A deep ATCA 20cm radio survey of the AKARI Deep Field South near the South Ecliptic Pole

The results of a deep 20 cm radio survey at 20 cm are reported of the AKARI Deep Field South (ADF-S) near the South Ecliptic Pole (SEP), using the Australia Telescope Compact Array telescope, ATCA. The survey has 1 sigma detection limits ranging from 18.7--50 microJy per beam over an area of ~1.1 sq degrees, and ~2.5 sq degrees to lower sensitivity. The observations, data reduction and source count analysis are presented, along with a description of the overall scientific objectives, and a catalogue containing 530 radio sources detected with a resolution of 6.2" x 4.9". The derived differential source counts show a pronounced excess of sources fainter than ~1 mJy, consistent with an emerging population of star forming galaxies. Cross-correlating the radio with AKARI sources and archival data we find 95 cross matches, with most galaxies having optical R-magnitudes in the range 18-24 mag, and 52 components lying within 1" of a radio position in at least one further catalogue (either IR or optical). We have reported redshifts for a sub-sample of our catalogue finding that they vary between galaxies in the local universe to those having redshifts of up to 0.825. Associating the radio sources with the Spitzer catalogue at 24 microns, we find 173 matches within one Spitzer pixel, of which a small sample of the identifications are clearly radio loud compared to the bulk of the galaxies. The radio luminosity plot and a colour-colour analysis suggest that the majority of the radio sources are in fact luminous star forming galaxies, rather than radio-loud AGN. There are additionally five cross matches between ASTE or BLAST submillimetre galaxies and radio sources from this survey, two of which are also detected at 90 microns, and 41 cross-matches with submillimetre sources detected in the Herschel HerMES survey Public Data release.Comment: MNRAS accepted and in press 9 July 2012: 28 pages, 15 Figures, 17 Table

Search for the Sagittarius Tidal Stream of Axion Dark Matter around 4.55 μ\mueV

We report the first search for the Sagittarius tidal stream of axion dark matter around 4.55 $\mu$eV using CAPP-12TB haloscope data acquired in March of 2022. Our result excluded the Sagittarius tidal stream of Dine-Fischler-Srednicki-Zhitnitskii and Kim-Shifman-Vainshtein-Zakharov axion dark matter densities of $\rho_a\gtrsim0.184$ and $\gtrsim0.025$ GeV/cm$^{3}$, respectively, over a mass range from 4.51 to 4.59 $\mu$eV at a 90% confidence level.Comment: 6 pages, 7 Figures, PRD Letter accepte

Clinical Significance of Thrombosis in an Intracardiac Blind Pouch After a Fontan Operation

The univentricular heart after the Fontan operation may have a blind pouch formed by the pulmonary stump or rudimentary ventricle according to the anatomy before surgery. Thrombosis in an intracardiac blind pouch of patients with a univentricular heart is a hazardous complication. Because only a few reports have described this complication, the authors evaluated the clinical significance of thrombosis in an intracardiac blind pouch of a univentricular heart. They performed a retrospective review of medical records from August 1986 to December 2007. Four patients were confirmed as having thrombosis in a pulmonary artery stump and one patient as having thrombosis in a rudimentary ventricle shown by cardiac computed tomography (CT). This represents 1.85% (5/271) of patients with ongoing regular follow-up evaluation after the Fontan operation. The median age at diagnosis was 14.2 years. Two of the five patients were taking aspirin and one patient was taking warfarin when they were identified for the development of thrombosis. None of the patients demonstrated thrombosis in the Fontan tract or venous side of the circulation. Brain magnetic resonance imaging (MRI) showed that three patients had cerebral infarction and one patient had suggestive old ischemia. Three patients with thrombus in the pulmonary stump underwent pulmonary artery stump thrombectomy and pulmonary valve obliteration. One patient with thrombus in the rudimentary ventricle underwent ventricular septal defect (VSD) closure with thrombectomy. Thrombus in a blind pouch could cause systemic thromboembolism despite little blood communication. Therefore, surgical modification of the pulmonary stump and VSD closure of the rudimentary ventricle are required to reduce the risk of later thrombus formation. Clinicians should not overlook the possibility of thrombus in a ligated pulmonary artery stump or a rudimentary ventricle after the Fontan operation, which may increase the risk of embolic stroke for patients with single-ventricle physiology

Extensive search for axion dark matter over 1\,GHz with CAPP's Main Axion eXperiment

We report an extensive high-sensitivity search for axion dark matter above 1\,GHz at the Center for Axion and Precision Physics Research (CAPP). The cavity resonant search, exploiting the coupling between axions and photons, explored the frequency (mass) range of 1.025\,GHz (4.24\,$\mu$eV) to 1.185\,GHz (4.91\,$\mu$eV). We have introduced a number of innovations in this field, demonstrating the practical approach of optimizing all the relevant parameters of axion haloscopes, extending presently available technology. The CAPP 12\,T magnet with an aperture of 320\,mm made of Nb$_3$Sn and NbTi superconductors surrounding a 37-liter ultralight-weight copper cavity is expected to convert DFSZ axions into approximately $10^2$ microwave photons per second. A powerful dilution refrigerator, capable of keeping the core system below 40\,mK, combined with quantum-noise limited readout electronics, achieved a total system noise of about 200\,mK or below, which corresponds to a background of roughly $4\times 10^3$ photons per second within the axion bandwidth. The combination of all those improvements provides unprecedented search performance, imposing the most stringent exclusion limits on axion--photon coupling in this frequency range to date. These results also suggest an experimental capability suitable for highly-sensitive searches for axion dark matter above 1\,GHz.Comment: A detailed axion dark matter article with 27 pages, 22 figure

Identification of differentially expressed genes using an annealing control primer system in stage III serous ovarian carcinoma

<p>Abstract</p> <p>Background</p> <p>Most patients with ovarian cancer are diagnosed with advanced stage disease (<it>i.e</it>., stage III-IV), which is associated with a poor prognosis. Differentially expressed genes (DEGs) in stage III serous ovarian carcinoma compared to normal tissue were screened by a new differential display method, the annealing control primer (ACP) system. The potential targets for markers that could be used for diagnosis and prognosis, for stage III serous ovarian cancer, were found by cluster and survival analysis.</p> <p>Methods</p> <p>The ACP-based reverse transcriptase polymerase chain reaction (RT PCR) technique was used to identify DEGs in patients with stage III serous ovarian carcinoma. The DEGs identified by the ACP system were confirmed by quantitative real-time PCR. Cluster analysis was performed on the basis of the expression profile produced by quantitative real-time PCR and survival analysis was carried out by the Kaplan-Meier method and Cox proportional hazards multivariate model; the results of gene expression were compared between chemo-resistant and chemo-sensitive groups.</p> <p>Results</p> <p>A total of 114 DEGs were identified by the ACP-based RT PCR technique among patients with stage III serous ovarian carcinoma. The DEGs associated with an apoptosis inhibitory process tended to be up-regulated clones while the DEGs associated with immune response tended to be down-regulated clones. Cluster analysis of the gene expression profile obtained by quantitative real-time PCR revealed two contrasting groups of DEGs. That is, a group of genes including: <it>SSBP1</it>, <it>IFI6 DDT</it>, <it>IFI27</it>, <it>C11orf92</it>, <it>NFKBIA</it>, <it>TNXB</it>, <it>NEAT1 </it>and <it>TFG </it>were up-regulated while another group of genes consisting of: <it>LAMB2</it>, <it>XRCC6</it>, <it>MEF2C</it>, <it>RBM5</it>, <it>FOXP1</it>, <it>NUDCP2</it>, <it>LGALS3</it>, <it>TMEM185A</it>, and <it>C1S </it>were down-regulated in most patients. Survival analysis revealed that the up-regulated genes such as <it>DDAH2, RNase K and TCEAL2 </it>might be associated with a poor prognosis. Furthermore, the prognosis of patients with chemo-resistance was predicted to be very poor when genes such as <it>RNase K, FOXP1</it>, <it>LAMB2 </it>and <it>MRVI1 </it>were up-regulated.</p> <p>Conclusion</p> <p>The DEGs in patients with stage III serous ovarian cancer were successfully and reliably identified by the ACP-based RT PCR technique. The DEGs identified in this study might help predict the prognosis of patients with stage III serous ovarian cancer as well as suggest targets for the development of new treatment regimens.</p

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fishers exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient usingin vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage (http://www.wang-lab-hkust.com:3838/TMZEP) Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs

Prediction of major depressive disorder following beta-blocker therapy in patients with cardiovascular diseases

Incident depression has been reported to be associated with poor prognosis in patients with cardiovascular disease (CVD), which might be associated with beta-blocker therapy. Because early detection and intervention can alleviate the severity of depression, we aimed to develop a machine learning (ML) model predicting the onset of major depressive disorder (MDD). A model based on L1 regularized logistic regression was trained against the South Korean nationwide administrative claims database to identify risk factors for the incident MDD after beta-blocker therapy in patients with CVD. We identified 50,397 patients initiating beta-blockers for CVD, with 774 patients developing MDD within 365 days after initiating beta-blocker therapy. An area under the receiver operating characteristic curve (AUC) of 0.74 was achieved. A history of non-selective beta-blockers and factors related to anxiety disorder, sleeping problems, and other chronic diseases were the most strong predictors. AUCs of 0.62–0.71 were achieved in the external validation conducted on six independent electronic health records and claims databases in the USA and South Korea. In conclusion, an ML model that identifies patients at high-risk for incident MDD was developed. Application of ML to identify susceptible patients for adverse events of treatment may serve as an important approach for personalized medicine

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher’s exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs

Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

Background Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and simultaneous activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step toward clinical application of patient-tailored treatment regimens. Results Toward this goal, we establish a library of 139 gynecologic tumors including epithelial ovarian cancers (EOCs), cervical, endometrial tumors, and uterine sarcomas that are genomically and/or pharmacologically annotated and explore dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discover lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identify TP53 mutation as a molecular determinant that elicits therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identify transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Conclusions Together, our results demonstrate the potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers

Prevalence and detection of low-allele-fraction variants in clinical cancer samples

Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay