Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of the carboxyl-terminal domain of TolA in protein import and integrity of the outer membrane

The TolA protein is involved in maintaining the integrity of the outer membrane of Escherichia coli, as mutations in tolA cause the bacteria to become hypersensitive to detergents and certain antibiotics and to leak periplasmic proteins into the medium. This protein also is required for the group A colicins to exert their effects and for many of the filamentous single-stranded bacteriophage to infect the bacterial cell. TolA is a three-domain protein, with the amino-terminal domain anchoring it to the inner membrane. The helical second domain is proposed to span the periplasmic space to allow the carboxyl-terminal third domain to interact with the outer membrane. A plasmid that allowed the synthesis and transport of the carboxyl-terminal third domain into the periplasmic space was constructed. The presence of an excess of this domain in the periplasm of a wild-type cell resulted in an increased sensitivity to deoxycholate, the release of periplasmic alkaline phosphatase and RNase into the medium, and an increased tolerance to colicins E1, E2, E3, and A. There was no effect on the cells' response to colicin D, which depends on TonB instead of TolA for its action. The presence of the free carboxyl-terminal domain of TolA in the periplasm in a tolA null mutation did not restore the wild-type phenotype, suggesting that this domain must be part of the intact TolA molecule to perform its function. Our results are consistent with a model in which the carboxyl-terminal domain of TolA interacts with components in the periplasm or on the inner surface of the outer membrane to function in maintaining the integrity of this membrane.
Integrating lateral expansion into models of peatland development in temperate New England

1 As peatlands form they create a temporal archive of community development, allowing the reconstruction of vegetation dynamics through the analysis of sediments and the development of detailed chronologies of successional change. Peatland formation occurs through two mechanisms: (i) terrestrialization, when a water body fills with sediments and peat; and (ii) paludification, the conversion of dry land to peatland. In temperate regions, where high summer temperatures may limit peat accumulation, general models of peatland development suggest that allogenic factors such as climate change control peatland development and that terrestrialization is the primary mechanism of formation. 2 This study evaluates this widely accepted model by comparing the developmental histories of three peatlands within the same climate region in New England in order to: (i) describe the development and timing of successional events among peatlands; (ii) document the roles of paludification and terrestrialization as developmental mechanisms; and (iii) evaluate the importance of climate change vs. autogenic factors in peatland development in this temperate region. 3 Basin morphometry, sediment stratigraphies, and chronologies of community change determined through radiocarbon dating indicate that peatland development at each site involved terrestrialization followed by paludification, with no apparent influence of broad‐scale climate change on the timing of these processes. Paludification was consistently initiated coincident with the consolidation of a shrub mat across each lake‐basin, and was controlled in extent and rate by the topography of the adjoining uplands. The timing of stratigraphic changes varied among sites, suggesting that autogenic factors associated with the accumulation of peat rather than regional climate change controlled development. These results provide the foundation for a model of temperate peatland development driven by autogenic factors and caution against the use of temperate peatland development as a proxy for climatic reconstruction.
Variable-rate tree-structured vector quantizers

In general, growth algorithms for optimal tree-structured vector quantizers do not exist. In this paper we show that if the source satisfies certain conditions; namely, that of diminishing marginal returns; optimal growth algorithms do exist. We present such an algorithm and compare its performance with that of other tree growth algorithms. Even for sources that do not meet the necessary conditions for the growth algorithm to be optimal, such as for speech with unknown statistics, it is seen by simulation that the algorithm outperforms other known growth algorithms, For sources that do not satisfy the required conditions, the algorithm presented here can also be used to grow the initial tree for the pruning process. The performance of such pruned trees is superior to that of trees pruned from full trees of the same rate. >
Regularized ERM on random subspaces

