Combinatorial regulation of transcription factors and microRNAs

<p>Abstract</p> <p>Background</p> <p>Gene regulation is a key factor in gaining a full understanding of molecular biology. <it>Cis</it>-regulatory modules (CRMs), consisting of multiple transcription factor binding sites, have been confirmed as the main regulators in gene expression. In recent years, a novel regulator known as microRNA (miRNA) has been found to play an important role in gene regulation. Meanwhile, transcription factor and microRNA co-regulation has been widely identified. Thus, the relationships between CRMs and microRNAs have generated interest among biologists.</p> <p>Results</p> <p>We constructed new combinatorial regulatory modules based on CRMs and miRNAs. By analyzing their effect on gene expression profiles, we found that genes targeted by both CRMs and miRNAs express in a significantly similar way. Furthermore, we constructed a regulatory network composed of CRMs, miRNAs, and their target genes. Investigating its structure, we found that the feed forward loop is a significant network motif, which plays an important role in gene regulation. In addition, we further analyzed the effect of miRNAs in embryonic cells, and we found that mir-154, as well as some other miRNAs, have significant co-regulation effect with CRMs in embryonic development.</p> <p>Conclusions</p> <p>Based on the co-regulation of CRMs and miRNAs, we constructed a novel combinatorial regulatory network which was found to play an important role in gene regulation, particularly during embryonic development.</p

First in Man Studies of Pharmacokinetic Profiles of a Novel Oral PTH(1-34)

Background: PTH(1-34) (Teriparatide) is an anabolic agent used in treatment of osteoporosis. It promotes bone formation and reduces the risk of vertebral and some non-vertebral fractures. The route of administration by daily subcutaneous (sc) injection can cause problems in certain patients. A new oral delivery system for human PTH(1-34) has been developed as a possible treatment option. Galitzer et al. presented pre-clinical data (ASBMR 2012, MO0402) and first-in-human results (ASBMR 2013, FR0378) on safety, tolerability and absorption dynamics of oral PTH(1-34) in various dosages. We now describe the pharmacokinetics (PK) of oral PTH(1-34) compared to sc and placebo in healthy subjects. Objective: A single-center, double blinded, triple crossover study was designed to compare the 1.8 mg optimal dose of oral PTH(1-34) against standard dosage of teriparatide injection and oral placebo. Method: The study was conducted following and in accordance with the Hadassah Medical Center ethical approval committee. 12 healthy volunteers (6m/6f), 18-50y, received three treatments: single sc injection of 20µg FORTEO®, 1.8 mg oral PTH(1-34), or placebo. Blood samples were collected at time 0, 10, 15, 20, 30, 45, 60, 75, 90, 120, 180, 240, 300 minute post dose. Plasma concentration of PTH(1-34) (IDS, Tyne and Wear, UK) and cyclic adenosine 3’,5’monophosphate (cAMP) were measured on all samples. Results: All 12 subjects on oral PTH(1-34) showed rapid, post dose increase then decrease of PTH(1-34), from baseline mean (±SD) of 5.9 (1.8) pg/mL to peak mean of 185.3 (±128.8) pg/mL. PK profiles of oral PTH(1-34) showed Cmax (pg/mL), Tmax (mins), AUC0-last of 238.3 (110.8), 17.5 (5.4) and 6161.7 (2726.7), respectively; whereas sc showed mean Cmax (pg/mL), Tmax (mins), AUC0-last of 172.3 (55.7), 20.8 (8.7) and 13965.9 (2984.8), respectively. Plasma cAMP increased in all subjects in response to oral PTH(1-34) and sc treatment. Serum adjusted calcium in all subjects remained within normal limits throughout the studies. Conclusion: PK profiles showed a single oral dose of 1.8 mg PTH(1-34) is rapidly absorbed, and no significant difference in Cmax and Tmax when compared with 20µg of sc teriparatide. A significant difference in the rate of plasma clearance and AUC0-last value was observed (fig.1). These differing profiles and modality of administration of PTH(1-34) could offer unique advantages in the treatment of calcium and metabolic bone disorders

A possible pathway for rapid growth of sulfate during haze days in China

Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM[subscript 2. 5]) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM[subscript 2. 5], iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies

Mitigating NO_x emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei (BTH), China

Stringent mitigation measures have reduced wintertime PM_(2.5) concentrations by 42.2% from 2013 to 2018 in the BTH. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM_(2.5), although the surface-measured NO₂ level has decreased by over 20%. It still remains elusive about contributions of nitrogen oxides (NO_x) emissions mitigation to the nitrate and PM_(2.5) level. The WRF-Chem model simulations of a persistent haze episode in January 2019 in the BTH reveal that NO_x emissions mitigation does not help lower wintertime nitrate and PM_(2.5) concentrations under current conditions in the BTH, because the substantial O₃ increase induced by NO_x mitigation offsets the HNO₃ loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by occurrence of the severe PM pollution in the BTH during the COVID-19 outbreak with a significant reduction of NO₂

Mitigating NO_x emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei (BTH), China

Stringent mitigation measures have reduced wintertime PM_(2.5) concentrations by 42.2% from 2013 to 2018 in the BTH. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM_(2.5), although the surface-measured NO₂ level has decreased by over 20%. It still remains elusive about contributions of nitrogen oxides (NO_x) emissions mitigation to the nitrate and PM_(2.5) level. The WRF-Chem model simulations of a persistent haze episode in January 2019 in the BTH reveal that NO_x emissions mitigation does not help lower wintertime nitrate and PM_(2.5) concentrations under current conditions in the BTH, because the substantial O₃ increase induced by NO_x mitigation offsets the HNO₃ loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by occurrence of the severe PM pollution in the BTH during the COVID-19 outbreak with a significant reduction of NO₂

Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences

Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research

Prediction of Protein Functions from Protein-Protein Interaction Data Based on a New Measure of Network Betweenness

Assigning functions to proteins that have not been annotated is an important problem In the post-genomic era. Meanwhile, the availability of data on protein-protein interactions provides a new way to predict protein functions. Previously, several computational methods have been developed to solve this problem. Among them, Deng et al. developed a method based on the Markov random field (MRF). Lee et al. extended it to the kernel logistic regression model (KLR) based on the diffusion kernel. These two methods were tested on yeast benchmark data, and the results demonstrated that both MRF and KLR had high precision in function prediction. On that basis, inspired by the idea of a Markov cluster algorithm, we defined a new measure of network betweenness, and developed a betweenness-based logistic regression model (BLR). Applying it to predict protein functions on the yeast benchmark data, we found that BLR outperformed both the KLR and the MRF models. It is evidently that BLR is a more proper and efficient approach of function prediction. ? 2010 IEEE.EI

<p>Worsening summertime ozone pollution in the Guanzhong Basin, China from 2014 to 2018: Impacts of synoptic conditions and anthropogenic emissions</p>

The ozone (O-3) pollution in the Guanzhong Basin (GZB), China has progressively deteriorated from 2014 to 2018, with the summertime near-surface maximum daily 8 h average (MDA8) O-3 concentration ([O-3]) increasing from about 104 to 141 mu g m(-3), although the emission mitigation strategies have been carried out since 2013. However, it remains elusive about whether anthropogenic emissions or meteorological conditions contribute to the worsening of O-3 pollution in the GZB. A subjective classification method is first used to classify the synoptic patterns influencing the GZB into favorable and unfavorable conditions. The unfavorable synoptic conditions generally correspond to less precipitation, more solar radiation and higher near-surface temperature, which facilitate formation of the O-3 pollution, and it is opposite for the favorable conditions. The increasing trend of MDA8 [O-3] is correlated well with the increase in occurrence of unfavorable synoptic conditions and near-surface temperature from 2014 to 2018. Sensitivity experiments using the WRF-Chem model reveals that the emission mitigation strategies from 2014 to 2018 enhance MDA8 [O-3] by 19.2% on average in the GZB, which counts about 54% of the observed MDA8 O-3 increasing trend. Particularly, the particulate matter decrease due to the emission mitigation contributes about 11.5% of the observed trend, caused by the reduced HO2 heterogeneous uptake and enhanced photolysis. The rest 46% of the observed MDA8 O-3 increasing trend can be mainly contributed by the variation of occurrence days of unfavorable synoptic situations