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Menopause predisposes women to osteoporosis due to declining estrogen levels. This results in a decrease in bone mineral density (BMD) and an increase in fractures. Osteoporotic fractures lead to substantial morbidity and mortality, and are considered one of the largest public health priorities by the World Health Organization (WHO). It is therefore essential for menopausal women to receive appropriate guidance for the prevention and management of osteoporosis. The Women’s Health Initiative (WHI) randomized controlled trial first proved hormonal therapy (HT) reduces the incidence of all osteoporosis-related fractures in postmenopausal women. However, the study concluded that the adverse effects outweighed the potential benefits on bone, leading to a significant decrease in HT use for menopausal symptoms. Additionally, HT was not used as first-line therapy for osteoporosis and fractures. Subsequent studies have challenged these initial conclusions and have shown significant efficacy of HT in various doses, durations, regimens, and routes of administration. These studies support that HT improves BMD and reduces fracture risk in women with and without osteoporosis. Furthermore, the studies suggest that low-dose and transdermal HT are less likely associated with the adverse effects of breast cancer, endometrial hyperplasia, coronary artery disease (CAD), and venous thromboembolism (VTE) previously observed in standard-dose oral HT regimens. Given the need for estrogen in menopausal women and evidence supporting the cost effectiveness, safety, and efficacy of HT, we propose that HT should be considered for the primary prevention and treatment of osteoporosis in appropriate candidates. HT should be individualized and the once “lowest dose for shortest period of time” concept should no longer be used. This review will focus on the prior and current studies for various HT formulations used for the prevention and treatment of osteoporosis, exploring the safety profile of low-dose and transdermal HT that have been shown to be safer than oral standard-dose HT.

Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. Traditional experimental implementations need N 2 units such as Mach-Zehnder interferometers (MZIs) for an input dimension N to realize typical computing operations (convolutions and matrix multiplication), resulting in limited scalability and consuming excessive power. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing using two ultracompact diffractive cells (Fourier transform operation) and only N MZIs. The footprint and energy consumption scales linearly with the input data dimension, instead of the quadratic scaling in the traditional ONN framework. A ~10-fold reduction in both footprint and energy consumption, as well as equal high accuracy with previous MZI-based ONNs was experimentally achieved for computations performed on the MNIST and Fashion-MNIST datasets. The integrated diffractive optical network (IDNN) chip demonstrates a promising avenue towards scalable and low-power-consumption optical computational chips for optical-artificial-intelligence. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing with reduced footprint and energy consumption.

Osteoclasts are cells derived from bone marrow macrophages and are important in regulating bone resorption during bone homeostasis. Understanding what drives osteoclast differentiation and activity is important when studying diseases characterized by heightened bone resorption relative to formation, such as osteoporosis. In the last decade, studies have indicated that reactive oxygen species (ROS), including superoxide and hydrogen peroxide, are crucial components that regulate the differentiation process of osteoclasts. However, there are still many unanswered questions that remain. This review will examine the mechanisms by which ROS can be produced in osteoclasts as well as how it may affect osteoclast differentiation and activity through its actions on osteoclastogenesis signaling pathways. In addition, the contribution of ROS to the aging-associated disease of osteoporosis will be addressed and how targeting ROS may lead to the development of novel therapeutic treatment options.

Complex-valued neural networks have many advantages over their real-valued counterparts. Conventional digital electronic computing platforms are incapable of executing truly complex-valued representations and operations. In contrast, optical computing platforms that encode information in both phase and magnitude can execute complex arithmetic by optical interference, offering significantly enhanced computational speed and energy efficiency. However, to date, most demonstrations of optical neural networks still only utilize conventional real-valued frameworks that are designed for digital computers, forfeiting many of the advantages of optical computing such as efficient complex-valued operations. In this article, we highlight an optical neural chip (ONC) that implements truly complex-valued neural networks. We benchmark the performance of our complex-valued ONC in four settings: simple Boolean tasks, species classification of an Iris dataset, classifying nonlinear datasets (Circle and Spiral), and handwriting recognition. Strong learning capabilities (i.e., high accuracy, fast convergence and the capability to construct nonlinear decision boundaries) are achieved by our complex-valued ONC compared to its real-valued counterpart. Most demonstrations of optical neural networks for computing have been so far limited to real-valued frameworks. Here, the authors implement complex-valued operations in an optical neural chip that integrates input preparation, weight multiplication and output generation within a single device.