We study a natural extension of classical empirical risk minimization, where the hypothesis space is a random subspace of a given space. In particular, we consider possibly data dependent subspaces spanned by a random subset of the data. This approach naturally leads to computational savings, but the question is whether the corresponding learning accuracy is degraded. These statistical-computational tradeoffs have been recently explored for the least squares loss and self-concordant loss functions, such as the logistic loss. Here, we work to extend these results to convex Lipschitz loss functions, that might not be smooth, such as the hinge loss used in support vector machines. Our main results show the existence of different regimes, depending on how hard the learning problem is, for which computational efficiency can be improved with no loss in performance. Theoretical results are complemented with numerical experiments on large scale benchmark data sets.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Graph representation learning has emerged as a powerful technique for addressing real-world problems. Various downstream graph learning tasks have benefited from its recent developments, such as node classification, similarity search, and graph classification. However, prior arts on graph representation learning focus on domain specific problems and train a dedicated model for each graph dataset, which is usually non-transferable to out-of-domain data. Inspired by the recent advances in pre-training from natural language processing and computer vision, we design Graph Contrastive Coding (GCC) --- a self-supervised graph neural network pre-training framework --- to capture the universal network topological properties across multiple networks. We design GCC's pre-training task as subgraph instance discrimination in and across networks and leverage contrastive learning to empower graph neural networks to learn the intrinsic and transferable structural representations. We conduct extensive experiments on three graph learning tasks and ten graph datasets. The results show that GCC pre-trained on a collection of diverse datasets can achieve competitive or better performance to its task-specific and trained-from-scratch counterparts. This suggests that the pre-training and fine-tuning paradigm presents great potential for graph representation learning.
An almost Zoll affine surface

An affine surface is said to be an affine Zoll surface if all affine geodesics close smoothly. It is said to be an affine almost Zoll surface if thru any point, every affine geodesic but one closes smoothly (the exceptional geodesic is said to be alienated as it does not return). We exhibit an affine structure on the cylinder which is almost Zoll. This structure is geodesically complete, affine Killing complete, and affine symmetric.
Combined QSAR-based virtual screening and fluorescence binding assay to identify natural product mediators of Interferon Regulatory Factor 7 (IRF-7) in pulmonary infection

Abstract Interferon regulatory factor-7 (IRF-7) is involved in pulmonary infection and pneumonia. Here, a synthetic strategy that combined quantitative structure–activity relationship (QSAR)-based virtual screening and in vitro binding assay was described to identify new and potent mediator ligands of IRF-7 from natural products. In the procedure, a QSAR scoring function was developed and validated using Gaussian process (GP) regression and a structure-based set of protein–ligand affinity data. By integrating hotspot pocket prediction, pharmacokinetics profile analysis and molecular docking calculations, the scoring function was successfully applied to virtual screening against a large library of structurally diverse, drug-like natural products. With the method we were able to identify a number of potential hits, from which several compounds were found to have moderate or high affinity to IRF-7 using fluorescence binding assays, with dissociation constants Kd at micromolar level. We have also examined the structural basis and noncovalent interactions of computationally modelled IRF-7 complex with its potent ligands. It is revealed that hydrophobic forces and van der Waals contacts play a central role in stabilization of the complex architecture, while few hydrogen bonds confer additional specificity for the protein–ligand recognition.
In Search of Family Resilience

This study explores the construct of family resilience defined as a family variable that enables the family to survive major life challenges and as a coping resource that enables the individual to deal with traumas and to thrive from the experience. Nurses who were working with infected patients in a major epidemic in Singapore provided the sample and the context to search for family resilience. Two studies are reported in this article: Study 1 consisted of an in-depth interview with 30 nurses and some of their family members to identify the factors within their families that they perceived to have enabled them to cope with the stress and difficulties. Based on the results from Study 1, a family resilience (FR) scale was constructed. Using the FR scale, Study 2 employed a structured survey to identify the internal organization and the psychometric properties of FR. Factor analysis of the results identified five meaningful factors. The FR scale was found to have excellent psychometric properties. Path analyses were conducted to test whether family resilience is a spurious factor and whether it is a construct distinct and independent from individual resilience (IR). It was found that FR predicts individual well-being with both direct and indirect effect mediated by individual resilience, supporting the nonspurious nature of FR and the potential reciprocal causal effects between FR and IR.
Overexpression of monocyte chemoattractant protein 1 in systemic sclerosis: role of platelet-derived growth factor and effects on monocyte chemotaxis and collagen synthesis.

