/control patients. Kaplan-Meier and Cox regression compared EFS and OS for overall groups, 3:1 (NO-DFMO:DFMO) propensity score–matched cohorts balanced on 11 baseline demographic and disease characteristics with exact matching on MYCN, and additional sensitivity analyses. RESULTS DFMO after completion of immunotherapy was associated with improved EFS (hazard ratio [HR], 0.50 [95% CI, 0.29 to 0.84]; P = .008) and OS (HR, 0.38 [95% CI, 0.19 to 0.76]; P = .007). The results were confirmed with propensity score–matched cohorts and sensitivity analyses. CONCLUSION The externally controlled analyses presented show a relapse risk reduction in patients with HRNB treated with postimmunotherapy DFMO.
Generative artificial intelligence empowers digital twins in drug discovery and clinical trials

ABSTRACT Introduction The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulations and experiments. DTs increase the efficiency of drug discovery and development by digitalizing processes associated with high economic, ethical, or social burden. The impact is multifaceted: DT models sharpen disease understanding, support biomarker discovery and accelerate drug development, thus advancing precision medicine. One way to realize DTs is by generative artificial intelligence (AI), a cutting-edge technology that enables the creation of novel, realistic and complex data with desired properties. Areas covered The authors provide a brief introduction to generative AI and describe how it facilitates the modeling of DTs. In addition, they compare existing implementations of generative AI for DTs in drug discovery and clinical trials. Finally, they discuss technical and regulatory challenges that should be addressed before DTs can transform drug discovery and clinical trials. Expert opinion The current state of DTs in drug discovery and clinical trials does not exploit the entire power of generative AI yet and is limited to simulation of a small number of characteristics. Nonetheless, generative AI has the potential to transform the field by leveraging recent developments in deep learning and customizing models for the needs of scientists, physicians and patients.
Fibroblast growth factor 10 reverses cigarette smoke- and elastase-induced emphysema and pulmonary hypertension in mice

Background COPD is an incurable disease and a leading cause of death worldwide. In mice, fibroblast growth factor (FGF)10 is essential for lung morphogenesis, and in humans, polymorphisms in the human FGF10 gene correlate with an increased susceptibility to develop COPD. Methods We analysed FGF10 signalling in human lung sections and isolated cells from healthy donor, smoker and COPD lungs. The development of emphysema and PH was investigated in Fgf10+/− and Fgfr2b+/− (FGF receptor 2b) mice upon chronic exposure to cigarette smoke. In addition, we overexpressed FGF10 in mice following elastase- or cigarette smoke-induced emphysema and pulmonary hypertension (PH). Results We found impaired FGF10 expression in human lung alveolar walls and in primary interstitial COPD lung fibroblasts. In contrast, FGF10 expression was increased in large pulmonary vessels in COPD lungs. Consequently, we identified impaired FGF10 signalling in alveolar walls as an integral part of the pathomechanism that leads to emphysema and PH development: mice with impaired FGF10 signalling (Fgf10+/− and Fgfr2b+/−) spontaneously developed lung emphysema, PH and other typical pathomechanistic features that generally arise in response to cigarette smoke exposure. Conclusion In a therapeutic approach, FGF10 overexpression successfully restored lung alveolar and vascular structure in mice with established cigarette smoke- and elastase-induced emphysema and PH. FGF10 treatment triggered an initial increase in the number of alveolar type 2 cells that gradually returned to the basal level when the FGF10-mediated repair process progressed. Therefore, the application of recombinant FGF10 or stimulation of the downstream signalling cascade might represent a novel therapeutic strategy in the future. Tweetable abstract Impaired FGF10 signalling is an integral part of the pathomechanism that leads to development of cigarette smoke-induced emphysema and PH. Restoration of FGF10 signalling reverses established cigarette smoke- and elastase-induced emphysema and PH in mice. https://bit.ly/3PgqrBw
Effect of combined tobacco use and type 2 diabetes mellitus on prevalent fibrosis in patients with MASLD

