C2H2-zinc-finger transcription factors bind RNA and function in diverse post-transcriptional regulatory processes.

Cys2-His2 zinc-finger proteins (C2H2-ZNFs) constitute the largest class of DNA-binding transcription factors (TFs) yet remain largely uncharacterized. Although certain family members, e.g., GTF3A, have been shown to bind both DNA and RNA, the extent to which C2H2-ZNFs interact with-and regulate-RNA-associated processes is not known. Using UV crosslinking and immunoprecipitation (CLIP), we observe that 148 of 150 analyzed C2H2-ZNFs bind directly to RNA in human cells. By integrating CLIP sequencing (CLIP-seq) RNA-binding maps for 50 of these C2H2-ZNFs with data from chromatin immunoprecipitation sequencing (ChIP-seq), protein-protein interaction assays, and transcriptome profiling experiments, we observe that the RNA-binding profiles of C2H2-ZNFs are generally distinct from their DNA-binding preferences and that they regulate a variety of post-transcriptional processes, including pre-mRNA splicing, cleavage and polyadenylation, and m6A modification of mRNA. Our results thus define a substantially expanded repertoire of C2H2-ZNFs that bind RNA and provide an important resource for elucidating post-transcriptional regulatory programs.

A central chaperone-like role for 14-3-3 proteins in human cells.

14-3-3 proteins are highly conserved regulatory proteins that interact with hundreds of structurally diverse clients and act as central hubs of signaling networks. However, how 14-3-3 paralogs differ in specificity and how they regulate client protein function are not known for most clients. Here, we map the interactomes of all human 14-3-3 paralogs and systematically characterize the effect of disrupting these interactions on client localization. The loss of 14-3-3 binding leads to the coalescence of a large fraction of clients into discrete foci in a client-specific manner, suggesting a central chaperone-like function for 14-3-3 proteins. Congruently, the engraftment of 14-3-3 binding motifs to nonclients can suppress their aggregation or phase separation. Finally, we show that 14-3-3s negatively regulate the localization of the RNA-binding protein SAMD4A to cytoplasmic granules and inhibit its activity as a translational repressor. Our work suggests that 14-3-3s have a more prominent role as chaperone-like molecules than previously thought.

Regulation of alternative polyadenylation by the C2H2-zinc-finger protein Sp1.

Alternative polyadenylation (APA) enhances gene regulatory potential by increasing the diversity of mRNA transcripts. 3' UTR shortening through APA correlates with enhanced cellular proliferation and is a widespread phenomenon in tumor cells. Here, we show that the ubiquitously expressed transcription factor Sp1 binds RNA in vivo and is a common repressor of distal poly(A) site usage. RNA sequencing identified 2,344 genes (36% of the total mapped mRNA transcripts) with lengthened 3' UTRs upon Sp1 depletion. Sp1 preferentially binds the 3' UTRs of such lengthened transcripts and inhibits cleavage at distal sites by interacting with the subunits of the core cleavage and polyadenylation (CPA) machinery. The 3' UTR lengths of Sp1 target genes in breast cancer patient RNA-seq data correlate with Sp1 expression levels, implicating Sp1-mediated APA regulation in modulating tumorigenic properties. Taken together, our findings provide insights into the mechanism for dynamic APA regulation by unraveling a previously unknown function of the DNA-binding transcription factor Sp1.

Rad5 Recruits Error-Prone DNA Polymerases for Mutagenic Repair of ssDNA Gaps on Undamaged Templates.

Post-replication repair (PRR) allows tolerance of chemical- and UV-induced DNA base lesions in both an error-free and an error-prone manner. In classical PRR, PCNA monoubiquitination recruits translesion synthesis (TLS) DNA polymerases that can replicate through lesions. We find that PRR responds to DNA replication stress that does not cause base lesions. Rad5 forms nuclear foci during normal S phase and after exposure to types of replication stress where DNA base lesions are likely absent. Rad5 binds to the sites of stressed DNA replication forks, where it recruits TLS polymerases to repair single-stranded DNA (ssDNA) gaps, preventing mitotic defects and chromosome breaks. In contrast to the prevailing view of PRR, our data indicate that Rad5 promotes both mutagenic and error-free repair of undamaged ssDNA that arises during physiological and exogenous replication stress.

Modeling single cell trajectory using forward-backward stochastic differential equations.

Recent advances in single-cell sequencing technology have provided opportunities for mathematical modeling of dynamic developmental processes at the single-cell level, such as inferring developmental trajectories. Optimal transport has emerged as a promising theoretical framework for this task by computing pairings between cells from different time points. However, optimal transport methods have limitations in capturing nonlinear trajectories, as they are static and can only infer linear paths between endpoints. In contrast, stochastic differential equations (SDEs) offer a dynamic and flexible approach that can model non-linear trajectories, including the shape of the path. Nevertheless, existing SDE methods often rely on numerical approximations that can lead to inaccurate inferences, deviating from true trajectories. To address this challenge, we propose a novel approach combining forward-backward stochastic differential equations (FBSDE) with a refined approximation procedure. Our FBSDE model integrates the forward and backward movements of two SDEs in time, aiming to capture the underlying dynamics of single-cell developmental trajectories. Through comprehensive benchmarking on multiple scRNA-seq datasets, we demonstrate the superior performance of FBSDE compared to other methods, highlighting its efficacy in accurately inferring developmental trajectories.

RNALigands: a database and web server for RNA-ligand interactions.

RNA molecules can fold into complex and stable 3D structures, allowing them to carry out important genetic, structural, and regulatory roles inside the cell. These complex structures often contain 3D pockets made up of secondary structural motifs that can be potentially targeted by small molecule ligands. Indeed, many RNA structures in PDB contain bound small molecules, and high-throughput experimental studies have generated a large number of interacting RNA and ligand pairs. There is considerable interest in developing small molecule lead compounds targeting viral RNAs or those RNAs implicated in neurological diseases or cancer. We hypothesize that RNAs that have similar secondary structural motifs may bind to similar small molecule ligands. Toward this goal, we established a database collecting RNA secondary structural motifs and bound small molecule ligands. We further developed a computational pipeline, which takes as input an RNA sequence, predicts its secondary structure, extracts structural motifs, and searches the database for similar secondary structure motifs and interacting small molecule. We demonstrated the utility of the server by querying α-synuclein mRNA 5' UTR sequence and finding potential matches which were validated as correct. The server is publicly available at http://RNALigands.ccbr.utoronto.ca The source code can also be downloaded at https://github.com/SaisaiSun/RNALigands.

Health Impacts of Fine Particulate Matter Shift Due to Urbanization in China.

Rapid urbanization and industrialization have resulted in diverse anthropogenic activities and emissions between urban and non-urban regions, leading to varying levels of exposure to air pollutants and associated health risks. However, endeavors to mitigate air pollution and health benefits have displayed considerable heterogeneity across different regions. Therefore, comprehending the changes in air pollutant concentrations and health impacts within an urbanization context is imperative for promoting environmental equity. This paper uses gross domestic product (GDP)- and population-weighted methods to distinguish anthropogenic emissions from urban and non-urban areas in China and quantified their contributions to fine particulate matter (PM2.5) using the Community Multiscale Air Quality (CMAQ) model in 2010 and 2019. Anthropogenic emissions from urban and non-urban (outside urban) regions decreased by 26 and 44% from 2010 to 2019, respectively, resulting in 31 and 28% reductions of PM2.5 in China. PM2.5-related premature mortality attributed to non-urban and urban anthropogenic emission decreases by 8%. Non-urban anthropogenic activities are the main contributor to PM2.5 (56% in 2010 and 2019) and its associated premature mortality (59%), which also predominantly affects non-urban premature mortality (37-42% in 2010-2019). Population changes increase the proportion of premature mortality in urban populations (7-19%) from 2010 to 2019. This study emphasizes the shift of affected populations due to urbanization and population changes.

An Effective and Promising Strategy for Plant Protection: Synthesis of L-Carvone-Based Thiazolinone-Hydrazone/Nanochitosan Complexes with Antifungal Activity and Sustained Releasing Performance.

The development of novel natural product-derived nano-pesticide systems with loading capacity and sustained releasing performance of bioactive compounds is considered an effective and promising plant protection strategy. In this work, 25 L-carvone-based thiazolinone-hydrazone compounds 4a~4y were synthesized by the multi-step modification of L-carvone and structurally confirmed. Compound 4h was found to show favorable and broad-spectrum antifungal activity through the in vitro antifungal activity evaluation of compounds 4a~4y against eight phytopathogenic fungi. Thus, it could serve as a leading compound for new antifungal agents in agriculture. Moreover, the L-carvone-based nanochitosan carrier 7 bearing the 1,3,4-thiadiazole-amide group was rationally designed for the loading and sustained releasing applications of compound 4h, synthesized, and characterized. It was proven that carrier 7 had good thermal stability below 200 °C, dispersed well in the aqueous phase to form numerous nanoparticles with a size of~20 nm, and exhibited an unconsolidated and multi-aperture micro-structure. Finally, L-carvone-based thiazolinone-hydrazone/nanochitosan complexes were fabricated and investigated for their sustained releasing behaviors. Among them, complex 7/4h-2 with a well-distributed, compact, and columnar micro-structure displayed the highest encapsulation efficiency and desirable sustained releasing property for compound 4h and thus showed great potential as an antifungal nano-pesticide for further studies.

ProTICS reveals prognostic impact of tumor infiltrating immune cells in different molecular subtypes.

Different subtypes of the same cancer often show distinct genomic signatures and require targeted treatments. The differences at the cellular and molecular levels of tumor microenvironment in different cancer subtypes have significant effects on tumor pathogenesis and prognostic outcomes. Although there have been significant researches on the prognostic association of tumor infiltrating lymphocytes in selected histological subtypes, few investigations have systemically reported the prognostic impacts of immune cells in molecular subtypes, as quantified by machine learning approaches on multi-omics datasets. This paper describes a new computational framework, ProTICS, to quantify the differences in the proportion of immune cells in tumor microenvironment and estimate their prognostic effects in different subtypes. First, we stratified patients into molecular subtypes based on gene expression and methylation profiles by applying nonnegative tensor factorization technique. Then we quantified the proportion of cell types in each specimen using an mRNA-based deconvolution method. For tumors in each subtype, we estimated the prognostic effects of immune cell types by applying Cox proportional hazard regression. At the molecular level, we also predicted the prognosis of signature genes for each subtype. Finally, we benchmarked the performance of ProTICS on three TCGA datasets and another independent METABRIC dataset. ProTICS successfully stratified tumors into different molecular subtypes manifested by distinct overall survival. Furthermore, the different immune cell types showed distinct prognostic patterns with respect to molecular subtypes. This study provides new insights into the prognostic association between immune cells and molecular subtypes, showing the utility of immune cells as potential prognostic markers. Availability: R code is available at https://github.com/liu-shuhui/ProTICS.

Clonal hematopoiesis in the donor does not adversely affect long-term outcomes following allogeneic hematopoietic stem cell transplantation: result from a 13-year follow-up.

Donor clonal hematopoiesis may be transferred to the recipient through allogeneic hematopoietic stem cell transplantation (HSCT), but the potential for adverse long-term impact on transplant outcomes remains unknown. A total of 744 samples from 372 recipients who received HSCT and the corresponding donors were included. Bar-coded error-corrected sequencing using a modified molecular inversion probe capture protocol was performed, which targeted 33 genes covering mutations involved in clonal hematopoiesis with indeterminate potential (CHIP) and other acute myeloid leukemia-related mutations. A total of 30 mutations were detected from 25 donors (6.7%): the most frequently mutated gene was TET2 (n=7, 28%), followed by DNMT3A (n=4, 16%), SMC3 (n=3, 12%) and SF3B1 (n=3, 12%). With a median follow-up duration of 13 years among survivors, the presence of CHIP in the donor was not associated with recipient overall survival (P=0.969), relapse incidence (P=0.600) or non-relapse mortality (P=0.570). Donor CHIP did not impair neutrophil (P=0.460) or platelet (P=0.250) engraftment, the rates of acute (P=0.490), or chronic graft-versus-host disease (P=0.220). No significant difference was noted for secondary malignancy following HSCT between the two groups. The present study suggests that the presence of CHIP in allogeneic stem donors does not adversely affect transplant outcomes after HSCT. Accordingly, further study is warranted to reach a clearer conclusion on whether molecular profiling to determine the presence of CHIP mutations is necessary for the pretransplant evaluation of donors prior to stem cell donation.

Inferring RNA-binding protein target preferences using adversarial domain adaptation.

Precise identification of target sites of RNA-binding proteins (RBP) is important to understand their biochemical and cellular functions. A large amount of experimental data is generated by in vivo and in vitro approaches. The binding preferences determined from these platforms share similar patterns but there are discernable differences between these datasets. Computational methods trained on one dataset do not always work well on another dataset. To address this problem which resembles the classic "domain shift" in deep learning, we adopted the adversarial domain adaptation (ADDA) technique and developed a framework (RBP-ADDA) that can extract RBP binding preferences from an integration of in vivo and vitro datasets. Compared with conventional methods, ADDA has the advantage of working with two input datasets, as it trains the initial neural network for each dataset individually, projects the two datasets onto a feature space, and uses an adversarial framework to derive an optimal network that achieves an optimal discriminative predictive power. In the first step, for each RBP, we include only the in vitro data to pre-train a source network and a task predictor. Next, for the same RBP, we initiate the target network by using the source network and use adversarial domain adaptation to update the target network using both in vitro and in vivo data. These two steps help leverage the in vitro data to improve the prediction on in vivo data, which is typically challenging with a lower signal-to-noise ratio. Finally, to further take the advantage of the fused source and target data, we fine-tune the task predictor using both data. We showed that RBP-ADDA achieved better performance in modeling in vivo RBP binding data than other existing methods as judged by Pearson correlations. It also improved predictive performance on in vitro datasets. We further applied augmentation operations on RBPs with less in vivo data to expand the input data and showed that it can improve prediction performances. Lastly, we explored the predictive interpretability of RBP-ADDA, where we quantified the contribution of the input features by Integrated Gradients and identified nucleotide positions that are important for RBP recognition.

RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites.

RNA molecules can adopt stable secondary and tertiary structures, which are essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via coarse-grained molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28B. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs.

Significant Reductions in Secondary Aerosols after the Three-Year Action Plan in Beijing Summer.

Air quality in China has continuously improved during the Three-Year Action Plan (2018-2020); however, the changes in aerosol composition, properties, and sources in Beijing summer remain poorly understood. Here, we conducted real-time measurements of aerosol composition in five summers from 2018 to 2022 along with WRF-Community Multiscale Air Quality simulations to characterize the changes in aerosol chemistry and the roles of meteorology and emission reductions. Largely different from winter, secondary inorganic aerosol and photochemical-related secondary organic aerosol (SOA) showed significant decreases by 55-67% in summer, and the most decreases occurred in 2021. Comparatively, the decreases in the primary aerosol species and gaseous precursors were comparably small. While decreased atmospheric oxidation capacity as indicated by ozone changes played an important role in changing SOA composition, the large decrease in aerosol liquid water and small increase in particle acidity were critical for nitrate changes by decreasing gas-particle partitioning substantially (∼28%). Analysis of meteorological influences demonstrated clear and similar transitions in aerosol composition and formation mechanisms at a relative humidity of 50-60% in five summers. Model simulations revealed that emission controls played the decisive role in reducing sulfate, primary OA, and anthropogenic SOA during the Three-Year Action Plan, while meteorology affected more nitrate and biogenic SOA.

Functional characterization of RebL1 highlights the evolutionary conservation of oncogenic activities of the RBBP4/7 orthologue in Tetrahymena thermophila.

Retinoblastoma-binding proteins 4 and 7 (RBBP4 and RBBP7) are two highly homologous human histone chaperones. They function in epigenetic regulation as subunits of multiple chromatin-related complexes and have been implicated in numerous cancers. Due to their overlapping functions, our understanding of RBBP4 and 7, particularly outside of Opisthokonts, has remained limited. Here, we report that in the ciliate protozoan Tetrahymena thermophila a single orthologue of human RBBP4 and 7 proteins, RebL1, physically interacts with histone H4 and functions in multiple epigenetic regulatory pathways. Functional proteomics identified conserved functional links for Tetrahymena RebL1 protein as well as human RBBP4 and 7. We found that putative subunits of multiple chromatin-related complexes including CAF1, Hat1, Rpd3, and MuvB, co-purified with RebL1 during Tetrahymena growth and conjugation. Iterative proteomics analyses revealed that the cell cycle regulatory MuvB-complex in Tetrahymena is composed of at least five subunits including evolutionarily conserved Lin54, Lin9 and RebL1 proteins. Genome-wide analyses indicated that RebL1 and Lin54 (Anqa1) bind within genic and intergenic regions. Moreover, Anqa1 targets primarily promoter regions suggesting a role for Tetrahymena MuvB in transcription regulation. RebL1 depletion inhibited cellular growth and reduced the expression levels of Anqa1 and Lin9. Consistent with observations in glioblastoma tumors, RebL1 depletion suppressed DNA repair protein Rad51 in Tetrahymena, thus underscoring the evolutionarily conserved functions of RBBP4/7 proteins. Our results suggest the essentiality of RebL1 functions in multiple epigenetic regulatory complexes in which it impacts transcription regulation and cellular viability.

Synthesis, Antifungal Activity, and Molecular Simulation Study of L-Carvone-Derived 1,3,4-Oxadiazole-Thioether Compounds.

To discover potent antifungal molecules with new and distinctive structures, 20 novel L-carvone-derived 1,3,4-oxadiazole-thioether compounds 5 a-5 t were synthesized through multi-step reaction of L-carvone, and their structures were confirmed by FT-IR, 1 H-NMR, 13 C-NMR, and HR-MS. The antifungal activities of compounds 5 a-5 t were preliminarily tested by in vitro method, and the results indicated that all of the title compounds displayed certain antifungal activities against the eight tested plant fungi, especially for P. piricola. Among them, compound 5 i (R=p-F) with the most significant antifungal activity deserved further study for discovering and developing novel natural product-based antifungal agents. Moreover, two molecular simulation technologies were employed for the investigation of their structure-activity relationships (SARs). Firstly, a reasonable and effective 3D-QSAR model was established by the comparative molecular field (CoMFA) method, and the relationship of the substituents linked with the benzene rings and the inhibitory activities of the title compounds against P. piricola was elucidated. Then, the binding mode of compound 5 i (R=p-F) and its potential biological target (CYP51) was simulated by molecular docking, and it was found that compound 5 i could readily bind with CYP51 in the active site, and the ligand-receptor interactions involved three hydrogen bonds and several hydrophobic effects.

Channel Modeling and Characteristics Analysis under Different 3D Dynamic Trajectories for UAV-Assisted Emergency Communications.

This study involved channel modeling and characteristics analysis of unmanned aerial vehicles (UAVs) according to different operating trajectories. Based on the idea of standardized channel modeling, air-to-ground (AG) channel modeling of a UAV was carried out, taking into consideration that both the receiver (Rx) and the transmitter (Tx) ran along different types of trajectories. In addition, based on Markov chains and a smooth-turn (ST) mobility model, the influences of different operation trajectories on typical channel characteristics-including time-variant power delay profile (PDP), stationary interval, temporal autocorrelation function (ACF), root mean square (RMS) delay spread (DS), and spatial cross-correlation function (CCF)-were studied. The multi-mobility multi-trajectory UAV channel model matched well with actual operation scenarios, and the characteristics of the UAV AG channel could be analyzed more accurately, thus providing a reference for future system design and sensor network deployment of sixth-generation (6G) UAV-assisted emergency communications.

Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios.

Regarding the new demands and challenges of sixth-generation (6G) mobile communications, wireless networks are undergoing a significant shift from traditional terrestrial networks to space-air-ground-sea-integrated networks. Unmanned aerial vehicle (UAV) communications in complicated mountainous scenarios are typical applications and have practical implications, especially in emergency communications. In this paper, the ray-tracing (RT) method was applied to reconstruct the propagation scenario and then acquire the wireless channel data. Channel measurements are also conducted in real mountainous scenarios for verification. By setting different flight positions, trajectories, and altitudes, channel data in the millimeter wave (mmWave) band was obtained. Important statistical properties, such as the power delay profile (PDP), Rician K-factor, path loss (PL), root mean square (RMS) delay spread (DS), RMS angular spreads (ASs), and channel capacity were compared and analyzed. The effects of different frequency bands on channel characteristics at 3.5 GHz, 4.9 GHz, 28 GHz, and 38 GHz bands in mountainous scenarios were considered. Furthermore, the effects of extreme weather, especially different precipitation, on the channel characteristics were analyzed. The related results can provide fundamental support for the design and performance evaluation of future 6G UAV-assisted sensor networks in complicated mountainous scenarios.

Studying Fluorescence Sensing of Acetone and Tryptophan and Antibacterial Properties Based on Zinc-Based Triple Interpenetrating Metal-Organic Skeletons.

Two triple interpenetrating Zn(II)-based MOFs were studied in this paper. Named [Zn6(1,4-bpeb)4(IPA)6(H2O)]n (MOF-1) and {[Zn3(1,4-bpeb)1.5(DDBA)3]n·2DMF} (MOF-2), {1,4-bpeb = 1,4-bis [2-(4-pyridy1) ethenyl]benze, IPA = Isophthalic acid, DDBA = 3,3'-Azodibenzoic acid}, they were synthesized by the hydrothermal method and were characterized and stability tested. The results showed that MOF-1 had good acid-base stability and solvent stability. Furthermore, MOF-1 had excellent green fluorescence and with different phenomena in different solvents, which was almost completely quenched in acetone. Based on this phenomenon, an acetone sensing test was carried out, where the detection limit of acetone was calculated to be 0.00365% (volume ratio). Excitingly, the MOF-1 could also be used as a proportional fluorescent probe to specifically detect tryptophan, with a calculated detection limit of 34.84 µM. Furthermore, the mechanism was explained through energy transfer and competitive absorption (fluorescence resonance energy transfer (FRET)) and internal filtration effect (IFE). For antibacterial purposes, the minimum inhibitory concentrations of MOF-1 against Escherichia coli and Staphylococcus aureus were 19.52 µg/mL and 39.06 µg/mL, respectively, and the minimum inhibitory concentrations of MOF-2 against Escherichia coli and Staphylococcus aureus were 68.36 µg/mL and 136.72 µg/mL, respectively.

[Tonglong Kaibi Prescription for the treatment of severe benign prostate hyperplasia: A clinical study].

OBJECTIVE: To evaluate the clinical effect of the traditional Chinese medicine (TCM) Tonglong Kaibi Prescription (TKP) in the treatment of severe BPH with kidney deficiency and blood stasis combined with damp heat syndrome. METHODS: We randomly divided 120 cases of severe BPH with kidney deficiency and blood stasis combined with damp heat syndrome into three groups of equal number, treated with TKP, doxazosin mesylate sustained-release tablets (the DM control), and TKP + DM, all for 8 weeks. We obtained the IPSS, TCM symptoms scores, quality of life (QOL) scores, maximum urinary flow rate (Qmax) and postvoid residual urine volume (PVR) from the patients before and after treatment and compared them among the three groups. RESULTS: After 8 weeks of treatment, the effectiveness rate was significantly higher in the TKP + DM than in the DM control group (P < 0.05). The IPSS, TCM symptoms scores, QOL scores and PVR decreased (P < 0.01), while the Qmax increased dramatically (P < 0.01) in all the three groups. Pairwise comparison showed that the IPSS and QOL scores were lower in the TKP + DM than in the TKP and DM control groups (P < 0.05 or 0.01), and so were the TCM syndrome scores in the TKP + DM and TKP groups than in the DM control (P < 0.01). There were no statistically significant differences in PVR and Qmax among the three groups after treatment (P> 0.05), and no serious adverse events during the treatment. CONCLUSION: TKP is safe and effective in the treatment of severe BPH, which can improve the TCM symptoms, reduce the IPSS, QOL scores and PVR and increase the Qmax of the patients. TKP is evidently superior to DM alone in improving TCM symptoms of BPH and combined medication of TKP and DM produces even better clinical efficacy.

Long Noncoding RNAs and Repetitive Elements: Junk or Intimate Evolutionary Partners?

Our recent ability to sequence entire genomes, along with all of their transcribed RNAs, has led to the surprising finding that only ∼1% of the human genome is used to encode proteins. This finding has led to vigorous debate over the functional importance of the transcribed but untranslated portions of the genome. Currently, scientists tend to assume coding genes are functional until proven not to be, while the opposite is true for noncoding genes. This review takes a new look at the evidence for and against widespread noncoding gene functionality. We focus in particular on long noncoding RNA (noncoding RNAs longer than 200 nucleotides) genes and their 'junk' associates, transposable elements, and satellite repeats. Taken together, the suggestion put forward is that more of this junk DNA may be functional than nonfunctional and that noncoding RNAs and transposable elements act symbiotically to drive evolution.