OBJECTIVE In addition to its chemotactic properties, recent evidence suggests that monocyte chemoattractant protein 1 (MCP-1) might participate in the fibrotic process by inducing the secretion of extracellular matrix (ECM) components. Since the factors that initiate the accumulation of inflammatory infiltrates and ECM deposits in systemic sclerosis (SSc) skin lesions are still unknown, this study was undertaken to examine the role of MCP-1 in SSc. METHODS In situ hybridization and immunohistochemistry studies for MCP-1 were performed on skin biopsy specimens from patients with SSc and healthy controls. To identify possible stimulators of MCP-1 overexpression in SSc lesions, cultured dermal fibroblasts were incubated with recombinant platelet-derived growth factor (PDGF) and analyzed by real-time polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay. The chemotactic effects of SSc fibroblasts were examined using a modified Boyden chamber assay. To analyze the fibrotic potential of MCP-1, cultured dermal fibroblasts were incubated with recombinant MCP-1, and type I procollagen was measured by radioimmunoassay and real-time PCR. RESULTS MCP-1 was expressed by fibroblasts, keratinocytes, and perivascular infiltrates throughout the skin, in involved as well as uninvolved skin areas, from 10 of 11 SSc patients, whereas no expression of MCP-1 was found in healthy controls. Stimulation with PDGF resulted in a significant increase in MCP-1 messenger RNA and protein, with differences between healthy control fibroblasts and fibroblasts from SSc patients. The chemotactic activity for peripheral blood mononuclear cells of SSc fibroblast supernatants increased in a time-dependent manner. Antibodies blocking MCP-1 decreased the chemotactic activity of SSc fibroblasts by a mean +/- SD of 37 +/- 12%. Despite an increase in type I collagen levels over time, no effect of recombinant MCP-1 on the synthesis of type I collagen was observed. CONCLUSION These data indicate that MCP-1 might contribute to the initiation of inflammatory infiltrates in SSc. Possible stimuli of MCP-1 in dermal SSc lesions include PDGF, which is known to be expressed in SSc. In contrast to previous findings in fibrotic lung diseases, no effect of MCP-1 on collagen synthesis was observed in SSc dermal fibroblasts in vitro.
Targeting elements in the amino-terminal part direct the human 70-kDa peroxisomal integral membrane protein (PMP70) to peroxisomes.

Peroxisomes are multipurpose organelles present in nearly all eukaryotic cells. All peroxisomale matrix and membrane proteins are synthesized in the cytoplasm. While a clear picture of the basic targeting mechanisms for peroxisomal matrix proteins has emerged over the past years, the targeting processes for peroxisomal membrane proteins are poorly understood. The 70-kDa peroxisomal integral membrane protein (PMP70) is one of the proteins located in the human peroxisome membrane. PMP70 belongs to the family of ATP-binding cassette (ABC) transporter proteins. It consists of six transmembrane domains and an ATP-binding fold in the cytosol. Here we describe that efficient peroxisomal targeting of human PMP70 depends on three targeting elements in the amino-terminal protein region, namely amino acids 61 to 80 located in the cytosol as well as the first and second transmembrane domains. Furthermore, peroxin 19 (PEX19) interactions are not required for targeting human PMP70 to peroxisomes. PEX19 does not specifically bind to the targeting elements of human PMP70.
Recent progress in the pharmacotherapy of Churg-Strauss syndrome

