Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

<p>Abstract</p> <p>Background</p> <p>Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome.</p> <p>Methods</p> <p>We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays.</p> <p>Results</p> <p>Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%.</p> <p>We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the <it>SLC45A3-ELK4 </it>e4-e2 TIC to <it>ERG</it>-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines.</p> <p>Conclusions</p> <p>Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as <it>MSMB-NCOA4</it>, may play functional roles in cancer.</p

Using gaming with audio-visual cues and SEMG/EEG data as biofeedback for rehabilitation and accelerated learning

212 p.Currently there are various approaches for stroke rehabilitation. Although various parameters can be measured using robotics technologies and other tools, there are few which provide biofeedback for eliminating compensatory muscle use. while at the same time providing a platform of therapy where supervision is minimised. Both these aspects are crucial in the emerging scenario of high levels of residual disability in chronic phase of stroke and a rapidly decreasing therapist-patient ratio in clinics around the world, and particularly in Singapore.Master of Science (Biomedical Engineering

Growth Factor Inhibiting PKC Sensor in E-coli Environment Using Classification Technique and ANN Method

Protein kinease C plays an important role in angiogenesis and apoptosis in cancer. During the phase of angiogenesis the growth factor is up regulated where as during apoptosis the growth factor is down regulated. For down regulation of growth factor the pH environment of intra-cellular fluid has a specific range in the alkaline medium. Protein kinease C along with E-coli through interaction of Selenometabolite is able to maintain that alkaline environment for the apoptosis of the cancer cell with inhibition of the growth factor related to antioxidant/oxidant ratio. The present paper through implementation of Artificial Neural Network and Decision Tree has focused on metastasis linked with Capacitance Relaxation phenomena and down regulation of growth factor (VGEF). In this paper a distributed neural network has been applied to a data mining problem for classification of cancer stages inorder to have proper diagnosis of patient with PKC sensor. The Network was trained off line using 270 patterns each of 6 inputs. Using the weight obtained during training, fresh patterns were tested for accuracy in diagnosis linked with the stages of cancer

Anti-depressant-like activity of a novel serotonin type-3 (5-HT₃) receptor antagonist in rodent models of depression

619-626N-Cyclohexyl-3-methoxyquinoxalin-2-carboxamide (QCM-13), a novel 5-HT3 antagonist identified from a series of compounds with higher pA2 (7.6) and good log P (2.91) value was screened in rodent models of depression such as forced swim test (FST), tail suspension test (TST), interaction studies with standard anti-depressants and confirmatory studies such as reversal of parthenolide induced depression and reserpine induced hypothermia. In FST (2 and 4 mg/kg) and TST (2 and 4 mg/kg), QCM-13 significantly reduced the duration of immobility in mice without affecting the base line locomotion. QCM-13 (2 and 4 mg/kg) was also found to have significant interaction with standard anti-depressants (fluoxetine and bupropion in FST and TST respectively). Further, reversal of parthenolide induced depression in mice and reserpine induced hypothermia in rat models indicate the serotonergic influence of QCM-13 for anti-depressant potential

Evaluation of SYBR green I based visual loop-mediated isothermal amplification (LAMP) assay for genus and species-specific diagnosis of malaria in P. vivax and P. falciparum endemic regions

Background & objectives: Loop-mediated isothermal amplification (LAMP) is an emerging nucleic acid based diagnostic approach that is easily adaptable to the field settings with limited technical resources. This study was aimed to evaluate the LAMP assay for the detection and identification of Plasmodium falciparum and P. vivax infection in malaria suspected cases using genus and species-specific assay. Methods: The 18S rRNA-based LAMP assay was evaluated for diagnosis of genus Plasmodium, and species-specific diagnosis of P. falciparum and P. vivax, infection employing 317 malaria suspected cases, and the results were compared with those obtained by 18S nested PCR (n-PCR). All the samples were confirmed by microscopy for the presence of Plasmodium parasite. Results: The n-PCR was positive in all Plasmodium-infected cases (n=257; P. falciparum=133; P. vivax=124) and negative in microscopy negative cases (n=58) except for two cases which were positive for P. vivax, giving a sensitivity of 100% (95% CI: 97.04-100%) and a specificity of 100% (95% CI: 88.45-99.5%). Genus-specific LAMP assay missed 11 (3.2%) microscopy and n-PCR confirmed vivax malaria cases. Considering PCR results as a reference, LAMP was 100% sensitive and specific for P. falciparum, whereas it exhibited 95.16% sensitivity and 96.7% specificity for P. vivax. The n-PCR assay detected 10 mixed infection cases while species-specific LAMP detected five mixed infection cases of P. vivax and P. falciparum, which were not detected by microscopy. Interpretation & conclusion: Genus-specific LAMP assay displayed low sensitivity. Falciparum specific LAMP assay displayed high sensitivity whereas vivax specific LAMP assay displayed low sensitivity. Failed detection of vivax cases otherwise confirmed by the n-PCR assay indicates exploitation of new targets and improved detection methods to attain 100% results for P. vivax detection

An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

Background: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]). Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable

Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19

Introduction: Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population. Methods: This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay. Results: Among patients with COVID-19 admitted to the intensive care unit, AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity. Conclusions: AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes