Miracle-dz/UniFAR-FTUs huggingface dataset:
NDUFAF5 Hydroxylates NDUFS7 at an Early Stage in the Assembly of Human Complex I*

Complex I (NADH ubiquinone oxidoreductase) in mammalian mitochondria is an L-shaped assembly of 45 proteins. One arm lies in the inner membrane, and the other extends about 100 Å into the matrix of the organelle. The extrinsic arm contains binding sites for NADH, the primary electron acceptor FMN, and seven iron-sulfur clusters that form a pathway for electrons linking FMN to the terminal electron acceptor, ubiquinone, which is bound in a tunnel in the region of the junction between the arms. The membrane arm contains four antiporter-like domains, energetically coupled to the quinone site and involved in pumping protons from the matrix into the intermembrane space contributing to the proton motive force. Seven of the subunits, forming the core of the membrane arm, are translated from mitochondrial genes, and the remaining subunits, the products of nuclear genes, are imported from the cytosol. Their assembly is coordinated by at least thirteen extrinsic assembly factor proteins that are not part of the fully assembled complex. They assist in insertion of co-factors and in building up the complex from smaller sub-assemblies. One such factor, NDUFAF5, belongs to the family of seven-β-strand S-adenosylmethionine-dependent methyltransferases. However, similar to another family member, RdmB, it catalyzes the introduction of a hydroxyl group, in the case of NDUFAF5, into Arg-73 in the NDUFS7 subunit of human complex I. This modification occurs early in the pathway of assembly of complex I, before the formation of the juncture between peripheral and membrane arms.
On Natural Representations of Objects

We give explanations on the differences between a number of representations that have been proposed in the literature to measure the structural complexity of an object. In particular, we propose the notion of process complexity, the notion of sophistication from a given perspective, the notion of sophisticated depth, and the notion of self-dissimilarity. We also propose the notion of an approximate process for an object and argue that for all practical purposes, an approximate process is as good as an exact process.
Lysophosphatidic Acid Induces Necrosis and Apoptosis in Hippocampal Neurons

Abstract: A diverse body of evidence indicates a role for the lipid biomediator lysophosphatidic acid (LPA) in the CNS. This study identifies and characterizes the induction of neuronal death by LPA. Treatment of cultured hippocampal neurons from embryonic rat brains with 50 µM LPA resulted in neuronal necrosis, as determined morphologically and by the release of lactate dehydrogenase. A concentration of LPA as low as 10 µM led to the release of lactate dehydrogenase. In contrast, treatment of neurons with 0.1 or 1.0 µM LPA resulted in apoptosis, as determined by chromatin condensation. In addition, neuronal death induced by 1 µM LPA was characterized as apoptotic on the basis of terminal dUTP nick end‐labeling (TUNEL) staining, externalization of phosphatidylserine, and protection against chromatin condensation, TUNEL staining, and phosphatidylserine externalization by treatment with N‐benzyloxycarbonyl‐Val‐Ala‐Asp‐fluoromethyl ketone, a broad‐spectrum inhibitor of caspases, i.e., members of the interleukin‐1β converting enzyme family. Studies with antagonists of ionotropic glutamate receptors did not indicate a significant role for these receptors in apoptosis induced by 1 µM LPA. LPA (1 µM) also induced a decrease in mitochondrial membrane potential. Moreover, pretreatment of neurons with cyclosporin A protected against the LPA‐induced decrease in mitochondrial membrane potential and neuronal apoptosis. Thus, LPA, at pathophysiological levels, can induce neuronal apoptosis and could thereby participate in neurodegenerative disorders.
Teaching White Students about Racism: The Search for White Allies and the Restoration of Hope

in teaching about race and racism in their classrooms have trouble identifying contemporary white men and women who have taken a public stand against racism, it is a reasonable assumption that our students will not be able to identify those names either. Why is this lack of information of concern? As I have discussed elsewhere, one consequence of addressing the issue of racism (and other forms of oppression) in the classroom is the generation of powerful emotional responses in both white students and students of color. White students, in particular, often struggle with strong feelings of guilt when they become aware of the pervasiveness of racism in our society. Even when they feel their own behavior has been nondiscriminatory, they often experience “guilt by association. ” These feelings are uncomfortable and can lead white students to resist learning about race and racism. And who can blame them? If learning about racism means seeing oneself as an “oppressor,” one of the “bad guys,” then of course there will be resistance. Few people would actively embrace such a self-definition. But what alternatives do we offer to white students? This article is intended to explore this question and its implications for teaching about racism, using Helms’s model of white racial identity development as a framework for understanding white students’ responses. The perspective I bring to this discussion is that of an African-American female college professor who has been teaching and/or leading workshops on racism in predominantly white settings since 1980. The student voices represented in this article come from journal entries written by students enrolled in my course on the psychology of racism.
Applying a socially inspired technique (tags) to improve cooperation in P2P networks

In this paper, we focus on the problem of maintaining significant levels of cooperation in peer-to-peer (P2P) networks of selfish adaptive peers. We propose a simple algorithm that maintains high levels of cooperation in such a network while performing the collective task of file sharing. The algorithm is adapted from novel "tag" models of cooperation that do not rely on explicit reciprocity, reputation or trust mechanisms. A sequence of three simulation models is presented-starting with an abstract model of tag-based cooperation (TagWorld) and finishing with a P2P file-sharing model (FileWorld) that puts the technique to work. From analysis of extensive computer simulations, we demonstrate the technique to be scalable, robust, and decentralized; it requires no central servers or authorities. The algorithm is relatively simple: peers do not need to store additional trust information about other nodes or to perform significant additional processing.
Microbial Community Response to Simulated Petroleum Seepage in Caspian Sea Sediments

Anaerobic microbial hydrocarbon degradation is a major biogeochemical process at marine seeps. Here we studied the response of the microbial community to petroleum seepage simulated for 190 days in a sediment core from the Caspian Sea using a sediment-oil-flow-through (SOFT) system. Untreated (without simulated petroleum seepage) and SOFT sediment microbial communities shared 43% bacterial genus-level 16S rRNA-based operational taxonomic units (OTU0.945) but shared only 23% archaeal OTU0.945. The community differed significantly between sediment layers. The detection of fourfold higher deltaproteobacterial cell numbers in SOFT than in untreated sediment at depths characterized by highest sulfate reduction rates and strongest decrease of gaseous and mid-chain alkane concentrations indicated a specific response of hydrocarbon-degrading Deltaproteobacteria. Based on an increase in specific CARD-FISH cell numbers, we suggest the following groups of sulfate-reducing bacteria to be likely responsible for the observed decrease in aliphatic and aromatic hydrocarbon concentration in SOFT sediments: clade SCA1 for propane and butane degradation, clade LCA2 for mid- to long-chain alkane degradation, clade Cyhx for cycloalkanes, pentane and hexane degradation, and relatives of Desulfobacula for toluene degradation. Highest numbers of archaea of the genus Methanosarcina were found in the methanogenic zone of the SOFT core where we detected preferential degradation of long-chain hydrocarbons. Sequencing of masD, a marker gene for alkane degradation encoding (1-methylalkyl)succinate synthase, revealed a low diversity in SOFT sediment with two abundant species-level MasD OTU0.96.
Effects of dietary fats (fish, olive and high-oleic-acid sunflower oils) on lipid composition and antioxidant enzymes in rat liver

The effects of two oleic-acid-rich diets (containing olive oil, OO, and high-oleic-acid sunflower oil, HOSO) on plasma and liver lipid composition detoxification enzyme activities, were compared with those of a fish-oil (FO) diet and a control diet. Compared with the control diet, plasma and hepatic total triacylglycerol concentrations were increased in the animals fed on the HOSO and OO diets and decreased in those fed on the FO diet. The animals fed on FO showed the highest level of cholesterol in the liver and had lower plasma cholesterol concentrations when compared with those fed on the two oleic-acid-rich diets. In comparison with the animals fed on the diets enriched in oleic acid, the FO group showed higher hepatic levels of polyunsaturated fatty acids of the n-3 series and lower levels of fatty acids of the n-6 series. Livers of FO-fed rats, compared with those of OO- and HOSO-fed rats showed: (1) significantly higher activities of catalase (EC 1.11.1.6) glutathione peroxidase (EC 1.11.1.9) and Cu/Zn superoxide dismutase (EC 1.15.1.1); (2) no differences in the NADPH-cytochrome c reductase (EC 1.6.99.3) activity. The HOSO diet had a similar effect on liver antioxidant enzyme activities as the OO diet. In conclusion, it appears that changes in the liver fatty acid composition due mainly to n-3 lipids may enhance the efficiency of the antioxidant defence system. The two monounsaturated fatty acids oils studied (OO and HOSO), with the same high content of oleic acid but different contents of natural antioxidants, had similar effects on the antioxidant enzyme activities measured.
Design of signal peptide bombyxin and its effect on secretory expression efficiency and levels of Helicobacter pylori urease subunit B in silkworm cells and larvae

This study employed a Bac-to-Bac/Bombyx mori bioreactor to mass-produce immunogenic urease subunit B (UreB) from Helicobacter pylori.The signal peptide bombyxin from B. mori was used to promote secretory expression to improve expression levels and was designed and integrated into the UreB gene to generate the Bacmid/BmNPV/(signal peptide)-UreB baculovirus expression system. To determine whether the bombyxin signal peptide resulted in secretory expression of recombinant UreB (rUreB) and to determine the secretory efficiency, we tested the secretory expression level of rUreB in Bm5 cells using ELISA. To further investigate whether secretory expression affected cell viability, cells were evaluated using 0.4% trypan blue staining, and Bacmid/BmNPV/UreB without the signal peptide served as a control. The above recombinant bacmid constructs were injected to silkworm larvae, and the secretory expression level of rUreB was detected using SDS-PAGE and semi-quantitative western blot analysis. The results indicated that the bombyxin signal peptide directed the secretory expression of rUreB and that this expression improved the viability of Bm5 cells. Moreover, the results showed that the expression level of rUreB was 1.5 times higher with the Bacmid/BmNPV constructs containing the bombyxin signal sequence than those without the signal sequence. These results demonstrate that secretory expression can enhance rUreB expression levels and is likely to aid in the large-scale expression and yield of rUreB in silkworm larvae.
Lawrence Berkeley National Laboratory Recent Work Title An immersed boundary method for rigid bodies Permalink

We develop an immersed boundary (IB) method for modeling flows around fixed or moving rigid bodies that is suitable for a broad range of Reynolds numbers, including steady Stokes flow. The spatio-temporal discretization of the fluid equations is based on a standard staggered-grid approach. Fluid-body interaction is handled using Peskin's IB method; however, unlike existing IB approaches to such problems, we do not rely on penalty or fractional-step formulations. Instead, we use an unsplit scheme that ensures the no-slip constraint is enforced exactly in terms of the Lagrangian velocity field evaluated at the IB markers. Fractional-step approaches, by contrast, can impose such constraints only approximately , which can lead to penetration of the flow into the body, and are inconsistent for steady Stokes flow. Imposing no-slip constraints exactly requires the solution of a large linear system that includes the fluid velocity and pressure as well as Lagrange multiplier forces that impose the motion of the body. The principal contribution of this paper is that it develops an efficient preconditioner for this exactly constrained IB formulation which is based on an analytical approximation to the Schur complement. This approach is enabled by the near translational and rotational invariance of Peskin's IB method. We demonstrate that only a few cycles of a geometric multigrid method for the fluid equations are required in each application of the preconditioner, and we demonstrate robust convergence of the overall Krylov solver despite the approximations made in the preconditioner. We empirically observe that to control the condition number of the coupled linear system while also keeping the rigid structure impermeable to fluid, we need to place the immersed boundary markers at a distance of about two grid spacings, which is significantly larger from what has been recommended in the literature for elastic bodies. We demonstrate the advantage of our monolithic solver over split solvers by computing the steady state flow through a two-dimensional nozzle at several Reynolds numbers. We apply the method to a number of benchmark problems at zero and finite Reynolds numbers, and we demonstrate first-order convergence of the method to several analytical solutions and benchmark computations.
Assessing Interpretable, Attribute-related Meaning Representations for Adjective-Noun Phrases in a Similarity Prediction Task

We present a distributional vector space model that incorporates Latent Dirichlet Allocation in order to capture the semantic relation holding between adjectives and nouns along interpretable dimensions of meaning: The meaning of adjective-noun phrases is characterized in terms of ontological attributes that are prominent in their compositional semantics. The model is evaluated in a similarity prediction task based on paired adjective-noun phrases from the Mitchell and Lapata (2010) benchmark data. Comparing our model against a high-dimensional latent word space, we observe qualitative differences that shed light on different aspects of similarity conveyed by both models and suggest integrating their complementary strengths.
Structure determination of a 16.8 kDa copper protein at 2.1 A resolution using anomalous scattering data with direct methods.

The structure of rusticyanin, an acid-stable copper protein, has been determined at 2.1 A resolution by direct methods combined with the single-wavelength anomalous scattering (SAS) of copper (f" = 3.9 e-) and then conventionally refined (Rcryst = 18.7%, Rfree = 21.9%). This is the largest unknown protein structure (Mr approximately /= 16.8 kDa) to be determined using the SAS and direct-methods approach and demonstrates that by exploiting the anomalous signal at a single wavelength, direct methods can be used to determine phases at typical (approximately 2 A) macromolecular crystallographic resolutions. Extrapolating from the size of the anomalous signal for copper (f" approximately 4 e-), this result suggests that the approach could be used for proteins with molecular weights of up to 33 kDa per Se (f"max++ = 8 e- at the 'white line') and 80 kDa for a Pt derivative (f"max = 19 e- at the 'white line', L3 edge). The method provides a powerful alternative in solving a de novo protein structure without either preparing multiple crystals (i.e. isomorphous heavy-atom derivative plus native crystals) or collecting multi-wavelength anomalous diffraction (MAD) data.
A Hash-based Hierarchical Algorithm for Massive Text Clustering

Text clustering is the process of segmenting a particular collection of texts into subgroups including content based similar ones. The purpose of text clustering is to meet human interests in information searching and understanding. This study proposes a new fast hierarchical text clustering algorithm HBSH (Hash-based Structure Hierarchical Clustering), which is suitable for massive text clustering. This algorithm uses hash table instead of numerical vectors as its input data. Compared with the other clustering algorithms, the HBSH performs the text clustering process without setting clustering center number and has minor space complexity in advance, which can achieve better performance. The experimental results illustrate that the average time of HBSH is faster than that of traditional text clustering algorithms.
Expression of multiple slow myosin heavy chain genes reveals a diversity of zebrafish slow twitch muscle fibres with differing requirements for Hedgehog and Prdm1 activity

The zebrafish embryo develops a series of anatomically distinct slow twitch muscle fibres that characteristically express genes encoding lineage-specific isoforms of sarcomeric proteins such as MyHC and troponin. We show here that different subsets of these slow fibres express distinct members of a tandem array of slow MyHC genes. The first slow twitch muscle fibres to differentiate, which are specified by the activity of the transcription factor Prdm1 (also called Ubo or Blimp1) in response to Hedgehog (Hh) signalling, express the smyhc1 gene. Subsequently, secondary slow twitch fibres differentiate in most cases independently of Hh activity. We find that although some of these later-forming fibres also express smyhc1, others express smyhc2 or smyhc3. We show that the smyhc1-positive fibres express the ubo (prdm1) gene and adopt fast twitch fibre characteristics in the absence of Prdm1 activity, whereas those that do not express smyhc1 can differentiate independently of Prdm1 function. Conversely, some smyhc2-expressing fibres, although independent of Prdm1 function, require Hh activity to form. The adult trunk slow fibres express smyhc2 and smyhc3, but lack smyhc1 expression. The different slow fibres in the craniofacial muscles variously express smyhc1, smyhc2 and smyhc3, and all differentiate independently of Prdm1.
A comprehensively characterized large panel of head and neck cancer patient‐derived xenografts identifies the mTOR inhibitor everolimus as potential new treatment option

Patient‐derived xenograft (PDX) models have shown to reflect original patient tumors better than any other preclinical model. We embarked in a study establishing a large panel of head and neck squamous cell carcinomas PDX for biomarker analysis and evaluation of established and novel compounds. Out of 115 transplanted specimens 52 models were established of which 29 were characterized for response to docetaxel, cetuximab, methotrexate, carboplatin, 5‐fluorouracil and everolimus. Further, tumors were subjected to sequencing analysis and gene expression profiling of selected mTOR pathway members. Most frequent response was observed for docetaxel and cetuximab. Responses to carboplatin, 5‐fluorouracil and methotrexate were moderate. Everolimus revealed activity in the majority of PDX. Mutational profiling and gene expression analysis did not reveal a predictive biomarker for everolimus even though by trend RPS6KB1 mRNA expression was associated with response. In conclusion we demonstrate a comprehensively characterized panel of head and neck cancer PDX models, which represent a valuable and renewable tissue resource for evaluation of novel compounds and associated biomarkers.
Self-paced Learning for Weakly Supervised Evidence Discovery in Multimedia Event Search

Multimedia event detection has been receiving increasing attention in recent years. Besides recognizing an event, the discovery of evidences (which is refered to as "recounting") is also crucial for user to better understand the searching result. Due to the difficulty of evidence annotation, only limited supervision of event labels are available for training a recounting model. To deal with the problem, we propose a weakly supervised evidence discovery method based on self-paced learning framework, which follows a learning process from easy "evidences" to gradually more complex ones, and simultaneously exploit more and more positive evidence samples from numerous weakly annotated video segments. Moreover, to evaluate our method quantitatively, we also propose two metrics, \textit{PctOverlap} and \textit{F1-score}, for measuring the performance of evidence localization specifically. The experiments are conducted on a subset of TRECVID MED dataset and demonstrate the promising results obtained by our method.
Social Cognitive Mediators and Moderators of the Relation Between Experiences of Community Violence and Adolescent Outcomes

Eric Dubow, Ph.D., Advisor This study examined moderation and mediation effects of three types of social cognitions (perceived social support, future expectations, and normative beliefs about aggression) on the relation between environmental experiences of aggression/violence and adolescent outcomes (depression and aggression). Additionally, this study sought to determine if moderation and mediation effects were varied based on the type of environmental experience of aggression/violence (victimization or witnessing) and/or on the level of severity of these experiences (low-severity or high-severity). Using a shortterm longitudinal design, 248 high school students in 9 through 12 grade were surveyed twice, three months apart, regarding victimization experiences, witnessing experiences, perceived social support, future expectations, normative beliefs, aggressive behavior, and depressive symptoms. Teachers completed surveys about students’ aggressive behavior and depressive symptoms. A confirmatory factor analysis indicated that experiences of aggression/violence fit a four-factor model (low-severity victimization, high-severity victimization, lowseverity witnessing, and high-severity witnessing) better than two or one factor models. Contrary to previous research, perceived social support did not moderate the relation between victimization and depression, but had a protective-reactive effect on the relations between victimization and aggression and between witnessing and aggression. Future expectations moderated experiences of aggression/violence (both victimization and