Gender difference in symptomatic radiographic knee osteoarthritis in the Knee Clinical Assessment – CAS(K): A prospective study in the general population

<p>Abstract</p> <p>Background</p> <p>A recent study of adults aged ≥50 years reporting knee pain found an excess of radiographic knee osteoarthritis (knee ROA) in symptomatic males compared to females. This was independent of age, BMI and other clinical signs and symptoms. Since this finding contradicts many previous studies, our objective was to explore four possible explanations for this gender difference: X-ray views, selection, occupation and non-articular conditions.</p> <p>Methods</p> <p>A community-based prospective study. 819 adults aged ≥50 years reporting knee pain in the previous 12 months were recruited by postal questionnaires to a research clinic involving plain radiography (weight-bearing posteroanterior semiflexed, supine skyline and lateral views), clinical interview and physical examination. Any knee ROA, ROA severity, tibiofemoral joint osteoarthritis (TJOA) and patellofemoral joint osteoarthritis (PJOA) were defined using all three radiographic views. Occupational class was derived from current or last job title. Proportions of each gender with symptomatic knee ROA were expressed as percentages, stratified by age; differences between genders were expressed as percentage differences with 95% confidence intervals.</p> <p>Results</p> <p>745 symptomatic participants were eligible and had complete X-ray data. Males had a higher occurrence (77%) of any knee ROA than females (61%). In 50–64 year olds, the excess in men was mild knee OA (particularly PJOA); in ≥65 year olds, the excess was both mild and moderate/severe knee OA (particularly combined TJOA/PJOA). This male excess persisted when using the posteroanterior view only (64% vs. 52%). The lowest level of participation in the clinic was symptomatic females aged 65+. Within each occupational class there were more males with symptomatic knee ROA than females. In those aged 50–64 years, non-articular conditions were equally common in both genders although, in those aged 65+, they occurred more frequently in symptomatic females (41%) than males (31%).</p> <p>Conclusion</p> <p>The excess of knee ROA among symptomatic males in this study seems unlikely to be attributable to the use of comprehensive X-ray views. Although prior occupational exposures and the presence of non-articular conditions cannot be fully excluded, selective non-participation bias seems the most likely explanation. This has implications for future study design.</p

BRCA1 Regulates Follistatin Function in Ovarian Cancer and Human Ovarian Surface Epithelial Cells

Follistatin (FST), a folliculogenesis regulating protein, is found in relatively high concentrations in female ovarian tissues. FST acts as an antagonist to Activin, which is often elevated in human ovarian carcinoma, and thus may serve as a potential target for therapeutic intervention against ovarian cancer. The breast cancer susceptibility gene 1 (BRCA1) is a known tumor suppressor gene in human breast cancer; however its role in ovarian cancer is not well understood. We performed microarray analysis on human ovarian carcinoma cell line SKOV3 that stably overexpress wild-type BRCA1 and compared with the corresponding empty vector-transfected clones. We found that stable expression of BRCA1 not only stimulates FST secretion but also simultaneously inhibits Activin expression. To determine the physiological importance of this phenomenon, we further investigated the effect of cellular BRCA1 on the FST secretion in immortalized ovarian surface epithelial (IOSE) cells derived from either normal human ovaries or ovaries of an ovarian cancer patient carrying a mutation in BRCA1 gene. Knock-down of BRCA1 in normal IOSE cells demonstrates down-regulation of FST secretion along with the simultaneous up-regulation of Activin expression. Furthermore, knock-down of FST in IOSE cell lines as well as SKOV3 cell line showed significantly reduced cell proliferation and decreased cell migration when compared with the respective controls. Thus, these findings suggest a novel function for BRCA1 as a regulator of FST expression and function in human ovarian cells

Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues

Imaging and Modeling Data from the Hydrogen Epoch of Reionization Array

We analyze data from the Hydrogen Epoch of Reionization Array. This is the third in a series of papers on the closure phase delay-spectrum technique designed to detect the HI 21cm emission from cosmic reionization. We present the details of the data and models employed in the power spectral analysis, and discuss limitations to the process. We compare images and visibility spectra made with HERA data, to parallel quantities generated from sky models based on the GLEAM survey, incorporating the HERA telescope model. We find reasonable agreement between images made from HERA data, with those generated from the models, down to the confusion level. For the visibility spectra, there is broad agreement between model and data across the full band of $\sim 80$MHz. However, models with only GLEAM sources do not reproduce a roughly sinusoidal spectral structure at the tens of percent level seen in the observed visibility spectra on scales $\sim 10$ MHz on 29 m baselines. We find that this structure is likely due to diffuse Galactic emission, predominantly the Galactic plane, filling the far sidelobes of the antenna primary beam. We show that our current knowledge of the frequency dependence of the diffuse sky radio emission, and the primary beam at large zenith angles, is inadequate to provide an accurate reproduction of the diffuse structure in the models. We discuss implications due to this missing structure in the models, including calibration, and in the search for the HI 21cm signal, as well as possible mitigation techniques

Understanding the HERA Phase i receiver system with simulations and its impact on the detectability of the EoR delay power spectrum

The detection of the Epoch of Reionization (EoR) delay power spectrum using a "foreground avoidance method" highly depends on the instrument chromaticity. The systematic effects induced by the radio-telescope spread the foreground signal in the delay domain, which contaminates the EoR window theoretically observable. Applied to the Hydrogen Epoch of Reionization Array (HERA), this paper combines detailed electromagnetic and electrical simulations in order to model the chromatic effects of the instrument, and quantify its frequency and time responses. In particular, the effects of the analogue receiver, transmission cables, and mutual coupling are included. These simulations are able to accurately predict the intensity of the reflections occurring in the 150-m cable which links the antenna to the back-end. They also show that electromagnetic waves can propagate from one dish to another one through large sections of the array due to mutual coupling. The simulated system time response is attenuated by a factor $10^{4}$ after a characteristic delay which depends on the size of the array and on the antenna position. Ultimately, the system response is attenuated by a factor $10^{5}$ after 1400 ns because of the reflections in the cable, which corresponds to characterizable ${k_\parallel}$-modes above 0.7 $h\;\rm{Mpc}^{-1}$ at 150 MHz. Thus, this new study shows that the detection of the EoR signal with HERA Phase I will be more challenging than expected. On the other hand, it improves our understanding of the telescope, which is essential to mitigate the instrument chromaticity

Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues

Automated Detection of Antenna Malfunctions in Large-N Interferometers: A case study With the Hydrogen Epoch of Reionization Array

We present a framework for identifying and flagging malfunctioning antennas in large radio interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study. Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets

Foreground modelling via Gaussian process regression: An application to HERA data

The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on the different spectral properties of the two components, although, in real life, the foreground intrinsic spectrum is often corrupted by the instrumental response, inducing systematic effects that can further jeopardize the measurement of the 21-cm signal. In this paper, we use Gaussian Process Regression to model both foreground emission and instrumental systematics in $\sim 2$ hours of data from the Hydrogen Epoch of Reionization Array. We find that a simple co-variance model with three components matches the data well, giving a residual power spectrum with white noise properties. These consist of an "intrinsic" and instrumentally corrupted component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating the line of sight power spectrum over scales $k_{\parallel} \le 0.2$ h cMpc$^{-1}$) and a baseline dependent periodic signal with a period of $\sim 1$ MHz (dominating over $k_{\parallel} \sim 0.4 - 0.8$h cMpc$^{-1}$) which should be distinguishable from the 21-cm EoR signal whose typical coherence-scales is $\sim 0.8$ MHz

Foreground modelling via Gaussian process regression: An application to HERA data

The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on the different spectral properties of the two components, although, in real life, the foreground intrinsic spectrum is often corrupted by the instrumental response, inducing systematic effects that can further jeopardize the measurement of the 21-cm signal. In this paper, we use Gaussian Process Regression to model both foreground emission and instrumental systematics in $\sim 2$ hours of data from the Hydrogen Epoch of Reionization Array. We find that a simple co-variance model with three components matches the data well, giving a residual power spectrum with white noise properties. These consist of an "intrinsic" and instrumentally corrupted component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating the line of sight power spectrum over scales $k_{\parallel} \le 0.2$ h cMpc$^{-1}$) and a baseline dependent periodic signal with a period of $\sim 1$ MHz (dominating over $k_{\parallel} \sim 0.4 - 0.8$h cMpc$^{-1}$) which should be distinguishable from the 21-cm EoR signal whose typical coherence-scales is $\sim 0.8$ MHz