Predictive value of anti-Mullerian hormone for pregnancy outcomes following assisted reproductive techniques (ART) in Southwest China.

Background: Anti-Müllerian hormone (AMH) is secreted by granulosa cells in preantral follicles and small antral follicles. There is limited information about whether serum AMH levels are related to pregnancy outcomes during in vitro fertilization and embryo transfer (IVF-ET). The aim of this study was to provide a theoretical basis for improving pregnancy outcomes.

Identification and validation of tumor microenvironment-related lncRNA prognostic signature for uveal melanoma.

Aim: To investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis.

Methods: UM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated.

Combining Dual-Light Emissions to Achieve Efficient Broadband Yellowish-Green Luminescence in One-Dimensional Hybrid Lead Halides.

In recent years, low-dimensional lead halides have emerged as some of most attractive photoelectric materials due to their intrinsic broadband emissions with a potential application in white-light emitting diodes. To achieve the desired performance, tremendous research has emphasized the modulation of inorganic components as optical centers; however, less work has paid attention to the direct contribution of the organic components. Herein, we successfully assembled two new hybrid lead halides of [HBPP]PbX (X = Br, , and Cl, ) containing one-dimensional double [PbX] chains using optically active 1,3-bis(4-pyridyl)-propane (BPP) as an organic cation.

Relationship Between Anti-Müllerian Hormone and Fertilization-Embryo Transfer in Clinical Pregnancy.

Objectives: To retrospectively analyze the correlation between anti-Müllerian hormone (AMH) and the number of oocytes obtained by controlled ovarian hyperstimulation (COH) in women of different ages and explore the factors affecting fertilization and embryo transfer (IVF-ET) in clinical pregnancy of infertile women to provide evidence for infertile women to choose assisted reproduction strategies.

Methods: Infertile women who received IVF-ET or intracytoplasmic sperm injection and embryo transfer (ICSI-ET) treatment in the reproductive center of XX hospital between October 2018 and September 2019 were included. Patient data on medical records, age, body mass index (BMI), years of infertility, basic follicle-stimulating hormone (FSH), basic luteinizing hormone (LH), basic estradiol (E), anti-Müllerian hormone level (AMH), antral follicle count (AFC), gonadotropins (Gn) medication days, Gn dosage, endometrial thickness on transplantation day, the number of retrieved oocytes, the number of mature oocytes obtained, the number of embryos transferred, clinical pregnancy status, etc.

Tandem Lewis Pair Polymerization and Organocatalytic Ring-Opening Polymerization for Synthesizing Block and Brush Copolymers.

Lewis pair polymerization is a powerful method for preparing soluble polymers bearing pendant active vinyl groups by directly polymerizing dissymmetric divinyl polar monomers. Herein, we present a strategy for synthesizing block and brush copolymers via tandem Lewis pair polymerization of methacrylates, "thiol-ene" click reaction and organocatalytic ring-opening polymerization of lactide.

The prediction of palmitoylation site locations using a multiple feature extraction method.

As an extremely important and ubiquitous post-translational lipid modification, palmitoylation plays a significant role in a variety of biological and physiological processes. Unlike other lipid modifications, protein palmitoylation and depalmitoylation are highly dynamic and can regulate both protein function and localization. The dynamic nature of palmitoylation is poorly understood because of the limitations in current assay methods.

Position-specific analysis and prediction for protein lysine acetylation based on multiple features.

Protein lysine acetylation is a type of reversible post-translational modification that plays a vital role in many cellular processes, such as transcriptional regulation, apoptosis and cytokine signaling. To fully decipher the molecular mechanisms of acetylation-related biological processes, an initial but crucial step is the recognition of acetylated substrates and the corresponding acetylation sites. In this study, we developed a position-specific method named PSKAcePred for lysine acetylation prediction based on support vector machines.

Identifying protein quaternary structural attributes by incorporating physicochemical properties into the general form of Chou's PseAAC via discrete wavelet transform.

In vivo, some proteins exist as monomers and others as oligomers. Oligomers can be further classified into homo-oligomers (formed by identical subunits) and hetero-oligomers (formed by different subunits), and they form the structural components of various biological functions, including cooperative effects, allosteric mechanism and ion-channel gating. Therefore, with the avalanche of protein sequences generated in the post-genomic era, it is very important for both basic research and the pharmaceutical industry to acquire the possible knowledge about quaternary structural attributes of their proteins of interest.

A method to distinguish between lysine acetylation and lysine methylation from protein sequences.

Lysine acetylation and methylation are two major post-translational modifications of lysine residues. They play vital roles in both biological and pathological processes. Specific lysine residues in H3 histone protein tails appear to be targeted for either acetylation or methylation.

PMeS: prediction of methylation sites based on enhanced feature encoding scheme.

Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases.

PredSulSite: prediction of protein tyrosine sulfation sites with multiple features and analysis.

Tyrosine sulfation is a ubiquitous posttranslational modification that regulates extracellular protein-protein interactions, intracellular protein transportation modulation, and protein proteolytic process. However, identifying tyrosine sulfation sites remains a challenge due to the lability of sulfation sequences. In this study, we developed a method called PredSulSite that incorporates protein secondary structure, physicochemical properties of amino acids, and residue sequence order information based on support vector machine to predict sulfotyrosine sites.

PLMLA: prediction of lysine methylation and lysine acetylation by combining multiple features.

Post-translational lysine methylation and acetylation are two major modifications of lysine residues. They play critical roles in various biological processes, especially in gene regulation. Identification of protein methylation and acetylation sites would be a foundation for understanding their modification dynamics and molecular mechanism.

A novel algorithm combining support vector machine with the discrete wavelet transform for the prediction of protein subcellular localization.

Knowing the subcellular localization of proteins within the cell is an important step in elucidating its role in biological processes, its function and its potential as a drug target for disease diagnosis. As the number of complete genomes rapidly increases, accurate and efficient methods that automatically predict the subcellular localizations become more urgent. In the current paper, we developed a novel method that coupled the discrete wavelet transform with support vector machine based on the amino acid polarity to predict the subcellular localizations of prokaryotic and eukaryotic proteins.

OligoPred: a web-server for predicting homo-oligomeric proteins by incorporating discrete wavelet transform into Chou's pseudo amino acid composition.

In vivo, some proteins exist as monomers (single polypeptide chains) and others as oligomers. Not like monomers, oligomers are composed of two or more chains (subunits) that are associated with each other through non-covalent interactions and, occasionally, through disulfide bonds. These proteins are the structural components of various biological functions, including cooperative effects, allosteric mechanisms and ion-channel gating.

Predicting homo-oligomers and hetero-oligomers by pseudo-amino acid composition: an approach from discrete wavelet transformation.

Many proteins exist in vivo as oligomers with different quaternary structural attributes rather than as individual chains. These proteins are the structural components of various biological functions, including cooperative effects, allosteric mechanisms and ion-channel gating. With the dramatic increase in the number of protein sequences submitted to the public databank, it is important for both basic research and drug discovery research to acquire the knowledge about possible quaternary structural attributes of their interested proteins in a timely manner.

Identify submitochondria and subchloroplast locations with pseudo amino acid composition: approach from the strategy of discrete wavelet transform feature extraction.

It is very challenging and complicated to predict protein locations at the sub-subcellular level. The key to enhancing the prediction quality for protein sub-subcellular locations is to grasp the core features of a protein that can discriminate among proteins with different subcompartment locations. In this study, a different formulation of pseudoamino acid composition by the approach of discrete wavelet transform feature extraction was developed to predict submitochondria and subchloroplast locations.

Prediction of the types of membrane proteins based on discrete wavelet transform and support vector machines.

Membrane proteins are crucial for many biological functions and have become attractive targets for both basic research and drug discovery. With the unprecedented increasing of newly found protein sequences in the post-genomic era, it is both time-consuming and expensive to determine the types of newly found membrane proteins solely with traditional experiment, and so it is highly demanded to develop an automatic method for fast and accurately identifying the type of membrane proteins according to their amino acid sequences. In this study, the discrete wavelet transform (DWT) and support vector machine (SVM) have been used for the prediction of the types of membrane proteins.

Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine.

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. As a result of genome and other sequencing projects, the gap between the number of known apoptosis protein sequences and the number of known apoptosis protein structures is widening rapidly.