Churg-Strauss syndrome (CSS) is a primary systemic vasculitis occurring primarily in patients with asthma. Unlike other small vessel vasculitides, CSS is characterised by blood and tissue eosinophilia. Corticosteroids are the therapy of first choice for all stages of the disease when active vasculitis needs to be treated rapidly. In patients with severe disease and organ- or life-threatening manifestation, the addition of cyclophosphamide appears to improve the outcome and reduces the incidence of relapses. In cases with an apparently better prognosis and less severe disease, methotrexate can be given as a corticosteroid-sparing agent in order to reduce the cumulative dose of corticosteroids, which is generally high in most cases as long-term administration of corticosteroids is often inevitable in order to control asthma, even if the vasculitis is inactive. In very severe cases of CSS, cyclophosphamide and corticosteroids may be insufficient to induce remission. In these cases, anti-TNF blocking agents such as infliximab or etanercept, may be added for a limited period of time. As this intense immunosuppression increases the risk for infections, a prophylaxis with sulfamethoxazole/trimethoprim is advised. Alternatively, the administration of recombinant IFN-α can be a effective when given on a short-term basis in otherwise refractory cases. Whether a continous administration of immunosuppressive agents in addition to corticosteroids can reduce the frequency of relapses in CSS who are in remission is still unknown. As relapses occur in > 25% of all patients, studies addressing the prevention of relapses in CSS are highly desirable in the future.
StatAssist & GradBoost: A Study on Optimal INT8 Quantization-aware Training from Scratch

This paper studies the scratch training of quantization-aware training (QAT), which has been applied to the lossless conversion of lower-bit, especially for INT8 quantization. Due to its training instability, QAT have required a full-precision (FP) pre-trained weight for fine-tuning and the performance is bound to the original FP model with floating-point computations. Here, we propose critical but straightforward optimization methods which enable the scratch training: floating-point statistic assisting (StatAssist) and stochastic-gradient boosting (GradBoost). We discovered that, first, the scratch QAT get comparable and often surpasses the performance of the floating-point counterpart without any help of the pre-trained model, especially when the model becomes complicated.We also show that our method can even train the minimax generation loss, which is very unstable and hence difficult to apply QAT fine-tuning. From extent experiments, we show that our method successfully enables QAT to train various deep models from scratch: classification, object detection, semantic segmentation, and style transfer, with comparable or often better performance than their FP baselines.
Stochastic modelling of star-formation histories II: star-formation variability from molecular clouds and gas inflow

A key uncertainty in galaxy evolution is the physics regulating star formation, ranging from small-scale processes related to the life-cycle of molecular clouds within galaxies to large-scale processes such as gas accretion on to galaxies. We study the imprint of such processes on the time-variability of star formation with an analytical approach tracking the gas mass of galaxies (‘regulator model’). Specifically, we quantify the strength of the fluctuation in the star-formation rate (SFR) on different time-scales, i.e. the power spectral density (PSD) of the star-formation history, and connect it to gas inflow and the life-cycle of molecular clouds. We show that in the general case the PSD of the SFR has three breaks, corresponding to the correlation time of the inflow rate, the equilibrium time-scale of the gas reservoir of the galaxy, and the average lifetime of individual molecular clouds. On long and intermediate time-scales (relative to the dynamical time-scale of the galaxy), the PSD is typically set by the variability of the inflow rate and the interplay between outflows and gas depletion. On short time-scales, the PSD shows an additional component related to the life-cycle of molecular clouds, which can be described by a damped random walk with a power-law slope of β ≈ 2 at high frequencies with a break near the average cloud lifetime. We discuss star-formation ‘burstiness’ in a wide range of galaxy regimes, study the evolution of galaxies about the main sequence ridgeline, and explore the applicability of our method for understanding the star-formation process on cloud-scale from galaxy-integrated measurements.
Interferon-alpha-producing cells are localized in gut-associated lymphoid tissues in transmissible gastroenteritis virus (TGEV) infected piglets.

Transmissible gastroenteritis virus (TGEV) infection of piglets results in a very rapid and massive release of IFN-alpha in serum and secretions. The objective of this work was to characterize the IFN-alpha-producing cells (IPC) in tissues of TGEV-infected piglets. Caesarean-derived colostrum-deprived piglets were infected orally with the TGEV virulent Miller strain and IPC were characterized in situ by immunohistochemistry, using a rabbit anti-pig IFN-alpha antiserum. IPC were almost exclusively detected in intestinal tissues and mesenteric lymph nodes (MLN), as early as 6 h post inoculation (p.i.), with a peak at 12-18 h. They disappeared by 24 h. IPC were localized between enterocytes in the small intestine epithelial layer, in the lamina propria, around the Peyer's patches and, at highest frequency, in MLN. Very few IPC were present in the spleen and popliteal lymph nodes of infected piglets. Double immunohistochemical staining for IFN-alpha and leukocyte markers on MLN cryosections showed that IPC were mainly Swine Leukocyte Antigen (SLA) class II positive, and were not stained by an anti-macrophage (SWC3a) MAb. In addition, double staining with anti-TGEV and anti-IFN-alpha MAbs showed that viral antigens were present in MLN, close to IPC. These results show for the first time the presence of IPC in gut mucosa and gut-associated lymphoid tissues in response to an enteropathogenic virus. Moreover, this work shows that IFN-alpha released in serum is likely to originate almost exclusively from gut IPC triggered locally by viral antigens to produce IFN-alpha, since there were very few IPC in spleen or peripheral lymph nodes. MHC class II molecule expression by gut-associated IPC suggests that these cells may be the in vivo mucosal counterparts of the dendritic cells recently shown to produce IFN-alpha after in vitro viral induction.
TESS unveils the optical phase curve of KELT-1b

We present the detection and analysis of the phase curve of KELT-1b at optical wavelengths, analyzing data taken by the Transiting Exoplanet Survey Satellite (TESS) during cycle 2 and sector 17. With a mass of ~27 MJup, KELT-1b is an example of a low-mass brown dwarf. Due to the high mass and close proximity of its companion, the host star exhibits a TESS light curve that shows clear ellipsoidal variations. We modeled the data with a six-component model: secondary eclipse, phase curve accounting for reflected light and thermal emission, Doppler beaming, ellipsoidal variations, stellar activity, and the primary transit. We determined the secondary eclipse depth in the TESS bandpass to be 304 ± 75 parts-per-million (ppm). In addition, we measured the amplitude of the phase curve to be 128 ± 27 ppm, with a corresponding eastward offset between the region of maximum brightness and the substellar point of 19.2 ± 9.6 degrees, with the latter showing good agreement with Spitzer measurements. We determined a day-side brightness temperature in the TESS bandpass of 3201 ± 147 K that is approximately 200 K higher than the values determined from the Spitzer 3.6 and 4.5 μm data. By combining TESS and Spitzer eclipse depths, we derived a day-side effective temperature of Teff = 3010 ± 78 K. Previously published eclipse depths in the near-infrared suggest a much higher brightness temperature and this discrepancy cannot be explained by spectral models combined with the current data. We attribute those large eclipse depths to unmodeled ellipsoidal variations, which would typically be manifested as a deeper secondary eclipse in observations with insufficient phase coverage. A one-dimensional self-consistent atmospheric model is able to explain the TESS and Spitzer day-side brightness temperatures with thermal emission alone and no reflected light. The difference between the TESS and Spitzer brightness temperatures can be explained via CO absorption due to a non-inverted temperature profile. The night side data fix an upper limit of ~2000 K on the internal temperature of KELT-1 b.
Parallel Variable Distribution Algorithm for Constrained Optimization with Nonmonotone Technique

A modified parallel variable distribution (PVD) algorithm for solving large-scale constrained optimization problems is developed, which modifies quadratic subproblem at each iteration instead of the of the SQP-type PVD algorithm proposed by C. A. Sagastizabal and M. V. Solodov in 2002. The algorithm can circumvent the difficulties associated with the possible inconsistency of subproblem of the original SQP method. Moreover, we introduce a nonmonotone technique instead of the penalty function to carry out the line search procedure with more flexibly. Under appropriate conditions, the global convergence of the method is established. In the final part, parallel numerical experiments are implemented on CUDA based on GPU (Graphics Processing unit).