Background: Several studies have investigated the independent effect of cigarette smoking or type 2 diabetes mellitus (T2DM) on MASLD. However, the interaction effect between tobacco consumption and T2DM on MASLD severity remains underexplored. In this study, we assessed the combined effect of tobacco use and T2DM on hepatic fibrosis in MASLD. Methods: We conducted a single-center retrospective cross-sectional analysis of eligible participants from the Mass General Brigham Fibroscan© database. The participants were divided into 3 groups: those with T2DM and a history of tobacco use (primary exposure group), those with T2DM but no history of tobacco use (secondary exposure group), and those without T2DM and no history of tobacco use (reference group). An additional model was developed, which included a fourth group, participants with a history of tobacco use but no T2DM. The likelihood of fibrosis was determined using a defined fibrosis-4 index cutoff value of 1.3. In addition, we computed the estimated marginal means for liver stiffness measurement and compared the values among the exposure groups. Bivariable and multivariable logistic regression models were used to explore the associations between the exposure groups and the risk for hepatic fibrosis. Results: Overall, 598 individuals were enrolled in the study. The bivariable logistic regression model revealed a significant independent association between T2DM, combined smoking and T2DM, and the outcome of interest, fibrosis. Age, sex, metabolic syndrome, aspirin use, statin use, hemoglobin A1C (A1C), and total bilirubin level were also significantly associated with fibrosis. In the adjusted fibrosis-4 multivariable model (comparing exposure groups to controls), cigarette smoking and T2DM interaction had higher odds of prevalent fibrosis (aOR, 3.04; 95% CI, 1.62–5.76), compared to those with T2DM alone (aOR 2.28; 95% CI, 1.37–3.85). The continuous liver stiffness measurement comparison across the exposure group showed an estimated marginal means of 6.26 (95% CL: 5.58–6.94), 7.54 (95% CL: 6.78–8.30), and 7.88 (6.78–8.99) for the reference group, T2DM only group, and tobacco-T2DM group, respectively. The diabetes-only group and the combined tobacco-T2DM group had statistically significant associations with liver stiffness measurement (p values: 0.013 and 0.014, respectively). Conclusion: Although diabetes is independently associated with hepatic fibrosis in patients with MASLD, the combination of tobacco consumption and diabetes is associated with a higher prevalence of fibrosis. Therefore, lifestyle change through tobacco use cessation in patients with diabetes could be beneficial in reducing the incidence of liver fibrosis among individuals with MASLD.
Laboratory simulations and parameterization of the primary marine aerosol production

A major source of the primary marine aerosol is the bursting of air bubbles produced by breaking waves. Several source parameterizations are available from the literature, usually limited to particles with a dry diameter Dp > 1 μm. The objective of this work is to extend the current knowledge to submicrometer particles. Bubbles were generated in synthetic seawater using a sintered glass filter, with a size spectra that are only partly the same spectra as measured in the field. Bubble spectra, and size distributions of the resulting aerosol (0.020-20.0 μm Dp) of the resulting aerosol, were measured for different salinity, water temperature (Tw), and bubble flux. The spectra show a minimum at ∼1 μm Dp, which separates two modes, one at ∼0.1 μm, with the largest number of particles, and one at 2.5 μm Dp. The modes show different behavior with the variation of salinity and water temperature. When the water temperature increases, the number concentration Np decreases for Dp 0.35 μm, Np increases. The salinity effect suggests different droplet formation processes for droplets smaller and larger than 0.2 μm Dp. The number of particles produced per size increment, time unit, and whitecap surface (φ) is described as a linear function of Tw and a polynomial function of Dp. Combining φ with the whitecap coverage fraction W (in percent), an expression results for the primary marine aerosol source flux dFo/dlogDp = W φ (m-2 s-1 ). The results are compared with other commonly used formulations as well as with recent field observations. Implications for aerosol-induced effects on climate are discussed.
Observations of correlated behavior of stratospheric ozone and aerosol at Thule during winter 1991‐1992

Using a recently installed lidar, a series of measurements of aerosol concentrations have been carried out between 12-1991 and 3-1992. This work was in conjunction with the European Arctic Stratospheric Ozone Experiment. Scattering ratios were very high because of the presence of aerosols from the Mt Pinatubo volcanic eruption. Ozone observations were made in this period by sondes. This paper reports on correlations between these observations. The correlations observed were not always positive. Both observations saw distinct layered structures representing density variations with height.
Infer global, predict local: Quantity-relevance trade-off in protein fitness predictions from sequence data

Predicting the effects of mutations on protein function is an important issue in evolutionary biology and biomedical applications. Computational approaches, ranging from graphical models to deep-learning architectures, can capture the statistical properties of sequence data and predict the outcome of high-throughput mutagenesis experiments probing the fitness landscape around some wild-type protein. However, how the complexity of the models and the characteristics of the data combine to determine the predictive performance remains unclear. Here, based on a theoretical analysis of the prediction error, we propose descriptors of the sequence data, characterizing their quantity and relevance relative to the model. Our theoretical framework identifies a trade-off between these two quantities, and determines the optimal subset of data for the prediction task, showing that simple models can outperform complex ones when inferred from adequately-selected sequences. We also show how repeated subsampling of the sequence data is informative about how much epistasis in the fitness landscape is not captured by the computational model. Our approach is illustrated on several protein families, as well as on in silico solvable protein models.
Evolution of reproductive modes in sharks and rays

The ecological and life history drivers of the diversification of reproductive modes in early vertebrates are not fully understood. Sharks, rays and chimaeras (group Chondrichthyes) have an unusually diverse variety of reproductive modes and are thus an ideal group to test the factors driving the evolution of reproductive complexity. Here, using 960 species representing all major Chondrichthyes taxa, we reconstruct the evolution of their reproduction modes and investigate the ecological and life history predictors of reproduction. We show that the ancestral Chondrichthyes state was egg‐laying and find multiple independent transitions between egg‐laying and live‐bearing via an intermediate state of yolk‐only live‐bearing. Using phylogenetically informed analysis, we also show that live‐bearing species have larger body size and larger offspring than egg‐laying species. In addition, live‐bearing species are distributed over shallow to intermediate depths, while egg‐layers are typically found in deeper waters. This suggests that live‐bearing is more closely associated with pelagic, rather than demersal habitats. Taken together, using a basal vertebrate group as a model, we demonstrat how reproductive mode co‐evolves with environmental conditions and life‐history traits.
Retargeting video with an end-to-end framework

Video holds significance in computer graphics applications. Because of the heterogeneous of digital devices, retargeting videos becomes an essential function to enhance user viewing experience in such applications. In the research of video retargeting, preserving the relevant visual content in videos, avoiding flicking, and processing time are the vital challenges. Extending image retargeting techniques to the video domain is challenging due to the high running time. Prior work of video retargeting mainly utilizes time-consuming preprocessing to analyze frames. Plus, being tolerant of different video content, avoiding important objects from shrinking, and the ability to play with arbitrary ratios are the limitations that need to be resolved in these systems requiring investigation. In this paper, we present an end-to-end RETVI method to retarget videos to arbitrary aspect ratios. We eliminate the computational bottleneck in the conventional approaches by designing RETVI with two modules, content feature analyzer (CFA) and adaptive deforming estimator (ADE). The extensive experiments and evaluations show that our system outperforms previous work in quality and running time.
MDM2 Regulation of HIF Signaling Causes Microvascular Dysfunction in Hypertrophic Cardiomyopathy

BACKGROUND: Microvasculature dysfunction is a common finding in pathologic remodeling of the heart and is thought to play an important role in the pathogenesis of hypertrophic cardiomyopathy (HCM), a disease caused by sarcomere gene mutations. We hypothesized that microvascular dysfunction in HCM was secondary to abnormal microvascular growth and could occur independent of ventricular hypertrophy. METHODS: We used multimodality imaging methods to track the temporality of microvascular dysfunction in HCM mouse models harboring mutations in the sarcomere genes Mybpc3 (cardiac myosin binding protein C3) or Myh6 (myosin heavy chain 6). We performed complementary molecular methods to assess protein quantity, interactions, and post-translational modifications to identify mechanisms regulating this response. We manipulated select molecular pathways in vivo using both genetic and pharmacological methods to validate these mechanisms. RESULTS: We found that microvascular dysfunction in our HCM models occurred secondary to reduced myocardial capillary growth during the early postnatal time period and could occur before the onset of myocardial hypertrophy. We discovered that the E3 ubiquitin protein ligase MDM2 (murine double minute 2) dynamically regulates the protein stability of both HIF1α (hypoxia-inducible factor 1 alpha) and HIF2α (hypoxia-inducible factor 2 alpha)/EPAS1 (endothelial PAS domain protein 1) through canonical and noncanonical mechanisms. The resulting HIF imbalance leads to reduced proangiogenic gene expression during a key period of myocardial capillary growth. Reducing MDM2 protein levels by genetic or pharmacological methods normalized HIF protein levels and prevented the development of microvascular dysfunction in both HCM models. CONCLUSIONS: Our results show that sarcomere mutations induce cardiomyocyte MDM2 signaling during the earliest stages of disease, and this leads to long-term changes in the myocardial microenvironment.
Incorporation of healthy volunteers data on receptor occupancy into a phase II proof‐of‐concept trial using a Bayesian dynamic borrowing design

Receptor occupancy in targeted tissues measures the proportion of receptors occupied by a drug at equilibrium and is sometimes used as a surrogate of drug efficacy to inform dose selection in clinical trials. We propose to incorporate data on receptor occupancy from a phase I study in healthy volunteers into a phase II proof‐of‐concept study in patients, with the objective of using all the available evidence to make informed decisions. A minimal physiologically based pharmacokinetic modeling is used to model receptor occupancy in healthy volunteers and to predict it in the patients of a phase II proof‐of‐concept study, taking into account the variability of the population parameters and the specific differences arising from the pathological condition compared to healthy volunteers. Then, given an estimated relationship between receptor occupancy and the clinical endpoint, an informative prior distribution is derived for the clinical endpoint in both the treatment and control arms of the phase II study. These distributions are incorporated into a Bayesian dynamic borrowing design to supplement concurrent phase II trial data. A simulation study in immuno‐inflammation demonstrates that the proposed design increases the power of the study while maintaining a type I error at acceptable levels for realistic values of the clinical endpoint.