Miracle-dz/UniFAR-FTUs huggingface dataset:
Stem cell therapies for retinal diseases: recapitulating development to replace degenerated cells

Retinal degenerative diseases are the leading causes of blindness worldwide. Replacing lost retinal cells via stem cell-based therapies is an exciting, rapidly advancing area of translational research that has already entered the clinic. Here, we review the status of these clinical efforts for several significant retinal diseases, describe the challenges involved and discuss how basic developmental studies have contributed to and are needed to advance clinical goals. Summary: This Review article summarizes the current state-of-the-art retinal stem cell therapies, and highlights the essential role of developmental biology in moving this field forward.
Late gestational intermittent hypoxia induces metabolic and epigenetic changes in male adult offspring mice

Late gestation during pregnancy has been associated with a relatively high prevalence of obstructive sleep apnoea (OSA). Intermittent hypoxia, a hallmark of OSA, could impose significant long‐term effects on somatic growth, energy homeostasis and metabolic function in offspring. Here we show that late gestation intermittent hypoxia induces metabolic dysfunction as reflected by increased body weight and adiposity index in adult male offspring that is paralleled by epigenomic alterations and inflammation in visceral white adipose tissue. Fetal perturbations by OSA during pregnancy impose long‐term detrimental effects manifesting as metabolic dysfunction in adult male offspring.
The Relationship between Runs of Homozygosity and Inbreeding in Jersey Cattle under Selection

Inbreeding is often an inevitable outcome of strong directional artificial selection but on average it reduces population fitness with increased frequency of recessive deleterious alleles. Runs of homozygosity (ROH) representing genomic autozygosity that occur from mating between selected and genomically related individuals may be able to reveal the regions affecting fitness. To examine the influence of genomic autozygosity on fitness, we used a genome-wide association test to evaluate potential negative correlations between ROH and daughter pregnancy rate (DPR) or somatic cell score (SCS) in US Jersey cattle. In addition, relationships between changes of local ROH and inbreeding coefficients (F) were assessed to locate genomic regions with increased inbreeding. Despite finding some decreases in fertility associated with incremental increases in F, most emerging local ROH were not significantly associated with DPR or SCS. Furthermore, the analyses of ROH could be approximated with the most frequent haplotype(s), including the associations of ROH and F or traits. The analysis of the most frequent haplotype revealed that associations of ROH and fertility could be accounted for by the additive genetic effect on the trait. Thus, we suggest that a change of autozygosity is more likely to demonstrate footprints of selected haplotypes for production rather than highlight the possible increased local autozygosity of a recessive detrimental allele resulting from the mating between closely related animals in Jersey cattle.
Learning with Complex Loss Functions and Constraints

We develop a general approach for solving constrained classification problems, where the loss and constraints are defined in terms of a general function of the confusion matrix. We are able to handle complex, non-linear loss functions such as the F-measure, G-mean or H-mean, and constraints ranging from budget limits, to constraints for fairness, to bounds on complex evaluation metrics. Our approach builds on the framework of Narasimhan et al. (2015) for unconstrained classification with complex losses, and reduces the constrained learning problem to a sequence of cost-sensitive learning tasks. We provide algorithms for two broad families of problems, involving convex and fractional-convex losses, subject to convex constraints. Our algorithms are statistically consistent, generalize an existing approach for fair classification, and readily apply to multiclass problems. Experiments on a variety of tasks demonstrate the efficacy of our methods.
Atomic‐resolution dissection of the energetics and mechanism of isomerization of hydrated ATP‐Mg2+ through the SOMA string method

The atomic mechanisms of isomerization of ATP‐Mg2+ in solution are characterized using the recently developed String Method with Optimal Molecular Alignment (SOMA) and molecular‐dynamics simulations. Bias‐Exchange Metadynamics simulations are first performed to identify the primary conformers of the ATP‐Mg2+ complex and their connectivity. SOMA is then used to elucidate the minimum free‐energy path (MFEP) for each transition, in a 48‐dimensional space. Analysis of the per‐atom contributions to the global free‐energy profiles reveals that the mechanism of these transitions is controlled by the Mg2+ ion and its coordinating oxygen atoms in the triphosphate moiety, as well as by the ion‐hydration shell. Metadynamics simulations in path collective variables based on the MFEP demonstrate these isomerizations proceed across a narrow channel of configurational space, thus validating the premise underlying SOMA. This study provides a roadmap for the examination of conformational changes in biomolecules, based on complementary enhanced‐sampling techniques with different strengths. © 2015 Wiley Periodicals, Inc.
A Bandwise Noise Model Combined With Low-Rank Matrix Factorization for Hyperspectral Image Denoising

Hyperspectral image (HSI) is usually polluted by dense additive white Gaussian noise (AWGN). The noise intensity of AWGN is different for different bands of the HSI, and it has been utilized by many denoising algorithms. However, many of them did not convey this phenomenon in the objective function. In this paper, a bandwise noise model is proposed to overcome the problem. Furthermore, based on the low-rank structure of the HSI, the proposed bandwise noise model is combined with the low-rank matrix factorization to obtain a new efficient HSI denoising algorithm. Additionally, as the noise estimation is an important preprocessing step for the proposed algorithm, a classical noise estimation algorithm is improved to increase its efficiency. The proposed algorithm is used on the HSI corrupted by mixed noise. Both simulated and real experiments demonstrate the state-of-the-art performance and efficiency of the proposed algorithm.
Stable Expression of Lentiviral Antigens by Quality-Controlled Recombinant Mycobacterium bovis BCG Vectors

ABSTRACT The well-established safety profile of the tuberculosis vaccine strain, Mycobacterium bovis bacille Calmette-Guérin (BCG), makes it an attractive vehicle for heterologous expression of antigens from clinically relevant pathogens. However, successful generation of recombinant BCG strains possessing consistent insert expression has encountered challenges in stability. Here, we describe a method for the development of large recombinant BCG accession lots which stably express the lentiviral antigens, human immunodeficiency virus (HIV) gp120 and simian immunodeficiency virus (SIV) Gag, using selectable leucine auxotrophic complementation. Successful establishment of vaccine stability stems from stringent quality control criteria which not only screen for highly stable complemented BCG ΔleuCD transformants but also thoroughly characterize postproduction quality. These parameters include consistent production of correctly sized antigen, retention of sequence-pure plasmid DNA, freeze-thaw recovery, enumeration of CFU, and assessment of cellular aggregates. Importantly, these quality assurance procedures were indicative of overall vaccine stability, were predictive for successful antigen expression in subsequent passaging both in vitro and in vivo, and correlated with induction of immune responses in murine models. This study has yielded a quality-controlled BCG ΔleuCD vaccine expressing HIV gp120 that retained stable full-length expression after 1024-fold amplification in vitro and following 60 days of growth in mice. A second vaccine lot expressed full-length SIV Gag for >1068-fold amplification in vitro and induced potent antigen-specific T cell populations in vaccinated mice. Production of large, well-defined recombinant BCG ΔleuCD lots can allow confidence that vaccine materials for immunogenicity and protection studies are not negatively affected by instability or differences between freshly grown production batches.
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach

Tree ensembles, such as random forests and boosted trees, are renowned for their high prediction performance. However, their interpretability is critically limited due to the enormous complexity. In this study, we present a method to make a complex tree ensemble interpretable by simplifying the model. Specifically, we formalize the simplification of tree ensembles as a model selection problem. Given a complex tree ensemble, we aim at obtaining the simplest representation that is essentially equivalent to the original one. To this end, we derive a Bayesian model selection algorithm that optimizes the simplified model while maintaining the prediction performance. Our numerical experiments on several datasets showed that complicated tree ensembles were reasonably approximated as interpretable.
Heuristic evolution with genetic programming for traveling thief problem

In many real-world applications, one needs to deal with a large multi-silo problem with interdependent silos. In order to investigate the interdependency between silos (sub-problems), the Traveling Thief Problem (TTP) was designed as a benchmark problem. TTP is a combination of two well-known sub-problems, Traveling Salesman Problem (TSP) and Knapsack Problem (KP). Although each sub-problem has been intensively investigated, the interdependent combination has been demonstrated to be challenging, and cannot be solved by simply solving the sub-problems separately. The Two-Stage Memetic Algorithm (TSMA) is an effective approach that has decent solution quality and scalability, which consists of a tour improvement stage and an item picking stage. Unlike the traditional TSP local search operators adopted in the former stage, the heuristic for the latter stage is rather intuitive. To further investigate the effect of item picking heuristic, Genetic Programming (GP) is employed to evolve a gain function and a picking function, respectively. The resultant two heuristics were tested on some representative TTP instances, and showed competitive performance, which indicates the potential of evolving more promising heuristics for solving TTP more systematically by GP.
Medical Image Retrieval Using Manifold Ranking with Relevance Feedback

Medical image retrieval (MedIR) is a challenging field in Visual information retrieval, due to the multi-dimensional and multi-modal context of the underlying content. Traditional models do not take the intrinsic characteristics of data into consideration and have achieved limited accuracy in application to medical images. Manifold Ranking (MR) is a technique that can be used in further optimizing precision and recall in MedIR applications as it ranks items by traversing a dynamically constructed content-specific information graph. In this paper, a MedIR approach based on Manifold Ranking is proposed. Medical images being multi-dimensional, exhibit underlying cluster and manifold information which enhances semantic relevance and allows for label uniformity. Hence, when adapted for MedIR, MR can help in achieving large-scale ranking across datasets as is the case in most medical imaging applications. In addition, a relevance feedback mechanism was also incorporated to support a learning based system. We show that MR achieved significant improvement in retrieval results with relevance feedback as compared to the Euclidean Distance (ED) rankings. This showcases the importance of analyzing the inherent latent structure in medical image data for better performance over traditional methods.
Design and Evaluation of a Customizable Multi-Domain Reference Architecture on Top of Product Lines of Self-Driving Heavy Vehicles - An Industrial Case Study

Self-driving vehicles for commercial use cases like logistics or overcast mines increase their owners' economic competitiveness. Volvo maintains, evolves, and distributes a vehicle control product line for different brands like Volvo Trucks, Renault, and Mack in more than 190 markets world-wide. From the different application domains of their customers originates the need for a multi-domain reference architecture concerned with transport mission planning, execution, and tracking on top of the vehicle control product line. This industrial case study is the first of its kind reporting about the systematic process to design such a reference architecture involving all relevant external and internal stakeholders, development documents, low level artifacts, and literature. Quantitative and qualitative metrics were applied to evaluate non-functional requirements on the reference architecture level before a concrete variant was evaluated using a Volvo FMX truck in an exemplary construction site setting.
Formation of nm-Size Dispersoids from Supersaturated Solid Solutions of Aluminium

The principles are discussed which control the formation of ultra fine heterogeneous microstructures from supersaturated solid solutions of Al-alloys. The role of defects in nucleation of metastable or stable phases is emphasized with respect to the formation of dispersoids of nano-sized particles, which in turn cause maximum hardening. Finally, a + /-rule (atomic size ratios) and an extended version of Ostwald's step rule are applied as gidelines for obtaining this objective.
Pieces of Eight: 8-bit Neural Machine Translation

Neural machine translation has achieved levels of fluency and adequacy that would have been surprising a short time ago. Output quality is extremely relevant for industry purposes, however it is equally important to produce results in the shortest time possible, mainly for latency-sensitive applications and to control cloud hosting costs. In this paper we show the effectiveness of translating with 8-bit quantization for models that have been trained using 32-bit floating point values. Results show that 8-bit translation makes a non-negligible impact in terms of speed with no degradation in accuracy and adequacy.
Turboelectric Aircraft Drive Key Performance Parameters and Functional Requirements

The purpose of this paper is to propose specific power and efficiency as the key performance parameters for a turboelectric aircraft power system and investigate their impact on the overall aircraft. Key functional requirements are identified that impact the power system design. Breguet range equations for a base aircraft and a turboelectric aircraft are found. The benefits and costs that may result from the turboelectric system are enumerated. A break-even analysis is conducted to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.
New Insights into the Reaction Paths of 4-Carboxybenzophenone Triplet with Oligopeptides Containing N- and C-Terminal Methionine Residues.

The oxidation processes of l-Met-(Pro)n-l-Met peptides that contain two Met residues located on the N and C termini and separated by a defined number (n = 0-4) of proline residues were investigated in aqueous solutions using laser flash photolysis. The use of such peptides allowed for distance control between the sulfur atoms located in the side chains of the Met residues. Interactions between side chains of the Met residues were probed by the observation of transients with σ*-type 2c-3e (S∴S)+, (S∴N)+, and (S∴O)+ bonds as well as of α-(alkylthio)alkyl radicals (αS). This approach enabled the monitoring, in real time, of the efficiency and kinetics of interactions between amino acid chains. Such knowledge is important, inter alia, for long-distance electron-transfer (ET) processes because amino acid side chains can serve as relay stations. The yields of these transients (measured as quantum yields (Φ)) were found to be dependent on the number of Pro residues, however, not dependent in a simple way on the average distance between sulfur atoms in Met residues. A decrease in the yield of the (S∴S)+ species with the number of Pro residues occurred at the expense of an increase in the yields of intramolecular three electron-bonded (S∴O)+/(S∴N)+ radical cations and αS radicals. These observations were rationalized by the fact that the time required for adequate overlap of the bonding orbitals is a key factor effecting the yield of the (S∴S)+ species. The time, however, can be controlled not only by the average distance but also by the specific geometrical and conformational properties of the peptide molecules.
Histological assessment of the liver explant in transplanted hepatitis C virus patients achieving sustained virological response with direct‐acting antiviral agents

The use of direct‐acting anti‐viral agents (DAAs) has resulted in extremely high sustained virological response (SVR) rates in patients being treated while on liver transplantation (LT) waiting lists. The aim of this study was to evaluate the histological findings of hepatitis C virus (HCV) patients who achieved SVR after receiving DAA treatment [SVR(+)] prior to LT, and compare them with HCV patients who had not achieved SVR [SVR(−)].
Long Noncoding RNA uc002yug.2 Activates HIV-1 Latency through Regulation of mRNA Levels of Various RUNX1 Isoforms and Increased Tat Expression

ABSTRACT The HIV-1 reservoir is a major obstacle to complete eradication of the virus. Although many proteins and RNAs have been characterized as regulators in HIV-1/AIDS pathogenesis and latency, only a few long noncoding RNAs (lncRNAs) have been shown to be closely associated with HIV-1 replication and latency. In this study, we demonstrated that lncRNA uc002yug.2 plays a key role in HIV-1 replication and latency. uc002yug.2 potentially enhances HIV-1 replication, long terminal repeat (LTR) activity, and the activation of latent HIV-1 in both cell lines and CD4+ T cells from patients. Further investigation revealed that uc002yug.2 activates latent HIV-1 through downregulating RUNX1b and -1c and upregulating Tat protein expression. The accumulated evidence supports our model that the Tat protein has the key role in the uc002yug.2-mediated regulatory effect on HIV-1 reactivation. Moreover, uc002yug.2 showed an ability to activate HIV-1 similar to that of suberoylanilide hydroxamic acid or phorbol 12-myristate 13-acetate using latently infected cell models. These findings improve our understanding of lncRNA regulation of HIV-1 replication and latency, providing new insights into potential targeted therapeutic interventions. IMPORTANCE The latent viral reservoir is the primary obstacle to curing HIV-1 disease. To date, only a few lncRNAs, which play major roles in various biological processes, including viral infection, have been identified as regulators in HIV-1 latency. In this study, we demonstrated that lncRNA uc002yug.2 is important for both HIV-1 replication and activation of latent viruses. Moreover, uc002yug.2 was shown to activate latent HIV-1 through regulating alternative splicing of RUNX1 and increasing the expression of Tat protein. These findings highlight the potential merit of targeting lncRNA uc002yug.2 as an activating agent for latent HIV-1.
RB regulates the production and the survival of newborn neurons in the embryonic and adult dentate gyrus

In mammals, hippocampal dentate gyrus granule cells (DGCs) constitute a particular neuronal population produced both during embryogenesis and adult life, and play key roles in neural plasticity and memory. However, the molecular mechanisms regulating neurogenesis in the dentate lineage throughout development and adulthood are still not well understood. The Retinoblastoma protein (RB), a transcriptional repressor primarily involved in cell cycle control and cell death, plays crucial roles during cortical development but its function in the formation and maintenance of DGCs remains unknown. Here, we show that loss of RB during embryogenesis induces massive ectopic proliferation and delayed cell cycle exit of young DGCs specifically at late developmental stages but without affecting stem cells. This phenotype was partially counterbalanced by increased cell death. Similarly, during adulthood, loss of RB causes ectopic proliferation of newborn DGCs and dramatically impairs their survival. These results demonstrate a crucial role for RB in the generation and the survival of DGCs in the embryonic and the adult brain. © 2016 Wiley Periodicals, Inc.
The interaction of intense few-cycle laser pulses with nanoscale targets

In this thesis I describe investigations of the interaction of strong laser fields with nanoscale targets, particularly with atomic clusters. I have explored laser-irradiated clusters in a new regime of interaction where the pulse duration approaches the few-cycle regime and the cluster ions essentially do not move during the laser pulse. A key result of this thesis is the observation of a new anisotropy in the ion emission from the explosion of xenon and argon clusters subjected to ultra-short (∼ 30 fs) near-infrared high intensity (∼ 1015 W cm−2) laser pulses. In this regime more energetic ions are emitted in the direction perpendicular to the laser polarisation axis, which is the reverse of the well-known anisotropy previously observed in experiments with longer (∼ 100 fs) pulses. I show that the new anisotropy is a transient phenomenon present for a limited range of pulse durations, that is specific to the cluster size and atom species. As the pulse duration is increased the new anisotropy diminishes and a standard anisotropy appears. To explain the observed anisotropy, I have developed an electrostatic model, showing that the intracluster electric field can have a maximum in the direction perpendicular to the laser polarisation axis, leading to anisotropic ion acceleration consistent with experimental observations. These measurements and modeling give access to the initial dynamics, present early in the interaction of an intense laser field with a nanoscale dielectric. In addition to investigations of gas phase clusters I have also studied nanostructures on surfaces. An experiment to study time-dependent plasmonic fields with attosecond streaking is being designed and built. Here I present numerical simulations of nanoplasmonic streaking and address the issues that have to be considered for the ongoing experiment. I show how the plasmonic field can be retrieved from the simulated streaked spectra.
Structural and functional differences between porcine brain and budding yeast microtubules

ABSTRACT The cytoskeleton of eukaryotic cells relies on microtubules to perform many essential functions. We have previously shown that, in spite of the overall conservation in sequence and structure of tubulin subunits across species, there are differences between mammalian and budding yeast microtubules with likely functional consequences for the cell. Here we expand our structural and function comparison of yeast and porcine microtubules to show different distribution of protofilament number in microtubules assembled in vitro from these two species. The different geometry at lateral contacts between protofilaments is likely due to a more polar interface in yeast. We also find that yeast tubulin forms longer and less curved oligomers in solution, suggesting stronger tubulin:tubulin interactions along the protofilament. Finally, we observed species-specific plus-end tracking activity for EB proteins: yeast Bim1 tracked yeast but not mammalian MTs, and human EB1 tracked mammalian but not yeast MTs. These findings further demonstrate that subtle sequence differences in tubulin sequence can have significant structural and functional consequences in microtubule structure and behavior.