The U.S. Holstein cattle have unprecedentedly large samples for genomic evaluation with genotypes of Single Nucleotide Polymorphism (SNP) markers and phenotypic observations of dairy quantitative traits. Such large samples provided unprecedented opportunities for the discovery of genetic variants and mechanisms affecting quantitative traits in Holstein cattle. Recent studies using the Holstein large samples on finding genetic variants affecting quantitative traits included a fat percentage study and two studies on reproductive traits. The fat percentage study confirmed that a chromosome region interacted with all chromosomes and the reproductive studies detected sharply negative homozygous recessive genotypes that were recommended for heifer culling. These novel findings provided examples showing the power of large-sample genomic mining for quantitative traits.
Data mining is also known as the knowledge discovery data, which collects powerful and useful information from the large data and it is useful in future trends. The spontaneous of using large data from the discovered trends and the ways lead to the usage of simple research. Data mining enlightened the algorithms of mathematical studies to components of the data and calculates the possibility of future events.
Objectives: To analyze the position Indonesia's HCI compared to ASEAN countries in terms of the quality of health and education Study design: Analyzing secondary data published by the World Bank on the calculation HCI in 2018, Basic Health Research Report 2018 from the Indonesian Ministry of Health, Publication the Central Bureau of Statistics, various international research reports. The validity of interpreting numbers through deducto verificato which has scientific truth because it passes through the stages of scientific methodology that are generally accepted in the world of science. Principal findings: Acquisition of HCI in 2018; Singapore 0.90, Vietnam 0.67, Malaysia 0.65, Thailand 0.61, Philippines 0.58, Indonesia 0.55, Camboja 0.49, Myanmar 0.49, Timor Leste 0.47, and Laos 0.46. Indonesia's position is in 6th place among ASEAN Countries, above Cambodia, Myanmar, Timor Leste, and Laos. This means that children born in Singpura have the opportunity to utilize their abilities to generate an income of 0.90, while every child born in Indonesia only has 55% of the resources to manage available opportunities. The remaining 0.45% is used as idle capacity. The remaining capacity is probably due to low supply of nutrition, growth and development constraints, low Quality Adjusted Life Year due to various diseases, low access to modern health services, low quality of classroom learning, and low purchasing power which is robbing the poor. Conclusion: Increasing HCI in Indonesia needs to be a serious concern of the Government, religious and social institutions, international agencies, communities, and families so that Indonesian people can compete in the 4.0 era.
Posttranslational histone tail modifications are known to play a role in leukemogenesis and are therapeutic targets. A global analysis of the level and patterns of expression of multiple histone-modifying proteins (HMP) in acute myeloid leukemia (AML) and the effect of different patterns of expression on outcome and prognosis has not been investigated in AML patients. Here we analyzed 20 HMP by reverse phase protein array (RPPA) in a cohort of 205 newly diagnosed AML patients. Protein levels were correlated with patient and disease characteristics, including survival and mutational state. We identified different protein clusters characterized by higher (more on) or lower (more off) expression of HMP, relative to normal CD34+ cells. On state of HMP was associated with poorer outcome compared to normal-like and a more off state. FLT3 mutated AML patients were significantly overrepresented in the more on state. DNA methylation related mutations showed no correlation with the different HMP states. In this study, we demonstrate for the first time that HMP form recurrent patterns of expression and that these significantly correlate with survival in newly diagnosed AML patients.
Aims: The myocardial energy metabolism during Atrial Fibrillation (AF) a research hotspot. Proteomics provides a new method for the study of atrial fibrillation; however, there are no related studies of the effect of the Left Atrial Appendage (LAA) on the energy metabolism of the atrial muscle. We use proteomics to analyze the effect of resection of the LAA on the energy metabolism of the left atrial myocardial cells in beagle dogs with rapid atrial pacing. Methods: Nine beagle dogs were divided into three groups: the model group (rapid atrial pacing/LAA resection), the positive control group (rapid atrial pacing/LAA preservation), and the negative control group (sinus rhythm). Twelve weeks later, the atrial tissues were resected for proteomics study. Parallel Reaction Monitoring (PRM) was used for the validation of the targeted proteomics. Results: 55 proteins were up regulated and 68 proteins were down regulated in the experimental vs. the positive control group. Proteins related to glucose and lipid metabolism were mainly down regulated, and mitochondria- related proteins were mainly down regulated during rapid atrial pacing compared with sinus rhythm. After resection of the LAA, glucose-metabolism-related proteins showed a significant up regulation trend, lipid metabolism-related proteins were further down regulated, whereas mitochondria-related proteins were up regulated compared with rapid atrial pacing with LAA preservation. PRM confirmed the reliability of the proteomics results. Conclusion: In the setting of AF, the resection of the LAA had a relatively large effect on the energy metabolism structure by affecting the quantity and functions of mitochondria.
Cancer is a genetic disorder involving in dynamic changes in the genome leading to uncontrolled growth, ability to invade and metastasize
Background: An “organism tree” of insects, the largest and most species-diverse group of all living animals, can be considered as a metaphorical and conceptual tree to capture a simplified narrative of the complex and unpredictable evolutionary courses of the extant insects. Currently, the most common approach has been to construct a “gene tree”, as a surrogate for the organism tree, by selecting a group of highly alignable regions of each of the select genes/proteins to represent each organism. However, such selected regions account for a small fraction of all genes/ proteins and even smaller fraction of whole genome of an organism. During last decades, whole-genome sequences of many extant insects became available, providing an opportunity to construct a “whole-genome or whole-proteome tree” of insects using Information Theory without sequence alignment (alignment-free method). Results: A whole-proteome tree of the insects shows that (a) the demographic grouping-pattern is similar to those in the gene trees, but there are notable differences in the branching orders of the groups, thus, the sisterhood relationships between pairs of the groups; and (b) all the founders of the major groups have emerged in an “explosive burst” near the root of the tree. Conclusion: Since the whole-proteome sequence of an organism can be considered as a “book” of amino-acid alphabets, a tree of the books can be constructed, without alignment of sequences, using a text analysis method of Information Theory. Such tree provides an alternative view-point of constructing a narrative of evolution and kinship among the extant insects.
Swarm is a group of particles or animals from our surroundings. Swarm Intelligence (SI) is used to solve a complex, real-life problem in optimized ways. Understanding biological relation with technology, biological process modeling using tools and techniques and transforming model into technology transfer initiative are the steps involved. Conventional Swarm Intelligence Algorithms are optimized using cloud computing technologies. Each process uses infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) as needed. The algorithms are extended for swarm Optimization, Page ranking in google search, Very Large Scale Integrated (VLSI) circuits, and wireless Sensor Network Optimization.
In biomedical science, system biology is an approach to understanding the greater picture by bringing its parts together, whether at the level of the organism, tissue, or cell. It is in stark contrast to the reductionist biology of decades, which requires separating the pieces. In order to analyze biological data, bioinformatics and systems biology use computer methods. ... System biology is a field of study that focuses on understanding whole biological processes, such as protein complexes, metabolic pathways, or gene regulation networks, in comparison to the previous emphasis on single genes or proteins. Computational biology is an interdisciplinary field in which computational methods are created and applied in order to analyze large biological data sets, such as genetic sequences, cell populations or protein samples, to make new predictions or to discover new biology.
Couple infertility is one of the major public health problems nowadays. Genetic etiologies are rarely discussed in our country, because of the predominance of infectious causes. Here we report a case of translocation t (2; 5) (q37.3;14 q35.3) explaining infertility in a 50-year-old man with a spermogram showing astheno teratozoospermia and normal phenotypic examination.
Introduction: Insomnia, one of the most common mental disorders, not only affects the quality of life, but also damages physical and mental health. Therefore, it is very necessary to explore the molecular mechanism of insomnia and find some suitable treatments. At present, methods of using drugs to treat insomnia are not satisfactory due to lack of evidences and side effects. Hence, development of non-drug treatments is particularly important. Tuina manipulations, a Chinese massage method, has achieved certain therapeutic effects on injuries, rheumatism, neurological diseases and other types of diseases. We have treated patient with insomnia by Tuina manipulations, and obtained therapeutic effects indeed. Methods: In the current study, assessments were performed using the Pittsburgh Sleep Quality Index (PSQI) and the insomnia severity index (ISI). iTRAQ (isobaric Tags for Relative and Absolute Quantitation) quantitative proteomics was used to analyze plasma samples taken from the Healthy Control (HC) group, insomnia patients group (before Tuina treatment, BTT) and insomnia-therapy group (after Tuina treatment, ATT) to identify the molecular correlation of insomnia. Results: The results showed that the PSQI score and ISI score of the ATT group were significantly lower than those of BTT, and the difference was statistically significant. In addition, the proteomics results show that in BTT vs. HC, the expression of many immune-related and stress-related proteins is out of control, the expression of many immune-related and stress-related proteins were out of control, and it revealed that Tuina manipulations had the capacities to regulate expression of immune-related and stress-related proteins in ATT vs. BTT, suggesting that Tuina manipulations may improve insomnia by regulating immune-related and stress-related proteins. The proteomics verification results had been verified by commercial ELISA (Enzyme Linked Immunosorbent Assay. Conclusion: All in all, our study not only found a good way to treat insomnia, but also provided a research foundation for improving insomnia.
