NVB-tree: Failure-Atomic B+-tree for Persistent Memory

Department of Computer EngineeringEmerging non-volatile memory has opened new opportunities to re-design the entire system software stack and it is expected to break the boundaries between memory and storage devices to enable storage-less systems. Traditionally, B-tree has been used to organize data blocks in storage systems. However, B-tree is optimized for disk-based systems that read and write large blocks of data. When byte-addressable non-volatile memory replaces the block device storage systems, the byte-addressability of NVRAM makes it challenge to enforce the failure-atomicity of B-tree nodes. In this work, we present NVB-tree that addresses this challenge, reducing cache line flush overhead and avoiding expensive logging methods. NVB-tree is a hybrid tree that combines the binary search tree and the B+-tree, i.e., keys in each NVB-tree node are stored as a binary search tree so that it can benefit from the byte-addressability of binary search trees. We also present a logging-less split/merge scheme that guarantees failure-atomicity with 8-byte memory writes. Our performance study shows that NVB-tree outperforms the state-of-the-art persistent index - wB+-tree by a large margin.ope

Proteomic variation in Korean ginseng (Panax ginseng C.A. Meyer) isolates from different geographic regions

Korean ginseng is a traditional medicine that is widely used in Korea. In this study, a proteomic approach was used to investigate variations in Korean ginseng isolates that are associated with ecologic and geographic differences. Ginseng samples were collected from four geographically isolated locations in Korea: North gyeonggi, Gochang, Geumsan and Kanghwa. Two-dimensional gel electrophoresis (2-DE) and peptide fingerprinting of tryptic digests by mass spectrometry (MALDI-TOF) revealed primary ginseng root region-specific variations in protein profiles in these distinct areas. Thirty seven (37) major proteins that are common to the main root of ginseng at all four geographic sites and six proteins that are specific to the main root of a local ginseng (Kanghwa) were identified. Most of the major common proteins identified could be classified into the following functional categories: (i) stress response; (ii) transcription and translation; (iii) nucleotide metabolism; (iv) plant hormone response; (v) signal transduction; (vi) protein degradation; (vii) protein destination and storage; and (viii) unassigned. The results show that Korean ginseng species can be distinguished on the basis of classical proteomics.Keywords: Panax ginseng C.A. Meyer, 2-DE, peptide fingerprinting, classical proteomic

Stimuli-responsive cancer therapy based on porous materials

Department of ChemistrySurgical treatment, radiation therapy, and chemotherapy drugs are used to treat cancer. However, this treatment often kills normal cells and causes side effects. In addition, most cancer drugs are hydrophobic and therefore pose a number of problems to apply to the body. To solve this problem, nanomedicinehas been used for cancer treatment. This nanomedicine selectively accumulates to the cancer cells through passive and active targeting. Organic nanomedicine, involving micelle, liposomes, and proteins, has low stability in the body. Inorganic nanomedicine, on the other hand, has high stability, but a low loading capacity because it is limited to the direct modification method. To overcome this challenge, research has been conducted into porous materials in drug delivery. Porous material has high body-stability and drug-loading capacity. In addition, a variety of functional molecules are modified to the outer and inner surfaces, and the multifunctionality of porous materials facilitates stimulated drug release. In this dissertation, various stimuli-responsive porous materials were described for cancer therapy. A membrane composed of a Dendrimer (Den) and a gold nanorod (GNR) has pores through which the drug can be released. In addition, GNR shows the effect of surface plasmon resonance (SPR) even after membrane synthesis, and it generates heat by NIR irradiation and increases the local temperature that promotes drug release. This controlled release of the drug sustains the drug concentration within the therapeutic window, thereby reducing side effects and enhancing benefits. Unlike bare GNR, GNR capped with mesoporous silica (GNR@MS) has pores that facilitate drug loading, thereby increasing the chemotherapy effect of nanoparticles. However, the weak interaction between the drug and the MS surface causes the loaded drug to be released from the nanoparticle during the delivery process. In order to prevent premature release, a glutathione (GSH)-responsive polymer (PEG-PDS) is coated on GNR@MS surfaces to block the pores. Polymer coated GNR@MS (GNR@MS@PDS) increases the local temperature in response to NIR irradiation, which induces drug-release by expanding PEG-PDS. Furthermore, the PEG-PDS polymer is degraded by GSH, opening the pore of GN @MS and releasing the drug at the cancer cells. This dual-stimulus system can control the time and space of drug release in the body. NanoMOF with high surface and porosity is attracting much attention as a drug-delivery system. In particular, PCN-224 has high stability in aqua state, and the porphyrin derivative organic linker constituting of PCN is used as a PDT agent. That facilitates the photodynamic therapy under light irradiation without any additional processes. These properties enable combined chemo & PDT to enhance cancer treatment effectiveness. In addition, MOF can be easily modified by hyaluronic acid, while HA can control the drug release in response to HAdase as well as interact with the CD44 receptor to selectively target cancer. The unsaturated metal clusters of nanoMOF can form a coordination bond with the Lewis base, and the nanoMOF can easily be post-functionalized using this character. Various systems use this phenomenon to convert the cancer-targeting ligand to MOF. However, proteins and biochemicals, which have Lewis bases, are present in the body and compete with modified ligands to interact with MOF and induce ligand detachment. To overcome these problems, Folic acid-modified polyacrylic acid (PAA) was coated to the MOF surface. The polyvalent coordination between PAA and MOF increases the binding force of the ligand and the stability of the drug-delivery system in the body. Stimulus-responsive systems based on porous materials can effectively treat cancer with advantages like drug-concentration control, dual-stimulus response, combined therapy and increased biostability.clos

A low-cost Lactobacillus salivarius L29 growth medium containing molasses and corn steep liquor allows the attainment of high levels of cell mass and lactic acid production

The aim of the present work was to formulate a Lactobacillus salivarius L29 industrial fermentation medium. High cell numbers and good levels of lactic acid by a L. salivarius L29 were obtained after shake flask fermentation using molasses as the sole carbon source and corn steep liquor (CSL (industrial grade); an organic source of N) as the principal nitrogen source. The optimum concentrations of molasses and CSL facilitating good cell growth and high-level lactic acid production were found to be 6 and 6% (both v/v), respectively. The maximum cell yield was 2.02 × 109 CFU/mL, thus about 15% lower than that obtained when MRS broth was employed for 5-L fermenters culture. Lactic acid production upon growth in industrial broth was 105 g/L; the total sugar content of the medium was 118 g/L (sucrose: glucose: fructose 68:14:18; w/w/w). Upon growth in De Man, Rogosa and Sharpe (MRS) broth (the total sugar content of which was 127 g/L, all of which was glucose), the lactic acid yield was 120 g/L. The optimized industrial growth medium was significantly more economical than were conventional broths.Keywords: Lactobacillus salivarius L29, molasses, corn steep liquor, culture medium optimization, lactic acidAfrican Journal of Biotechnology Vol. 12(16), pp. 2013-201

Memory and Decoding in Signaling Transduction Pathways

Intercellular communication allows cells to broadcast and receive necessary information for decision making, and is essential for development, growth, and maintenance of a community of cells in a multicellular organism. Signaling pathways are highly conserved systems of communication between cells, each composed of a distinct network of protein interactions that detect extracellular signal and transduce the signal information for cellular response. A signaling pathway typically encodes information from signaling events into dynamics of second messengers, intracellular molecules in the signaling pathway that activate in response to signal and initiate cellular response. Therefore, understanding how information is encoded in second messenger dynamics, and how transcriptional machinery decode and generate output response is an important aspect in investigating how signaling information is transduced inside a cell. In the first chapter, we investigate the timescales of memory in endogenous β-catenin and Smad3, second messengers in the Wnt and Tgf-β pathways, through single cell timelapse microscopy. The findings demonstrate that both second messengers have short memory and high cell-to-cell variability, and that their memory is tunable through modulating cellular contexts. In the second chapter, we investigate decoding of information from β-catenin in the Wnt pathway. We identify a novel 11-bp DNA element that recruit β-catenin for transcriptional suppression. This negative regulatory element is shown to act in conjunction with the canonical Wnt responsive element to form an incoherent feedforward loop (IFFL). Through mathematical simulations, we present how the IFFL circuit can generate complex output functions in decoding β-catenin dynamics, which include those that confer robustness against perturbations in signaling response such as band-pass filtering and fold change detection.</p

Mixed cultures of Kimchi lactic acid bacteria show increased cell density and lactate productivity

This study was carried out to determine the characteristics of cell growth, lactate production and amino acid secretion among four kimchi lactic acid bacteria (Leuconostoc mesenteroides JEI, Leuconostoc kimchi 132, Lactobacillus sakei 171, and Weissella koreensis 521) alone and in selected mixtures. In solo culture, L. sakei 171 was superior in cell growth, lactate production and the release of amino acids to the extracellular medium. In contrast, W. koreensis 521 showed the least cell growth, lactate production and amino acid release among the tested bacteria. W. koreensis 521 consumed essential amino acids for growth, whereas L. sakei 171 released several of the essential amino acids important for the growth of W. koreensis 521. When we mixed L. sakei 171 and W. koreensis 521 at optimal concentrations, the obtained cell growth and lactic acid production were higher than those seen with either strain alone, presumably reflecting mutual effects between the two strains. Mixed culture of two kimchi lactobacilli on batch fermentation increased the cell density and lactic acid production with low nutrients consumption. These results suggest that mixed culturing of kimchi lactobacilli may be more effective than single culturing of kimchi lactic acid bacteria for improving lactic acid production.Keywords: Kimchi lactic acid bacteria, amino acid utilization, nutrients consumption.African Journal of BiotechnologyVol. 12(25), pp. 4000-400

DiffBlender: Scalable and Composable Multimodal Text-to-Image Diffusion Models

The recent progress in diffusion-based text-to-image generation models has significantly expanded generative capabilities via conditioning the text descriptions. However, since relying solely on text prompts is still restrictive for fine-grained customization, we aim to extend the boundaries of conditional generation to incorporate diverse types of modalities, e.g., sketch, box, and style embedding, simultaneously. We thus design a multimodal text-to-image diffusion model, coined as DiffBlender, that achieves the aforementioned goal in a single model by training only a few small hypernetworks. DiffBlender facilitates a convenient scaling of input modalities, without altering the parameters of an existing large-scale generative model to retain its well-established knowledge. Furthermore, our study sets new standards for multimodal generation by conducting quantitative and qualitative comparisons with existing approaches. By diversifying the channels of conditioning modalities, DiffBlender faithfully reflects the provided information or, in its absence, creates imaginative generation.Comment: 18 pages, 16 figures, and 3 table

CAST: Cluster-Aware Self-Training for Tabular Data

Self-training has gained attraction because of its simplicity and versatility, yet it is vulnerable to noisy pseudo-labels. Several studies have proposed successful approaches to tackle this issue, but they have diminished the advantages of self-training because they require specific modifications in self-training algorithms or model architectures. Furthermore, most of them are incompatible with gradient boosting decision trees, which dominate the tabular domain. To address this, we revisit the cluster assumption, which states that data samples that are close to each other tend to belong to the same class. Inspired by the assumption, we propose Cluster-Aware Self-Training (CAST) for tabular data. CAST is a simple and universally adaptable approach for enhancing existing self-training algorithms without significant modifications. Concretely, our method regularizes the confidence of the classifier, which represents the value of the pseudo-label, forcing the pseudo-labels in low-density regions to have lower confidence by leveraging prior knowledge for each class within the training data. Extensive empirical evaluations on up to 20 real-world datasets confirm not only the superior performance of CAST but also its robustness in various setups in self-training contexts.Comment: 17 pages with appendi

DreamStyler: Paint by Style Inversion with Text-to-Image Diffusion Models

Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain. However, expressing unique characteristics of an artwork (e.g. brushwork, colortone, or composition) with text prompts alone may encounter limitations due to the inherent constraints of verbal description. To this end, we introduce DreamStyler, a novel framework designed for artistic image synthesis, proficient in both text-to-image synthesis and style transfer. DreamStyler optimizes a multi-stage textual embedding with a context-aware text prompt, resulting in prominent image quality. In addition, with content and style guidance, DreamStyler exhibits flexibility to accommodate a range of style references. Experimental results demonstrate its superior performance across multiple scenarios, suggesting its promising potential in artistic product creation