The role of integrins on megakaryocyte development and function

Integrins are cell surface receptors mainly involved with cell-cell adhesion and cell adhesion to extracellular matrix (ECM) proteins. Integrin signaling participates in many cellular pathways and has multiple effects on cell behavior. The role of integrins on megakaryocytes (MKs) has been extensively studied, and integrins have been proven to be vital in regulating MK development and functions. MKs are large platelet-producing cells primarily residing in the bone marrow (BM). The interactions between MK and ECM proteins in the BM via integrins are thought to play an important role in maintaining normal thrombopoiesis, and deregulation of integrin signaling may lead to impaired MK maturation, MK migration, and proplatelet formation. Integrins also take part in the cell-cell adhesion of MK to other cells in the BM, such as osteoblasts and fibroblasts. MK adhesion is proved to stimulate the expansion of fibroblasts and osteoblasts, which may have strong implications for treating bone marrow fibrosis (BMF) and osteoporosis. In this review, we introduce different types of integrins expressed on MK and discuss their roles during MK differentiation and maturation from hematopoietic stem cells (HSCs) as well as their functions during thrombopoiesis. We also focus on surveying the interactions of MK with other BM cells via integrin signaling and examining the functions of MK integrins in regulating BM homeostasis. Finally, we explain diseases caused by defects associated with MK integrins and explore potential therapeutic treatments

Few-shot Image Generation via Style Adaptation and Content Preservation

Training a generative model with limited data (e.g., 10) is a very challenging task. Many works propose to fine-tune a pre-trained GAN model. However, this can easily result in overfitting. In other words, they manage to adapt the style but fail to preserve the content, where \textit{style} denotes the specific properties that defines a domain while \textit{content} denotes the domain-irrelevant information that represents diversity. Recent works try to maintain a pre-defined correspondence to preserve the content, however, the diversity is still not enough and it may affect style adaptation. In this work, we propose a paired image reconstruction approach for content preservation. We propose to introduce an image translation module to GAN transferring, where the module teaches the generator to separate style and content, and the generator provides training data to the translation module in return. Qualitative and quantitative experiments show that our method consistently surpasses the state-of-the-art methods in few shot setting

Characteristics of the salivary microbiota in cheilitis granulomatosa

Cheilitis granulomatosa (CG) is a disturbing and persistent idiopathic lip swelling. The cause and treatment has not been wholly elucidated. Some reports infer that CG is mainly associated with dental infection but no firm or reliable microbiological evidence has been provided for a causative organism. This study aimed to evaluate whether microorganisms contribute to the etiology of CG in order to inform appropriate treatment options in clinic. Unstimulated saliva was collected from 15 CG patients who were diagnosed clinically and pathologically and 15 healthy controls (HC). DNA was extracted from the precipitate of the centrifuged saliva for 16s rRNA high-throughput sequencing using the Miseq PE300 platform. The distribution of the microbiome between the two groups was compared. CG patients had a greater microbial flora that was more diverse than the HC. Prevotella, Alloprevotella, Porphyromonas, Actinomyces, Rothia, Fusobacterium, Haemophilus, and Aggregatibacter had a significantly higher abundance in CG patients. In contrast, Streptococcus and Campylobacter were the most abundant genera in HC with a mean relative abundance of 63% and 2%, respectively. The microbiological network indicated that most of the bacteria that were enriched at greater levels in CG patients were likely to be Prevotella, Actinomyces, and Rothia. These have been shown to co-exist with other bacteria. The composition and structure of bacterial communities in CG patients were different from HC. Most of the genera observed in CG patients were associated with periodontitis and pulp infection. These findings might be helpful in understanding the etiology of CG. Further study will be needed to confirm these findings and explore the underlying pathological mechanism

kMap.py: A Python program for simulation and data analysis in photoemission tomography

For organic molecules adsorbed as well-oriented ultra-thin films on metallic surfaces, angle-resolved photoemission spectroscopy has evolved into a technique called photoemission tomography (PT). By approximating the final state of the photoemitted electron as a free electron, PT uses the angular dependence of the photocurrent, a so-called momentum map or k-map, and interprets it as the Fourier transform of the initial state's molecular orbital, thereby gains insights into the geometric and electronic structure of organic/metal interfaces. In this contribution, we present kMap.py which is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform of real space molecular orbital distributions, which are used as program input and taken from density functional calculations. The program allows the user to vary a number of simulation parameters such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program enabling a direct visual comparison as well as an automatic optimization procedure to determine structural parameters of the molecules or weights of molecular orbitals contributions. With an increasing number of experimental groups employing photoemission tomography to study adsorbate layers, we expect kMap.py to serve as an ideal analysis software to further extend the applicability of PT

Rough set theory applied to pattern recognition of partial discharge in noise affected cable data

This paper presents an effective, Rough Set (RS) based, pattern recognition method for rejecting interference signals and recognising Partial Discharge (PD) signals from different sources. Firstly, RS theory is presented in terms of Information System, Lower and Upper Approximation, Signal Discretisation, Attribute Reduction and a flowchart of the RS based pattern recognition method. Secondly, PD testing of five types of artificial defect in ethylene-propylene rubber (EPR) cable is carried out and data pre-processing and feature extraction are employed to separate PD and interference signals. Thirdly, the RS based PD signal recognition method is applied to 4000 samples and is proven to have 99% accuracy. Fourthly, the RS based PD recognition method is applied to signals from five different sources and an accuracy of more than 93% is attained when a combination of signal discretisation and attribute reduction methods are applied. Finally, Back-propagation Neural Network (BPNN) and Support Vector Machine (SVM) methods are studied and compared with the developed method. The proposed RS method is proven to have higher accuracy than SVM and BPNN and can be applied for on-line PD monitoring of cable systems after training with valid sample data

Finite element study of the biomechanical effects on the rotator cuff under load

Rotator cuff injuries account for 50% of shoulder disorders that can cause shoulder pain and reduced mobility. The occurrence of rotator cuff injury is related to the variation in shoulder load, but the mechanical changes in the rotator cuff caused by load remain unclear. Therefore, the mechanical results of the rotator cuff tissue during glenohumeral abduction and adduction were analyzed based on a finite element shoulder model under non-load (0 kg) and load (7.5 kg) conditions. The results showed that the maximum von Mises stress on the supraspinatus muscle was larger than that on the subscapularis, infraspinatus, and teres minor muscles during glenohumeral abduction. Compared with the non-load condition, the maximum von Mises stress on the supraspinatus muscle increased by 75% under the load condition at 30° abduction. Under the load condition, the supraspinatus joint side exhibited an average stress that was 32% greater than that observed on the bursal side. The von Mises stress on the infraspinatus muscle was higher than that in other rotator cuff tissues during adduction. The stress on the infraspinatus muscle increased by 36% in the load condition compared to the non-load condition at 30° adduction. In summary, the increased load changed the mechanical distribution of rotator cuff tissue and increased the stress differential between the joint aspect and the bursal aspect of the supraspinatus tendon

How cold is the junction of a millikelvin scanning tunnelling microscope?

We employ a scanning tunnelling microscope (STM) cooled to millikelvin temperatures by an adiabatic demagnetization refrigerator (ADR) to perform scanning tunnelling spectroscopy (STS) on an atomically clean surface of Al(100) in a superconducting state using normal-metal and superconducting STM tips. Varying the ADR temperatures between 30 mK and 1.2 K, we show that the temperature of the STM junction $T$ is decoupled from the temperature of the surrounding environment $T_{\mathrm{env}}$. Simulating the STS data with the $P(E)$ theory, we determine that $T_{\mathrm{env}} \approx 1.5$ K, while the fitting of the superconducting gap spectrum yields the lowest $T=77$ mK.Comment: 12 pages, 10 figure