The Correspondence between Convergence Peaks from Weak Lensing and Massive Dark Matter Haloes

The convergence peaks, constructed from galaxy shape measurement in weak lensing, is a powerful probe of cosmology as the peaks can be connected with the underlined dark matter haloes. However the capability of convergence peak statistic is affected by the noise in galaxy shape measurement, signal to noise ratio as well as the contribution from the projected mass distribution from the large-scale structures along the line of sight (LOS). In this paper we use the ray-tracing simulation on a curved sky to investigate the correspondence between the convergence peak and the dark matter haloes at the LOS. We find that, in case of no noise and for source galaxies at $z_{\rm s}=1$, more than $65\%$ peaks with $\text{SNR} \geq 3$ (signal to noise ratio) are related to more than one massive haloes with mass larger than $10^{13} {\rm M}_{\odot}$. Those massive haloes contribute $87.2\%$ to high peaks ($\text{SNR} \geq 5$) with the remaining contributions are from the large-scale structures. On the other hand, the peaks distribution is skewed by the noise in galaxy shape measurement, especially for lower SNR peaks. In the noisy field where the shape noise is modelled as a Gaussian distribution, about $60\%$ high peaks ($\text{SNR} \geq 5$) are true peaks and the fraction decreases to $20\%$ for lower peaks ($3 \leq \text{SNR} < 5$). Furthermore, we find that high peaks ($\text{SNR} \geq 5$) are dominated by very massive haloes larger than $10^{14} {\rm M}_{\odot}$.Comment: 13 pages, 11 figures, 4 tables, accepted for publication in MNRAS. Our mock galaxy catalog is available upon request by email to the author ([email protected]

PitNETs and the gut microbiota: potential connections, future directions

The role of the gut microbiome has been widely discussed in numerous works of literature. The biggest concern is the association of the gut microbiome with the central nervous system through the microbiome-brain-gut axis in the past ten years. As more and more research has been done on the relationship between the disease of the central nervous system and gut microbes. This fact is being revealed that gut microbes seem to play an important role from the onset and progression of the disease to clinical symptoms, and new treatments. As a special tumor of the central nervous system, pituitary neuroendocrine tumors (PitNETs)are closely related to metabolism, endocrinology, and immunity. These factors are the vectors through which intestinal microbes interact with the central nervous system. However, little is known about the effects of gut microbes on the PitNET. In this review, the relationship of gut microbiota in PitNETs is introduced, the potential effects of the gut-brain axis in this relationship are analyzed, and future research directions are presented

Cosmological constraints from weak lensing peak statistics with Canada-France-Hawaii Telescope Stripe 82 Survey

We derived constraints on cosmological parameters using weak lensing peak statistics measured on the ∼ 130 deg2 of the Canada-France-Hawaii Telescope Stripe 82 Survey. This analysis demonstrates the feasibility of using peak statistics in cosmological studies. For our measurements, we considered peaks with signal-to-noise ratio in the range of ν = [3, 6]. For a flat Λ cold dark matter model with only (Ωm, σ8) as free parameters, we constrained the parameters of the following relation Σ8 = σ8(Ωm/0.27)α to be Σ8 = 0.82 ± 0.03 and α = 0.43 ± 0.02. The α value found is considerably smaller than the one measured in two-point and three-point cosmic shear correlation analyses, showing a significant complement of peak statistics to standard weak lensing cosmological studies. The derived constraints on (Ωm, σ8) are fully consistent with the ones from either WMAP9 or Planck. From the weak lensing peak abundances alone, we obtained marginalized mean values of $\Omega _{\rm m}=0.38^{+0.27}_{-0.24}$ and σ8 = 0.81 ± 0.26. Finally, we also explored the potential of using weak lensing peak statistics to constrain the mass-concentration relation of dark matter haloes simultaneously with cosmological parameter

Application of “mosiac sign” on T2-WI in predicting the consistency of pituitary neuroendocrine tumors

PurposeTumor consistency is important for pituitary neuroendocrine tumors (PitNETs) resection to improve surgical outcomes. In this study, we evaluated the T2-WI of PitNETs and defined a specific T2-WI signaling manifestation, the “Mosaic sign,” to predict tumor consistency and resection of PitNETs.DesignA retrospective review of MRI and tumor histology of 137 consecutive patients who underwent endoscopic endonasal resection for PitNETs was performed.MethodsThe “Mosaic sign” was defined by the ratio of the tumor itself T2-WI signals, and characterized by multiple intratumor hyperintense dots. The degree of tumor resection was an assessment by postoperative MRI examination. The presence of the “Mosaic sign” was compared with patients' basic information, tumor consistency, tumor pathological staining, and surgical result. To determine whether the presence or absence of “Mosaic sign” could predict tumor consistency and guide surgical resection of tumors.ResultsStatistical analysis showed that the consistency of the tumor and the degree of resection were correlated with the “Mosaic sign”. In the 137 cases of T2-WI, 43 had “Mosaic sign”, 39 cases had soft tumor consistency, and 4 were classified as fibrous, of which 42 were completely resected and 1 was subtotal resected. Of the 94 patients without “Mosaic sign”, the consistency of tumor of 54 cases were classified as soft, the remaining 40 cases were fibrous, 80 cases were completely resected, and 14 cases were subtotal resected. Postoperative cerebrospinal fluid leakage occurred in 1 patient. The number of corticotroph adenomas in the group of “Mosaic sign” was higher, with the statistical difference between the two groups (P = 0.0343).ConclusionsThe presence of the “Mosaic sign” in T2-WI may provide preoperative information for pituitary adenomas consistency and effectively guide surgical approaches

Cosmological Constraints From Weak Lensing Peak Statistics With CFHT Stripe 82 Survey

We derived constraints on cosmological parameters using weak lensing peak statistics measured on the $\sim130~{\rm deg}^2$ of the Canada-France-Hawaii Telescope Stripe 82 Survey (CS82). This analysis demonstrates the feasibility of using peak statistics in cosmological studies. For our measurements, we considered peaks with signal-to-noise ratio in the range of $\nu=[3,6]$. For a flat $\Lambda$CDM model with only $(\Omega_{\rm m}, \sigma_8)$ as free parameters, we constrained the parameters of the following relation $\Sigma_8=\sigma_8(\Omega_{\rm m}/0.27)^{\alpha}$ to be: $\Sigma_8=0.82 \pm 0.03$ and $\alpha=0.43\pm 0.02$. The $\alpha$ value found is considerably smaller than the one measured in two-point and three-point cosmic shear correlation analyses, showing a significant complement of peak statistics to standard weak lensing cosmological studies. The derived constraints on $(\Omega_{\rm m}, \sigma_8)$ are fully consistent with the ones from either WMAP9 or Planck. From the weak lensing peak abundances alone, we obtained marginalised mean values of $\Omega_{\rm m}=0.38^{+0.27}_{-0.24}$ and $\sigma_8=0.81\pm 0.26$. Finally, we also explored the potential of using weak lensing peak statistics to constrain the mass-concentration relation of dark matter halos simultaneously with cosmological parameters.Comment: 17 pages, 11 figures, MNRAS in pres

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase&nbsp;chain&nbsp;reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of&nbsp;prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics