Alternative trans-splicing of Caenorhabditis elegans sma-9/schnurri generates a short transcript that provides tissue-specific function in BMP signaling

<p>Abstract</p> <p>Background</p> <p>Transcription cofactors related to <it>Drosophila </it>Schnurri facilitate the transcriptional programs regulated by BMP signaling in <it>C. elegans</it>, <it>Drosophila</it>, Xenopus, and mouse. In different systems, Schnurri homologs have been shown to act as either agonists or antagonists of Smad function, and as either positive or negative regulators of transcription. How Schnurri proteins achieve this diversity of activities is not clear. The <it>C. elegans sma-9/schnurri </it>locus undergoes alternative splicing, including an unusual <it>trans</it>-splicing event that could generate two non-overlapping shorter transcripts.</p> <p>Results</p> <p>We demonstrate here that the shorter transcripts are expressed <it>in vivo</it>. Furthermore, we find that one of the short transcripts plays a tissue-specific role in <it>sma-9 </it>function, contributing to the patterning of male-specific sensory rays, but not to the regulation of body size. Based on previous results, we suggest that this transcript encodes a C-terminal SMA-9 isoform that may provide transcriptional activation activity, while full length isoforms may mediate transcriptional repression and/or activation in a context-dependent manner.</p> <p>Conclusion</p> <p>The alternative <it>trans</it>-splicing of <it>sma-9 </it>may contribute to the diversity of functions necessary to mediate tissue-specific outputs of BMP signaling.</p

A Partially Feasible Distributed SQO Method for Two-block General Linearly Constrained Smooth Optimization

This paper discusses a class of two-block smooth large-scale optimization problems with both linear equality and linear inequality constraints, which have a wide range of applications, such as economic power dispatch, data mining, signal processing, etc.Our goal is to develop a novel partially feasible distributed (PFD) sequential quadratic optimization (SQO) method (PFD-SQO method) for this kind of problems. The design of the method is based on the ideas of SQO method and augmented Lagrangian Jacobian splitting scheme as well as feasible direction method,which decomposes the quadratic optimization (QO) subproblem into two small-scale QOs that can be solved independently and parallelly. A novel disturbance contraction term that can be suitably adjusted is introduced into the inequality constraints so that the feasible step size along the search direction can be increased to 1. The new iteration points are generated by the Armijo line search and the partially augmented Lagrangian function that only contains equality constraints as the merit function. The iteration points always satisfy all the inequality constraints of the problem. The theoretical properties, such as global convergence, iterative complexity, superlinear and quadratic rates of convergence of the proposed PFD-SQO method are analyzed under appropriate assumptions, respectively. Finally, the numerical effectiveness of the method is tested on a class of academic examples and an economic power dispatch problem, which shows that the proposed method is quite promising

pH-responsive stearic acid-O-carboxymethyl chitosan assemblies as carriers delivering small molecular drug for chemotherapy.

Recently, chemotherapy is still widely exploited to treat the residual, infiltrative tumor cells after surgical resection. However, many anticancer drugs are limited in clinical application due to their poor water-solubility (hydrophibic) and stability, low bioavailability, and unfavorable pharmacokinetics. Herein, an amphiphilic stearic acid-O-carboxymethyl chitosan (SA-CMC) conjugate was synthesized by amide linkage of SA to the backbone of CMC polymer and then self-assembled into nanoparticles (SA-CMC NPs) with the hydrodynamic particle size of ~100 nm. Subsequently, Paclitaxel (PTX) as a potent and broad-spectrum anticancer drug was loaded into SA-CMC NPs by a probe sonication combined with dialysis method. Owing to the multi-hydrophobic inner cores, the prepared PTX-SA-CMC NPs showed a considerable drug-loading capacity of ~19 wt% and a biphasic release behavior with an accumulative release amount in the range of 70-90% within 72 h. PTX-SA-CMC NPs remarkably enhanced the accumulation at the tumor sites by passive targeting followed by cellular endocytosis. Upon the stimuli of acid, PTX-SA-CMC NPs showed exceptional instability by pH change, thereby triggering the rapid disassembly and accelerated drug release. Consequently, compared with Cremophor EL-based free PTX treatment, PTX-SA-CMC NPs under pH-stimuli accomplished highly efficient apoptosis in cancer cells and effectively suppression of tumors by chemotherapy. Overall, PTX-SA-CMC NPs integrating imaging capacity might be a simple yet feasible PTX nanosystem for tumor-targeted delivery and cancer therapy

pH-responsive stearic acid- O -carboxymethyl chitosan assemblies as carriers delivering small molecular drug for chemotherapy

Abstract(#br)Recently, chemotherapy is still widely exploited to treat the residual, infiltrative tumor cells after surgical resection. However, many anticancer drugs are limited in clinical application due to their poor water-solubility (hydrophibic) and stability, low bioavailability, and unfavorable pharmacokinetics. Herein, an amphiphilic stearic acid- O -carboxymethyl chitosan (SA-CMC) conjugate was synthesized by amide linkage of SA to the backbone of CMC polymer and then self-assembled into nanoparticles (SA-CMC NPs) with the hydrodynamic particle size of ~100 nm. Subsequently, Paclitaxel (PTX) as a potent and broad-spectrum anticancer drug was loaded into SA-CMC NPs by a probe sonication combined with dialysis method. Owing to the multi-hydrophobic inner cores, the prepared PTX-SA-CMC NPs showed a considerable drug-loading capacity of ~19 wt% and a biphasic release behavior with an accumulative release amount in the range of 70–90% within 72 h. PTX-SA-CMC NPs remarkably enhanced the accumulation at the tumor sites by passive targeting followed by cellular endocytosis. Upon the stimuli of acid, PTX-SA-CMC NPs showed exceptional instability by pH change, thereby triggering the rapid disassembly and accelerated drug release. Consequently, compared with Cremophor EL-based free PTX treatment, PTX-SA-CMC NPs under pH-stimuli accomplished highly efficient apoptosis in cancer cells and effectively suppression of tumors by chemotherapy. Overall, PTX-SA-CMC NPs integrating imaging capacity might be a simple yet feasible PTX nanosystem for tumor-targeted delivery and cancer therapy

Role of TMPRSS2-ERG Gene Fusion in Negative Regulation of PSMA Expression

Prostate specific membrane antigen (PSMA) is overexpressed in prostatic adenocarcinoma (CaP), and its expression is negatively regulated by androgen stimulation. However, it is still unclear which factors are involved in this downregulation. TMPRSS2-ERG fusion is the most common known gene rearrangement in prostate carcinoma. Androgen stimulation can increase expression of the TMPRSS2-ERG fusion in fusion positive prostate cancer cells. The purpose of this investigation is to determine whether PSMA expression can be regulated by the TMPRSS2-ERG gene fusion. We employed two PSMA positive cell lines: VCaP cells, which harbor TMPRSS2-ERG fusion, and LNCaP cells, which lack the fusion. After 24 hours of androgen treatment, TMPRSS2-ERG mRNA level was increased in VCaP cells. PSMA mRNA level was dramatically decreased in VCaP cells, while it only has moderate change in LNCaP cells. Treatment with the androgen antagonist flutamide partially restored PSMA expression in androgen-treated VCaP cells. Knocking down ERG by siRNA in VCaP cells enhances PSMA expression both in the presence and absence of synthetic androgen R1881. Overexpressing TMPRSS2-ERG fusions in LNCaP cells downregulated PSMA both in the presence or absence of R1881, while overexpressing wild type ERG did not. Using PSMA-based luciferase reporter assays, we found TMPRSS2-ERG fusion can inhibit PSMA activity at the transcriptional level. Our data indicated that downregulation of PSMA in androgen-treated VCaP cells appears partially mediated by TMPRSS2-ERG gene fusion

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Two New Conjugate Gradient Methods for Unconstrained Optimization

The conjugate gradient method is very effective in solving large-scale unconstrained optimal problems. In this paper, on the basis of the conjugate parameter of the conjugate descent (CD) method and the second inequality in the strong Wolfe line search, two new conjugate parameters are devised. Using the strong Wolfe line search to obtain the step lengths, two modified conjugate gradient methods are proposed for general unconstrained optimization. Under the standard assumptions, the two presented methods are proved to be sufficient descent and globally convergent. Finally, preliminary numerical results are reported to show that the proposed methods are promising

New approach for sugarcane disease recognition through visible and near-infrared spectroscopy and a modified wavelength selection method using machine learning models

The proliferation of pathogenic fungi in sugarcane crops poses a significant threat to agricultural productivity and economic sustainability. Early identification and management of sugarcane diseases are therefore crucial to mitigate the adverse impacts of these pathogens. In this study, visible and near-infrared spectroscopy (380–1400 nm) combined with a novel wavelength selection method, referred to as modified flower pollination algorithm (MFPA), was utilized for sugarcane disease recognition. The selected wavelengths were incorporated into machine learning models, including Naïve Bayes, random forest, and support vector machine (SVM). The developed simplified SVM model, which utilized the MFPA wavelength selection method yielded the best performances, achieving a precision value of 0.9753, a sensitivity value of 0.9259, a specificity value of 0.9524, and an accuracy of 0.9487. These results outperformed those obtained by other wavelength selection approaches, including the selectivity ratio, variable importance in projection, and the baseline method of the flower pollination algorithm