The kagome lattice 1 , which is the most prominent structural motif in quantum physics, benefits from inherent non-trivial geometry so that it can host diverse quantum phases, ranging from spin-liquid phases, to topological matter, to intertwined orders 2 – 8 and, most rarely, to unconventional superconductivity 6 , 9 . Recently, charge sensitive probes have indicated that the kagome superconductors A V 3 Sb 5 ( A = K, Rb, Cs) 9 – 11 exhibit unconventional chiral charge order 12 – 19 , which is analogous to the long-sought-after quantum order in the Haldane model 20 or Varma model 21 . However, direct evidence for the time-reversal symmetry breaking of the charge order remains elusive. Here we use muon spin relaxation to probe the kagome charge order and superconductivity in KV 3 Sb 5 . We observe a noticeable enhancement of the internal field width sensed by the muon ensemble, which takes place just below the charge ordering temperature and persists into the superconducting state. Notably, the muon spin relaxation rate below the charge ordering temperature is substantially enhanced by applying an external magnetic field. We further show the multigap nature of superconductivity in KV 3 Sb 5 and that the T c / λ a b − 2 ratio (where T c is the superconducting transition temperature and λ ab is the magnetic penetration depth in the kagome plane) is comparable to those of unconventional high-temperature superconductors. Our results point to time-reversal symmetry-breaking charge order intertwining with unconventional superconductivity in the correlated kagome lattice. An investigation of muon spin relaxation shows time-reversal symmetry-breaking charge order, intertwined with correlated superconductivity, due to orbital currents in the kagome superconductor KV 3 Sb 5 .

SummaryOur study demonstrated a high incidence of recollapse of the augmented vertebrae after PVP treatment for OVCFs. A risk score based on all significant factors can predict the rate of recollapse and gain clinical benefits to prevent recollapse in patients at high risk.BackgroundRecollapse of the augmented vertebrae after percutaneous vertebroplasty (PVP) treatment for osteoporotic vertebral compression fractures (OVCFs) has obtained much attention. However, little is known about risk factors and score for recollapse of the augmented vertebrae.ObjectiveTo determine risk factors and furthermore develop a risk score related to recollapse of the augmented vertebrae after PVP treatment for OVCFs.MethodsPatients who were treated with PVP for single OVCFs and met this study’s inclusion criteria were retrospectively reviewed. The follow-up period was at least 2 years. Associations of recollapse with co-variates (age, gender, bone mass density [BMD] with a T-score, fracture level, intravertebral cleft [IVC], fracture type, cement volume, cement leakage, leakage into a disc, cement distribution pattern, Non-PMMA-endplate-contact [NPEC], preoperative fracture severity, reduction rate [RR], reduction angle [RA]) were analyzed and a risk score for recollapse was further developed to predict recollapse.ResultsA total of 152 patients were included. Recollapse group was found in 42 (27.6%) patients. Preoperative IVC, solid lump cement distribution pattern, more RR (a cutoff value of 7%) and larger RA (a cutoff value of 3°) was significantly associated with increased risk for recollapse of the augmented vertebrae. A risk score was developed based on the number of risk factors present in each patient. Patients with a score of 4 had an approximately ninefold increased risk of developing recollapse over patients with a score of 0. The receiver operating characteristic curve of the risk score generated an area under the curve of 0.899 (95% CI 0.642–0.836, P = 0.000).ConclusionA risk score based on preoperative IVC, cement distribution pattern, reduction rate, and reduction angle predicts the rate of recollapse. Additional studies should aim to validate this score and inspect clinical benefits of recollapse prophylaxis in patients at high risk.

Vps34, a class III PtdIns3 lipid kinase involved in the control of both autophagic and endocytic systems, has been studied extensively in numerous fundamental cellular processes. Accumulating evidence indicates that Vps34 may also contribute to the development and progression of human cancers. However, the mechanism of Vps34 in tumorigenesis remains elusive. Here, we report an unanticipated role of Vps34 in the activation of p62 for cancer development. We identified that Vps34 is a transcriptional activator of p62 through competition of Nrf2 (nuclear factor erythroid 2-related factor 2) for Keap1 binding. Vps34 augments the association of PKC-δ with p62 for its phosphorylation at Serine 349, which leads to positive feedback on the Nrf2-dependent transcription of oncogenes. Additionally, we found that the expression of Vps34 is correlated with the tumorigenic activity of human breast cancer cells. Normally inactive in breast cancer, caspase 8 can cleave Vps34 at residue D285, which directly abolished its lipid kinase activity and dramatically altered cell invasion potential, colony formation, as well as tumorigenesis in orthotopic engraftments in mice. The cleavage at D285 blocks expression of LC3-II, Nrf2 and subsequently, p62, in addition to blocking tumor growth, indicating that the intact structure of Vps34 is essential for its activity. Moreover, either knockout of PKC-δ or knockdown of p62 by small interfering RNA in MCF-7 cells abrogates Vps34-dependent tumor growth. Data presented here suggested that Vps34 stimulates tumor development mainly through PKC-δ- activation of p62.

MicroRNAs are a class of small non-coding RNAs that have been implicated to mediate gene regulation in virtually all important biological processes. Recently there is accumulating evidence showing that miR-150 has essential regulatory roles in both normal and malignant hematopoiesis and holds great potential as a therapeutic target in treating various types of hematopoietic malignancies. The purpose of this review is to summarize our current knowledge about the expression patterns, biological functions and regulatory mechanisms of miR-150 in normal and malignant hematopoiesis, and to highlight the important questions to be answered in this burgeoning field.

The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1) is a modeling framework for estimating fluxes of biogenic compounds between terrestrial ecosystems and the atmosphere using simple mechanistic algorithms to account for the major known processes controlling biogenic emissions. It is available as an offline code and has also been coupled into land surface and atmospheric chemistry models. MEGAN2.1 is an update from the previous versions including MEGAN2.0, which was described for isoprene emissions by Guenther et al. (2006) and MEGAN2.02, which was described for monoterpene and sesquiterpene emissions by Sakulyanontvittaya et al. (2008). Isoprene comprises about half of the total global biogenic volatile organic compound (BVOC) emission of 1 Pg (1000 Tg or 1015 g) estimated using MEGAN2.1. Methanol, ethanol, acetaldehyde, acetone, α-pinene, β-pinene, t-β-ocimene, limonene, ethene, and propene together contribute another 30% of the MEGAN2.1 estimated emission. An additional 20 compounds (mostly terpenoids) are associated with the MEGAN2.1 estimates of another 17% of the total emission with the remaining 3% distributed among >100 compounds. Emissions of 41 monoterpenes and 32 sesquiterpenes together comprise about 15% and 3%, respectively, of the estimated total global BVOC emission. Tropical trees cover about 18% of the global land surface and are estimated to be responsible for ~80% of terpenoid emissions and ~50% of other VOC emissions. Other trees cover about the same area but are estimated to contribute only about 10% of total emissions. The magnitude of the emissions estimated with MEGAN2.1 are within the range of estimates reported using other approaches and much of the differences between reported values can be attributed to land cover and meteorological driving variables. The offline version of MEGAN2.1 source code and driving variables is available from http://bai.acd.ucar.edu/MEGAN/ and the version integrated into the Community Land Model version 4 (CLM4) can be downloaded from http://www.cesm.ucar.edu/.

The molecular characterization of cytogenetic abnormalities has not only provided insights into the mechanisms of leukemogenesis but also led to the establishment of new treatment strategies targeting these abnormalities and thereby further improve the prognosis of patients. We analyzed the prognosis of 1091 Chinese patients with newly diagnosed acute lymphoblastic leukemia (ALL) and explored the prognostic impacts of a large number of cytogenetic/molecular abnormalities. It was demonstrated that, in both B- and T-ALL settings, the prognosis was negatively correlated to the age as reported to date. For childhood T-ALL patients, it was also documented that the HOX11 expression represented a favorable prognostic factor as it was in adult ones. We identified CRLF2 overexpression as an intermediate-risk marker and Ik6 variant of IKZF1 gene as a high-risk one when stratifying pediatric B-ALL cases according to cytogenetic/molecular risks. We also found that Ik6 variant and CRLF2 overexpression had an important role in dictating the prognosis of Ph-negative patients, which may be useful markers in guiding the treatment of ALL in the future, with tyrosine kinase inhibitors on the other hand reversing the fate of Ph-positive ALL patients.