Construction of immune-related LncRNAs classifier to predict prognosis and immunotherapy response in thymic epithelial tumors

The primary objective of this study was to construct an immune-related long noncoding RNAs (IRLs) classifier to precisely predict the prognosis and immunotherapy response of patients with thymic epithelial tumors (TET). Based on univariable Cox regression analysis and Lasso regression, six prognosis-related IRLs (AC004466.3, {"type":"entrez-nucleotide","attrs":{"text":"AC138207.2","term_id":"29165571","term_text":"AC138207.2"}}AC138207.2, {"type":"entrez-nucleotide","attrs":{"text":"AC148477.2","term_id":"45504179","term_text":"AC148477.2"}}AC148477.2, {"type":"entrez-nucleotide","attrs":{"text":"AL450270.1","term_id":"11244554","term_text":"AL450270.1"}}AL450270.1, HOXB-AS1 and SNHG8) were selected to build an IRL classifier. Importantly, results of qRT-PCR validated that higher expression levels of {"type":"entrez-nucleotide","attrs":{"text":"AC138207.2","term_id":"29165571","term_text":"AC138207.2"}}AC138207.2, {"type":"entrez-nucleotide","attrs":{"text":"AC148477.2","term_id":"45504179","term_text":"AC148477.2"}}AC148477.2, {"type":"entrez-nucleotide","attrs":{"text":"AL450270.1","term_id":"11244554","term_text":"AL450270.1"}}AL450270.1 and SNHG8 as well as lower expression levels of AC004466.3, and HOXB-AS1 in TETs samples compared with normal controls. The IRL classifier could effectively classify patients into the low-risk and high-risk groups based on the different survival parameters. In terms of predictive ability and clinical utility, the IRL classifier was superior to Masaoka staging system. Additionally, IRL classifier is significantly associated with immune cells infiltration (dendritic cells, activated CD4 memory T cells and tumor-infiltrating lymphocyte (TIL), T cell subsets in particular), immune microenvironment (immune score and immune checkpoint inhibitors) and immunogenicity (TMB) in TETs, which hints that IRL classifier is tightly correlated with immune characteristics and might guide more effective immunotherapy strategies for TETs patients. Encouragingly, according to TIDE algorithm, there were more immunotherapy responders in the low-risk IRL subgroup and the IRL score was robustly negatively linked to the immunotherapeutic response. To sum up, the IRL classifier was established, which can be used to predict the prognosis, immune infiltration status, immunotherapy response in TETs patients, and may facilitate personalized counseling for immunotherapy.     

LncRNAs Expression in Preeclampsia Placenta Reveals the Potential Role of LncRNAs Contributing to Preeclampsia Pathogenesis

Background

Long non-coding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of diseases. In this study, we aimed to investigate the lncRNA profiles in preeclampsia. Preeclampsia has been observed in patients with molar pregnancy where a fetus is absent, which demonstrate that the placenta is sufficient to cause this condition. Thus, we analyzed the lncRNA profiles in preeclampsia placentas.

Methodology/Principal Findings

In this study, we described the lncRNA profiles in six preeclampsia placentas (T) and five normal pregnancy placentas (N) using microarray. With abundant and varied probes accounting for 33,045 LncRNAs in our microarray, 28,443 lncRNAs that were expressed at a specific level were detected. From the data, we found 738 lncRNAs that were differentially expressed (≥1.5-fold-change) among preeclampsia placentas compared with controls. Coding-non-coding gene co-expression networks (CNC network) were constructed based on the correlation analysis between the differentially expressed lncRNAs and mRNAs. According to the CNC network and GO analysis of differentially expressed lncRNAs/mRNAs, we selected three lncRNAs to analyze the relationship between lncRNAs and preeclampsia. LOC391533, LOC284100, and CEACAMP8 were evaluated using qPCR in 40 preeclampsia placentas and 40 controls. These results revealed that three lncRNAs were aberrantly expressed in preeclampsia placentas compared with controls.

Conclusions/Significance

Our study is the first study to determine the genome-wide lncRNAs expression patterns in preeclampsia placenta using microarray. These results revealed that clusters of lncRNAs were aberrantly expressed in preeclampsia placenta compared with controls, which indicated that lncRNAs differentially expressed in preeclampsia placenta might play a partial or key role in preeclampsia development. Misregulation of LOC391533, LOC284100, and CEACAMP8 might contribute to the mechanism underlying preeclampsia. Taken together, this study may provide potential targets for the future treatment of preeclampsia and novel insights into preeclampsia biology.     

A test of the use of NDVI data to predict secondary productivity

Question: How well does the use of NDVI predict secondary productivity at landscape scales? What is the influence of vegetation quality and phenology over secondary productivity? Location: Magellanic steppe in Tierra del Fuego, Argentina. (52°45’to 54° S, 68°15’to 67°30’W). Methods: Monthly and yearly integrated NDVI (NDVI‐I) were calculated from AVHRR/NOAA 14, as estimators of phenology and aerial net primary productivity respectively. From a vegetation map we obtained the proportional cover of different physiognomic types and calculated the palatable fraction (forage) productivity that were used as estimators of vegetation quality. Data were analysed through correlations and regressions. Results: NDVI‐I was not related with secondary productivity indices, while December and annual maximum NDVI, proportion of lawns and tussock grasslands and forage productivity were positively related with secondary productivity. A negative relationship was found between the proportion of heathlands and secondary productivity, but a positive relationship between heathland's proportion and NDVI‐I was found. Conclusions: NDVI‐I is not a good predictor of secondary productivity at the scale of our study. These results could be due to: (1) NDVI‐I is not related to primary productivity and (2) primary productivity is not related to secondary productivity.     

Rhesus macaques use probabilities to predict future events

Humans can use an intuitive sense of statistics to make predictions about uncertain future events, a cognitive skill that underpins logical and mathematical reasoning. Recent research shows that some of these abilities for statistical inferences can emerge in preverbal infants and non-human primates such as apes and capuchins. An important question is therefore whether animals share the full complement of intuitive reasoning abilities demonstrated by humans, as well as what evolutionary contexts promote the emergence of such skills. Here, we examined whether free-ranging rhesus macaques (Macaca mulatta) can use probability information to infer the most likely outcome of a random lottery, in the first test of whether primates can make such inferences in the absence of direct prior experience. We developed a novel expectancy-violation looking time task, adapted from prior studies of infants, in order to assess the monkeys' expectations. In Study 1, we confirmed that monkeys (n = 20) looked similarly at different sampled items if they had no prior knowledge about the population they were drawn from. In Study 2, monkeys (n = 80) saw a dynamic ‘lottery’ machine containing a mix of two types of fruit outcomes, and then saw either the more common fruit (expected trial) or the relatively rare fruit (unexpected trial) fall from the machine. We found that monkeys looked longer when they witnessed the unexpected outcome. In Study 3, we confirmed that this effect depended on the causal relationship between the sample and the population, not visual mismatch: monkeys (n = 80) looked equally at both outcomes if the experimenter pulled the sampled item from her pocket. These results reveal that rhesus monkeys spontaneously use information about probability to reason about likely outcomes, and show how comparative studies of nonhumans can disentangle the evolutionary history of logical reasoning capacities.     

LncRNAs: the missing link to senescence nuclear architecture

During cellular senescence and organismal aging, cells display various molecular and morphological changes. Although many aging-related long noncoding RNAs (lncRNAs) are highly associated with senescence-associated secretory phenotype, the roles of lncRNAs in senescence-associated nuclear architecture and morphological changes are just starting to emerge. Here I review lncRNAs associated with nuclear structure establishment and maintenance, their aging-related changes, and then focus on the pervasive, yet underappreciated, role of RNA double-strand DNA triplexes for lncRNAs to recognize targeted genomic regions, making lncRNAs the nexus between DNA and proteins to regulate nuclear structural changes. Finally, I discuss the future of deciphering direct links of lncRNA changes to various nuclear morphology changes assisted by artificial intelligence and genetic perturbations.     

长链非编码RNA在脂质代谢中的作用

脂质代谢是人体三大代谢之一，在激素等信号分子的调控下，脂质代谢处于稳定平衡的状态。当稳态被打破，血液中甘油三酯（triglyceride，TG）、胆固醇等水平发生变化，最终引起动脉粥样硬化（atherosclerosis，AS）、肥胖等脂质代谢疾病。长链非编码RNA（long noncoding RNA，lncRNA）是一组不具备蛋白质编码能力，长度大于200个核苷酸的RNA，近来研究发现，lncRNA与机体代谢、炎症和免疫系统以及血管功能的调控密切相关。大量文献表明，lncRNA参与脂质代谢调控，因而有望成为一些脂质代谢疾病的潜在治疗靶点。     

A simple topographical model to predict Golden Eagle Aquila chrysaetos space use during dispersal

Many large raptors exploit or rely on anabatic and orographic winds which provide vertical lift, to supplement or provide the energy fuelling flight. Airspace is therefore a critical habitat for such large raptors and its use is subject to the underlying terrestrial topography, because particular topographical features are more likely to provide wind-energetic lift. Accordingly, ridges and/or ‘rugged topography’ are common preferred features in habitat use by large raptors. Our study aimed to provide a simple model of space use for a large raptor, the Golden Eagle Aquila chrysaetos, based on thousands of GPS telemetry records during juvenile dispersal of 92 birds tagged as nestlings between 2007 and 2016 across upland Scotland. Model development was based on the hypothesis that four topographical variables would be influential: slope, aspect, altitude and distance from ridge. The telemetry dataset was divided into training and two testing components. The first testing set was derived by a temporal split resulting in approximately equal sample size on records and some temporal overlap in individuals’ records with training data. The second testing set involved no individuals from the training set. Aspect was removed early in training model development because it was not influential. The model found that young Golden Eagles preferred, or used according to availability, space above slopes greater than 10°, at an altitude of ≥ 300 m, and within 300 m of a ridge. The test data were highly correlated with those from the training data in the model variables, and performance as regard to expected preferences from the model was improved in both test datasets, indicating the model was robust. Given the apparent universal nature of large raptor dependence on topography, that topography is relatively immutable according to time and use, and that topographical data are readily available, we commend our approach to other habitat preference studies of Golden Eagles and other large raptors elsewhere.     

ESEfinder: A web resource to identify exonic splicing enhancers

Point mutations frequently cause genetic diseases by disrupting the correct pattern of pre-mRNA splicing. The effect of a point mutation within a coding sequence is traditionally attributed to the deduced change in the corresponding amino acid. However, some point mutations can have much more severe effects on the structure of the encoded protein, for example when they inactivate an exonic splicing enhancer (ESE), thereby resulting in exon skipping. ESEs also appear to be especially important in exons that normally undergo alternative splicing. Different classes of ESE consensus motifs have been described, but they are not always easily identified. ESEfinder (http://exon.cshl.edu/ESE/) is a web-based resource that facilitates rapid analysis of exon sequences to identify putative ESEs responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.     

The use of absorption enhancers to enhance the dispersibility of spray-dried powders for pulmonary gene therapy

