Positive Scalar Curvature Meets Ricci Limit Spaces

We investigate how the positive scalar curvature controls the size of a Ricci limit space when it comes from a sequence of $n$-manifolds with non-negative Ricci curvature and strictly positive scalar curvature lower bound. We prove such a limit space can split off $\mathbb{R}^{n-2}$ at most, and when the maximal splitting happens, the other non-splitting factor has an explicit uniform diameter upper bound. Besides, we study some other consequences of having positive scalar curvature for manifolds using Ricci limit spaces techniques, for instance volume gap estimates and volume growth order estimates.Comment: 22 pages. Some conditions added to the theorem 1.1 due to a gap in the original proof, and the proof is slightly changed accordingly. A corollary about the first Betti number is adde

Filling Radius, Quantitative KK-theory and Positive Scalar Curvature

We prove a quantitative upper bound on the filling radius of complete, spin manifolds with uniformly positive scalar curvature using the quantitative operator $K$-theory and index theory.Comment: minor revisio

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles

<p>Abstract</p> <p>Background</p> <p>High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study.</p> <p>Results</p> <p>The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system.</p> <p>Conclusion</p> <p>The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.</p

The role of Hippo pathway in ovarian development

The follicle is the functional unit of the ovary, whereby ovarian development is largely dependent on the development of the follicles themselves. The activation, growth, and progression of follicles are modulated by a diverse range of factors, including reproductive endocrine system and multiple signaling pathways. The Hippo pathway exhibits a high degree of evolutionary conservation between both Drosophila and mammalian systems, and is recognized for its pivotal role in regulating cellular proliferation, control of organ size, and embryonic development. During the process of follicle development, the components of the Hippo pathway show temporal and spatial variations. Recent clinical studies have shown that ovarian fragmentation can activate follicles. The mechanism is that the mechanical signal of cutting triggers actin polymerization. This process leads to the disruption of the Hippo pathway and subsequently induces the upregulation of downstream CCN and apoptosis inhibitors, thereby promoting follicle development. Thus, the Hippo pathway plays a crucial role in both the activation and development of follicles. In this article, we focused on the development and atresia of follicles and the function of Hippo pathway in these processes. Additionally, the physiological effects of Hippo pathway in follicle activation are also explored

Pathological mechanisms and therapeutic outlooks for arthrofibrosis

Arthrofibrosis is a fibrotic joint disorder that begins with an inflammatory reaction to insults such as injury, surgery and infection. Excessive extracellular matrix and adhesions contract pouches, bursae and tendons, cause pain and prevent a normal range of joint motion, with devastating consequences for patient quality of life. Arthrofibrosis affects people of all ages, with published rates varying. The risk factors and best management strategies are largely unknown due to a poor understanding of the pathology and lack of diagnostic biomarkers. However, current research into the pathogenesis of fibrosis in organs now informs the understanding of arthrofibrosis. The process begins when stress signals stimulate immune cells. The resulting cascade of cytokines and mediators drives fibroblasts to differentiate into myofibroblasts, which secrete fibrillar collagens and transforming growth factor-β (TGF-β). Positive feedback networks then dysregulate processes that normally terminate healing processes. We propose two subtypes of arthrofibrosis occur: active arthrofibrosis and residual arthrofibrosis. In the latter the fibrogenic processes have resolved but the joint remains stiff. The best therapeutic approach for each subtype may differ significantly. Treatment typically involves surgery, however, a pharmacological approach to correct dysregulated cell signalling could be more effective. Recent research shows that myofibroblasts are capable of reversing differentiation, and understanding the mechanisms of pathogenesis and resolution will be essential for the development of cell-based treatments. Therapies with significant promise are currently available, with more in development, including those that inhibit TGF-β signalling and epigenetic modifications. This review focuses on pathogenesis of sterile arthrofibrosis and therapeutic treatments. © 2019, The Author(s)

Bioluminescence imaging reveals inhibition of tumor cell proliferation by Alzheimer's amyloid β protein

Background: Cancer and Alzheimer's disease (AD) are two seemingly distinct diseases and rarely occur simultaneously in patients. To explore molecular determinants differentiating pathogenic routes towards AD or cancer, we investigate the role of amyloid β protein (Aβ) on multiple tumor cell lines that are stably expressing luciferase (human glioblastoma U87; human breast adenocarcinoma MDA-MB231; and mouse melanoma B16F). Results: Quantification of the photons emitted from the MDA-MB231 or B16F cells revealed a significant inhibition of cell proliferation by the conditioning media (CM) derived from amyloid precursor protein (APP) over-expressing cells. The inhibition of U87 cells was observed only after the media was conditioned for longer than 2 days with APP over-expressing cells. Conclusion: Our results suggest that Aβ plays an inhibitory role in tumor cell proliferation; this effect could depend on the type of tumor cells and amount of Aβ

Metatranscriptomic analysis revealed Prevotella as a potential biomarker of oropharyngeal microbiomes in SARS-CoV-2 infection

Background and objectivesDisease severity and prognosis of coronavirus disease 2019 (COVID-19) disease with other viral infections can be affected by the oropharyngeal microbiome. However, limited research had been carried out to uncover how these diseases are differentially affected by the oropharyngeal microbiome of the patient. Here, we aimed to explore the characteristics of the oropharyngeal microbiota of COVID-19 patients and compare them with those of patients with similar symptoms.MethodsCOVID-19 was diagnosed in patients through the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by quantitative reverse transcription polymerase chain reaction (RT-qPCR). Characterization of the oropharyngeal microbiome was performed by metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 144 COVID-19 patients, 100 patients infected with other viruses, and 40 healthy volunteers.ResultsThe oropharyngeal microbiome diversity in patients with SARS-CoV-2 infection was different from that of patients with other infections. Prevotella and Aspergillus could play a role in the differentiation between patients with SARS-CoV-2 infection and patients with other infections. Prevotella could also influence the prognosis of COVID-19 through a mechanism that potentially involved the sphingolipid metabolism regulation pathway.ConclusionThe oropharyngeal microbiome characterization was different between SARS-CoV-2 infection and infections caused by other viruses. Prevotella could act as a biomarker for COVID-19 diagnosis and of host immune response evaluation in SARS-CoV-2 infection. In addition, the cross-talk among Prevotella, SARS-CoV-2, and sphingolipid metabolism pathways could provide a basis for the precise diagnosis, prevention, control, and treatment of COVID-19

Research on UWB Indoor Positioning System Based on TOF Combined Residual Weighting

The performance of TDOA positioning based on UWB is limited by the hyperbolic characteristics of TDOA, especially for tags away from the hyperbolic asymptote. Aiming at this problem, a new UWB indoor positioning system is proposed. Firstly, TOF ranging is adopted to build the positioning equations; then the weighted centroid algorithm of four base stations is presented to compute the initial rough position of the tag; and the residual weighting is introduced to optimize the initial tag position; then, the corresponding nonlinear positioning equations, which will be algebraically transformed to one distribution function, are solved, and the optimal tag coordinates can be obtained by the Newton iteration method. Simulation experiments have verified the positioning reliability of the proposed algorithm under different noise environments and for different tag positions