The Role of Long Noncoding RNA SChLAP1 in Prostate Cancer

Prostate cancer is the most common malignancy in U.S. men, accounting for nearly 30,000 deaths annually. While the majority of prostate cancers are indolent, a subset of patients has aggressive disease. However, the molecular basis for this clinical heterogeneity remains incompletely understood. Long noncoding RNAs (lncRNAs) are an emerging class of regulatory molecules implicated in a diverse range of human malignancies. Here, SChLAP1 is identified as a novel, highly prognostic lncRNA that is expressed in 15-30% of prostate cancers. Functionally, SChLAP1 coordinates cancer cell invasion in vitro and metastatic spread in vivo. Mechanistically, SChLAP1 interacts with and antagonizes the tumor-suppressive SWI/SNF nucleosome-remodeling complex. While deleterious SWI/SNF mutations occur in 20% of all cancers, they are relatively rare in prostate cancer. Within prostate cancer, SWI/SNF mutations are associated with low SChLAP1 expression, suggesting that high SChLAP1 expression may represent a mutation-independent modality of SWI/SNF inhibition. Employing a previously described antagonistic model between SWI/SNF and Polycomb Repressive Complex 2 (PRC2), SChLAP1 is found to enhance PRC2 function in prostate cancer. Additionally, SChLAP1-expressing cells are more sensitive to pharmacologic EZH2 inhibition. Further characterization of SChLAP1 reveals a 250bp region near the 3’-end that mediates its invasive phenotype and coordinates its interaction with SWI/SNF. Additionally, SChLAP1 interacts with BRG1-containing but not BRM-containing SWI/SNF complexes, and knockdown of BRM in SChLAP1-expressing cells exposes a synthetic lethal vulnerability in prostate cancer. Finally, the largest biomarker discovery project to date in prostate cancer identifies SChLAP1 as one of the best genes for predicting metastatic progression. Characterization of SChLAP1 expression by in situ hybridization shows that SChLAP1 expression is enriched in metastatic samples. Additionally, SChLAP1 can be detected in patient urine samples and may be useful as a non-invasive biomarker. Lastly, targeting SChLAP1 with antisense oligonucleotides (ASO) suggests that directly targeting SChLAP1 may be an effective therapeutic strategy in prostate cancer. Taken together, this work defines an essential role for SChLAP1 in aggressive prostate cancer, uncovers novel aspects of lncRNA biology, and has broad implications for cancer biology.PHDMolecular & Cellular Path PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137075/1/asahu_1.pd

Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation

Purpose: Segmentation of surgical instruments in endoscopic videos is essential for automated surgical scene understanding and process modeling. However, relying on fully supervised deep learning for this task is challenging because manual annotation occupies valuable time of the clinical experts. Methods: We introduce a teacher-student learning approach that learns jointly from annotated simulation data and unlabeled real data to tackle the erroneous learning problem of the current consistency-based unsupervised domain adaptation framework. Results: Empirical results on three datasets highlight the effectiveness of the proposed framework over current approaches for the endoscopic instrument segmentation task. Additionally, we provide analysis of major factors affecting the performance on all datasets to highlight the strengths and failure modes of our approach. Conclusion: We show that our proposed approach can successfully exploit the unlabeled real endoscopic video frames and improve generalization performance over pure simulation-based training and the previous state-of-the-art. This takes us one step closer to effective segmentation of surgical tools in the annotation scarce setting.Comment: Accepted at IPCAI202

Thyroid dysfunction in metabolic syndrome: the ensuing storm

Background: Metabolic syndrome was initially defined as a constellation of hypertension, hyperglycemia, android obesity and gout. Thyroid dysfunction is characterized by altered thyroid stimulating hormone levels with normal or altered thyroid hormone levels. The aim of the study was to observe thyroid hormone levels and thyroid stimulating hormone levels in a cohort of patients with established metabolic syndrome and to report significant variations if any.Methods: 54 established cases of metabolic syndrome satisfying the IDF criteria were included in the study along with 54 ages and sex matched healthy controls.Results: Amongst the controls 92.6% were euthyroid, 5.6% were hypothyroid, 1.9% were subclinical hypothyroid. Among cases 64.8% were euthyroid. Thyroid dysfunction was found to be prevalent among 35.2% metabolic syndrome patients.Conclusions: Present study clearly reveals a higher incidence of thyroid dysfunction in metabolic syndrome. Metabolic syndrome and thyroid dysfunction are both considered as independent risk factors for cardiovascular disease. Therefore presence of both these entities in an individual increases the risk of a cardiovascular compromise. Hence assessment of thyroid function in metabolic syndrome might serve as a risk assesment tool to identify individuals predisposed to cardiovascular disease early, thereby resulting in a timely intervention.

Live visualizations of single isolated tubulin protein self-assembly via tunneling current: effect of electromagnetic pumping during spontaneous growth of microtubule

As we bring tubulin protein molecules one by one into the vicinity, they self-assemble and entire event we capture live via quantum tunneling. We observe how these molecules form a linear chain and then chains self-assemble into 2D sheet, an essential for microtubule, —fundamental nano-tube in a cellular life form. Even without using GTP, or any chemical reaction, but applying particular ac signal using specially designed antenna around atomic sharp tip we could carry out the self-assembly, however, if there is no electromagnetic pumping, no self-assembly is observed. In order to verify this atomic scale observation, we have built an artificial cell-like environment with nano-scale engineering and repeated spontaneous growth of tubulin protein to its complex with and without electromagnetic signal. We used 64 combinations of plant, animal and fungi tubulins and several doping molecules used as drug, and repeatedly observed that the long reported common frequency region where protein folds mechanically and its structures vibrate electromagnetically. Under pumping, the growth process exhibits a unique organized behavior unprecedented otherwise. Thus, “common frequency point” is proposed as a tool to regulate protein complex related diseases in the future.Japan. Ministry of Education, Culture, Sports, Science and Technology.Asian Office of Aerospace Research and Development (AOARD) (FA2386-11-1-0001AOARD104173)Asian Office of Aerospace Research and Development (AOARD) (FA2386-10-1-4059 AOARD-10-4059

Atomic water channel controlling remarkable properties of a single brain microtubule: Correlating single protein to its supramolecular assembly

Microtubule nanotubesarefoundineverylivingeukaryoticcells;theseareformedbyreversible polymerizationofthetubulinprotein,andtheirhollow fibersare filledwithuniquelyarrangedwater molecules.Herewemeasuresingletubulinmoleculeandsinglebrain-neuronextractedmicrotubule nanowirewithandwithoutwaterchannelinsidetounraveltheiruniqueelectronicandopticalproperties for the firsttime.Wedemonstratethattheenergylevelsofasingletubulinproteinandsinglemicrotubule madeof40,000tubulindimersareidenticalunlikeconventionalmaterials.Moreover,thetransmittedac powerandthetransient fluorescencedecay(singlephotoncount)areindependentofthemicrotubule length.Evenmoreremarkableisthefactthatthemicrotubulenanowireismoreconductingthanasingle proteinmoleculethatconstitutesthenanowire.Microtubule's vibrationalpeakscondensetoasinglemode thatcontrolstheemergenceofsizeindependentelectronic/opticalproperties,andautomatednoise alleviation,whichdisappearwhentheatomicwatercoreisreleasedfromtheinnercylinder.Wehave carriedoutseveraltrickystate-of-the-artexperimentsandidentified theelectromagneticresonancepeaksof singlemicrotubulereliably.Theresonantvibrationsestablishedthatthecondensationofenergylevelsand periodicoscillationofuniqueenergyfringesonthemicrotubulesurface,emergeastheatomicwatercore resonantlyintegratesallproteinsarounditsuchthatthenanotubeirrespectiveofitssizefunctionslikea singleproteinmolecule.Thus,amonomolecularwaterchannelresidinginsidetheprotein-cylinderdisplays an unprecedentedcontrolingoverningthetantalizingelectronicandopticalpropertiesofmicrotubule

A novel RNA in situ hybridization assay for the long noncoding RNA SChLAP1 predicts poor clinical outcome after radical prostatectomy in clinically localized prostate cancer.

Long noncoding RNAs (lncRNAs) are an emerging class of oncogenic molecules implicated in a diverse range of human malignancies. We recently identified SChLAP1 as a novel lncRNA that demonstrates outlier expression in a subset of prostate cancers, promotes tumor cell invasion and metastasis, and associates with lethal disease. Based on these findings, we sought to develop an RNA in situ hybridization (ISH) assay for SChLAP1 to 1) investigate the spectrum of SChLAP1 expression from benign prostatic tissue to metastatic castration-resistant prostate cancer and 2) to determine whether SChLAP1 expression by ISH is associated with outcome after radical prostatectomy in patients with clinically localized disease. The results from our current study demonstrate that SChLAP1 expression increases with prostate cancer progression, and high SChLAP1 expression by ISH is associated with poor outcome after radical prostatectomy in patients with clinically localized prostate cancer by both univariate (hazard ratio = 2.343, P = .005) and multivariate (hazard ratio = 1.99, P = .032) Cox regression analyses. This study highlights a potential clinical utility for SChLAP1 ISH as a novel tissue-based biomarker assay for outcome prognostication after radical prostatectomy

Conventional and new-breeding technologies for improving disease resistance in lentil (Lens culinaris Medik)

Lentil, an important cool season food legume, is a rich source of easily digestible protein, folic acid, bio-available iron, and zinc nutrients. Lentil grows mainly as a sole crop in the winter after harvesting rice in South Asia. However, the annual productivity is low due to its slow growth during the early phase, competitive weed infestation, and disease outbreaks during the crop growth period. Disease resistance breeding has been practiced for a long time to enhance resistance to various diseases. Often the sources of resistance are available in wild crop relatives. Thus, wide hybridization and the ovule rescue technique have helped to introgress the resistance trait into cultivated lentils. Besides hybridization, induced mutagenesis contributed immensely in creating variability for disease tolerance, and several disease-resistant mutant lines have been developed. However, to overcome the limitations of traditional breeding approaches, advancement in molecular marker technologies, and genomics has helped to develop disease-resistant and climate-resilient lentil varieties with more precision and efficiency. This review describes types of diseases, disease screening methods, the role of conventional and new breeding technologies in alleviating disease-incurred damage and progress toward making lentil varieties more resilient to disease outbreaks under the shadow of climate change

Massively parallel computing on an organic molecular layer

Current computers operate at enormous speeds of ~10^13 bits/s, but their principle of sequential logic operation has remained unchanged since the 1950s. Though our brain is much slower on a per-neuron base (~10^3 firings/s), it is capable of remarkable decision-making based on the collective operations of millions of neurons at a time in ever-evolving neural circuitry. Here we use molecular switches to build an assembly where each molecule communicates-like neurons-with many neighbors simultaneously. The assembly's ability to reconfigure itself spontaneously for a new problem allows us to realize conventional computing constructs like logic gates and Voronoi decompositions, as well as to reproduce two natural phenomena: heat diffusion and the mutation of normal cells to cancer cells. This is a shift from the current static computing paradigm of serial bit-processing to a regime in which a large number of bits are processed in parallel in dynamically changing hardware.Comment: 25 pages, 6 figure