A Social Referral Mechanism for Job Reference Recommendation

Recently, with the popularity of various social media, this new trend of information technologies has impacted our lives, redefined the way we interact with each other, and facilitated the communication and influence cross different social groups, such as enhancing the power of social search and appraisal. _x000D_ In this research, we mainly focus on this mystery process of information exchanges existing long ago on the base of sociology and apply this power in the field of job seeking. Considering the factors of both willingness and influence, we generate the list of proper reference candidates to desired job for job seekers to provide more job-related information or to be referrals. Integrating the knowledge of human resources management, we implement this social referral application with the support of information technologies and strive to enrich the service of social media, turning the passively searching for job seeking to actively consulting for exclusively job information._x000D

Clonal dissemination of invasive and colonizing clonal complex 1 of serotype VI group B Streptococcus in central Taiwan

Background/PurposeThe aim of this study was to investigate clinical presentation, serotype distribution and genetic correlation of group B streptococcus (GBS) diseases. Since serotype VI prevalence far exceeded that reported in prior studies, genetic relationship of isolates was further analyzed.MethodsGBS isolates obtaining from patients with invasive diseases and pregnant women with colonization between June 2007 and December 2010 were analyzed. All isolates were tested for serotypes by multiplex PCR assay and pulsed-field gel electrophoresis (PFGE). Serotype VI isolates were further analyzed by multilocus sequence typing (MLST).ResultsA total of 134 GBS isolates were recovered from blood of 126 patients with invasive disease (94.0%) and anogenital swabs of 8 pregnant women (6.0%). Most common serotype was Ib (21.6%), followed by V (20.1%), VI (18.7%), III (15.7%), II (11.9 %), Ia (11.2%), and IX (0.7%). Serotype VI was also the leading type in infants with early onset disease (EOD; 3/8, 37.5%) and colonizing pregnant women (3/8, 37.5%). PFGE distinguished 33 pulsotypes, reflecting genetic diversity among GBS isolates. Among 25 serotype VI isolates tested, 14 were ST-1, seven were ST-679, three were ST-678, one was ST-681, and distributed into four PFGE pulsotypes. ST-678, ST-679, and ST-681 were novel sequence types; ST-678 and ST-679 are single-locus variants of ST-1 that belongs to clonal complex (CC) 1.ConclusionCC1 dissemination of serotype VI GBS thus emerges as an important invasive pathogen in infants and nonpregnant adults in central Taiwan. Serotype prevalence of GBS must be continuously monitored geographically to guide prevention strategy of GBS vaccines

Nonapnea Sleep Disorders and the Risk of Acute Kidney Injury: A Nationwide Population-Based Study

Abstract Nonapnea sleep disorders (NASDs) and associated problems, which are highly prevalent in patients with kidney diseases, are associated with unfavorable medical sequelae. Nonetheless, whether NASDs are associated with acute kidney injury (AKI) development has not been thoroughly analyzed. We examined the association between NASD and AKI. We conducted a population-based study by using 1,000,000 representative data from the Taiwan National Health Insurance Research Database for the period from January 1, 2000, to December 31, 2010. We studied the incidence and risk of AKI in 9178 newly diagnosed NASD patients compared with 27,534 people without NASD matched according to age, sex, index year, urbanization level, region of residence, and monthly income at a 1:3 ratio. The NASD cohort had an adjusted hazard ratio (hazard ratio [HR]; 95% confidence interval [CI] = 1.15–2.63) of subsequent AKI 1.74-fold higher than that of the control cohort. Older age and type 2 diabetes mellitus were significantly associated with an increased risk of AKI (P < 0.05). Among different types of NASDs, patients with insomnia had a 120% increased risk of developing AKI (95% CI = 1.38–3.51; P = 0.001), whereas patients with other sleep disorders had a 127% increased risk of subsequent AKI (95% CI = 1.07–4.80; P = 0.033). Men with NASDs were at a high risk of AKI (P < 0.05). This nationwide population-based cohort study provides evidence that patients with NASDs are at higher risk of developing AKI than people without NASDs

Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P &lt; 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI

Impact of Ancestral Differences and Reassessment of the Classification of Previously Reported Pathogenic Variants in Patients With Brugada Syndrome in the Genomic Era: A SADS-TW BrS Registry

Brugada syndrome (BrS) is a heritable disease that results in sudden cardiac death. In the exome/genomic era, certain reported pathogenic variants in some genetic diseases have been reclassified as benign owing to their high frequency in some ancestries. In the present study, we comprehensively reassessed all previously reported pathogenic variants of BrS. We collected all pathogenic variants of BrS reported in the Human Gene Mutation Database and ClinVar throughout April 2017. We compared the minor allele frequency (MAF) of each variant among different ancestries by searching public whole-genome and exome databases. After considering the maximum credible allele frequency, variants with a MAF ≥ 0.001 were considered to be of questionable pathogenicity. We also investigated the percentage of SCN5A variants with a MAF ≥ 0.001 in 124 BrS patients from the Han Chinese population. We collected a total of 440 BrS variants, of which 18 had a MAF ≥ 0.001. There was a greater percentage of non-SCN5A variants with a MAF ≥ 0.001 than of SCN5A variants (21.8 versus 1.6%, p &lt; 0.0001). There were fewer frameshift and nonsense mutations than missense mutations (0.9 versus 5.6%, p = 0.032). Of the 18 variants, 14 (77.8%) were present only in the reference Asian population. In our cohort, we identified two SCN5A variants (p.A226V and p.V1340I) with MAFs ≥ 0.001 (0.45%). In conclusion, ancestral differences are important when considering the pathogenicity of BrS variants, especially in the case of missense variants and non-SCN5A variants, which may be pathogenic in some ancestries but only disease-predisposing in others

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Secretome-Based Identification of ULBP2 as a Novel Serum Marker for Pancreatic Cancer Detection

BACKGROUND: To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues. METHODS: ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9). RESULTS: Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls. CONCLUSIONS: Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July