BACKGROUND: Pulmonary gene therapy requires aerosolisation of the gene vectors to the target region of the lower respiratory tract. Pulmonary absorption enhancers have been shown to improve the penetration of pharmaceutically active ingredients in the airway. In this study, we investigate whether certain absorption enhancers may also enhance the aerosolisation properties of spray-dried powders containing non-viral gene vectors. METHODS: Spray-drying was used to prepare potentially respirable trehalose-based dry powders containing lipid-polycation-pDNA (LPD) vectors and absorption enhancers. Powder morphology and particle size were characterised using scanning electron microscopy and laser diffraction, respectively, with gel electrophoresis used to assess the structural integrity of the pDNA. The biological functionality of the powders was quantified using in vitro cell (A549) transfection. Aerosolisation from a Spinhaler dry powder inhaler into a multistage liquid impinger (MSLI) was used to assess the in vitro dispersibility and deposition of the powders. RESULTS: Spray-dried powder containing dimethyl-beta-cyclodextrin (DMC) demonstrated substantially altered particle morphology and an optimal particle size distribution for pulmonary delivery. The inclusion of DMC did not adversely affect the structural integrity of the LPD complex and the powder displayed significantly greater transfection efficiency as compared to unmodified powder. All absorption enhancers proffered enhanced powder deposition characteristics, with the DMC-modified powder facilitating high deposition in the lower stages of the MSLI. CONCLUSIONS: Incorporation of absorption enhancers into non-viral gene therapy formulations prior to spray-drying can significantly enhance the aerosolisation properties of the resultant powder and increase biological functionality at the site of deposition in an in vitro model.     

A systematic approach to identify functional motifs within vertebrate developmental enhancers

Uncovering the cis-regulatory logic of developmental enhancers is critical to understanding the role of non-coding DNA in development. However, it is cumbersome to identify functional motifs within enhancers, and thus few vertebrate enhancers have their core functional motifs revealed. Here we report a combined experimental and computational approach for discovering regulatory motifs in developmental enhancers. Making use of the zebrafish gene expression database, we computationally identified conserved non-coding elements (CNEs) likely to have a desired tissue-specificity based on the expression of nearby genes. Through a high throughput and robust enhancer assay, we tested the activity of ∼ 100 such CNEs and efficiently uncovered developmental enhancers with desired spatial and temporal expression patterns in the zebrafish brain. Application of de novo motif prediction algorithms on a group of forebrain enhancers identified five top-ranked motifs, all of which were experimentally validated as critical for forebrain enhancer activity. These results demonstrate a systematic approach to discover important regulatory motifs in vertebrate developmental enhancers. Moreover, this dataset provides a useful resource for further dissection of vertebrate brain development and function.     

The use of magnetic resonance imaging to predict ACL graft structural properties

Magnetic resonance imaging (MRI) could potentially be used to non-invasively predict the strength of an ACL graft after ACL reconstruction. We hypothesized that the volume and T2 relaxation parameters of the ACL graft measured with MRI will predict the graft structural properties and anteroposterior (AP) laxity of the reconstructed knee. Nine goats underwent ACL reconstruction using a patellar tendon autograft augmented with a collagen or collagen-platelet composite. After 6 weeks of healing, the animals were euthanized, and the reconstructed knees were retrieved and imaged on a 3T scanner. AP laxity was measured prior to dissecting out the femur-graft-tibia constructs which were then tested to tensile failure to determine the structural properties. Regression analysis indicated a statistically significant relationship between the graft volume and the failure load (r(2)=0.502; p=0.049). When graft volume was normalized to the T2 relaxation time, the relationship was even greater (r(2)=0.687; p=0.011). There was a significant correlation between the graft volume and the linear stiffness (r(2)=0.847; p<0.001), which remained significant with T2 normalization (r(2)=0.764; p=0.002). For AP laxity at 30° flexion, there was not a significant correlation with graft volume, but there was a significant correlation with volume normalized by the T2 relaxation time (r(2)=0.512; p=0.046). These results suggest that MRI volumetric measures combined with graft T2 properties may be useful in predicting the structural properties of ACL grafts.     

The use of Artemia biomass sampling to predict cyst yields in culture ponds

The possibility of using biomass volume (= mean biomass present in the pond.week ^–1) to predict the total amount of harvestable cysts (= kg wet weight collected. week ^–1) produced in a culture pond by an Artemia franciscana population using a mixed model regression was evaluated for two different sampling methods; horizontal transects and vertical point samples. For transects, the following equation was found: `log (0.01 + cyst yields) = –2.05 + 0.025<sup>*</sup>(biomass volume)' with F <sub>(1, 4.87)</sub> = 8.83 and p = 0.032. For the point samples, the regression was also significant with F <sub>(1, 55.2)</sub> = 13.62 and p = 0.0005 for following equation: `log (0.01 + cyst yield) = –3.613 + 0.021^*(biomass volume). As pond effect and interaction terms did not significantly explain a significant portion of the variance for either of the sampling methods (Transects: pond: F _{(3, 14.3)} = 2.48; p = 0.103; pond^*biomass volume: F _{(3, 3.61)} = 4.63; p = 0.0976; Point samples: pond: F _{(3, 44.5)} = 0.00; p = 0.999; pond^*biomass volume: F _{(3, 44.2)} = 0.11; p = 0.954 ), the variable pond (repeated measurement factor) was not included in the final calculations for the regression equations. Although a combination of factors influences the equation, the high significance levels of the regression indicate biomass volume can be safely used to predict production trends. The low investment requirements of this method make it especially attractive for on farm use, where correctly determining the point of cyst decline will help farmers to allocate resources where needed.     

LncRNAs as potential diagnostic and prognostic biomarkers in gastric cancer: A novel approach to personalized medicine

Gastric cancer is the third leading cause of cancer death with 5-year survival rate of about 30–35%. Since early detection is associated with decreased mortality, identification of novel biomarkers for early diagnosis and proper management of patients with the best response to therapy is urgently needed. Long noncoding RNAs (lncRNAs) due to their high specificity, easy accessibility in a noninvasive manner, as well as their aberrant expression under different pathological and physiological conditions, have received a great attention as potential diagnostic, prognostic, or predictive biomarkers. They may also serve as targets for treating gastric cancer. In this review, we highlighted the role of lncRNAs as tumor suppressors or oncogenes that make them potential biomarkers for the diagnosis and prognosis of gastric cancer. Relatively, lncRNAs such as H19, HOTAIR, UCA1, PVT1, tissue differentiation-inducing nonprotein coding, and LINC00152 could be potential diagnostic and prognostic markers in patients with gastric cancer. Also, the impact of lncRNAs such as ecCEBPA, MLK7-AS1, TUG1, HOXA11-AS, GAPLINC, LEIGC, multidrug resistance-related and upregulated lncRNA, PVT1 on gastric cancer epigenetic and drug resistance as well as their potential as therapeutic targets for personalized medicine was discussed.     

CancerEnD: A database of cancer associated enhancers

CancerEnD is an integrated resource developed for annotating 8524 unique expressed enhancers, associated genes, somatic mutations and copy number variations of 8063 cancer samples from 18 cancer types of TCGA. Somatic mutation data was taken from the COSMIC repository. To delineate the relationship of change in copy number of enhancer elements with the prognosis of cancer patients, survival analysis was done using the survival package in R. We identified 1762 overall survival associated enhancers, which can be used for prognostic purposes of cancer patients in a tissue-specific manner.CancerEnD (https://webs.iiitd.edu.in/raghava/cancerend/) is developed on a user-friendly responsive template, that enables searching, browsing and downloading of the annotated enhancer elements in terms of gene expression, copy number variation and survival association.We hope it provides a promising avenue for researchers to facilitate the understanding of enhancer deregulation in tumorigenesis, and to identify new biomarkers for therapy and disease-diagnosis.     

Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows

This study investigates the feasibility to predict individual methane (CH₄) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH₄ emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH₄ emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH₄ daily emissions ranged from 10.2 to 47.1 g CH₄/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH₄ data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH₄ measurement. The equations were built using Partial Least Squares regression. From the calculated R²_cv, it appears that the accuracy of CH₄ prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH₄ emissions gave the best results. The R² and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH₄/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH₄ emission at day 1.5. The lower R² (R² = 0.76) obtained between FA profile and CH₄ emission compared with the one corresponding to the obtained calibration (R²_c = 0.87) shows the interest to apply directly the developed CH₄ equation instead of the use of correlations between FA and CH₄. In conclusion, our preliminary results suggest the feasibility of direct CH₄ prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH₄ emissions at farm level or at the regional scale and it also could be used to identify low-CH₄-emitting cows.