LINC00662 promotes melanoma progression by competitively binding miR-107 and activating the ß-catenin signaling pathway.

Melanoma is a highly malignant tumor in the body. Long non-coding RNAs (lncRNAs) have been reported to be involved in the development of various tumors. Emerging evidence demonstrates the critical role of lncRNAs in melanoma development. In this study, we aimed to investigate the expression, biological function and regulatory mechanism of LINC00662 in melanomas. First, we found that LINC00662 was up-regulated in melanoma tissues and cell lines. High expression of LINC00662 in melanomas was associated with a poor patient prognosis. Silencing of LINC00662 suppressed the proliferation, migration, and invasion of melanoma cells in vitro and in vivo, while overexpression of LINC00662 promoted melanoma cell proliferation in vitro. Bioinformatics analysis, dual-luciferase assay, and RIP assay confirmed that LINC00662 competitively regulated miR-107. Silencing of LINC00662 upregulated miR-107 expression in a melanoma cell line. Inhibition of miR-107 significantly reversed the inhibitory effect of LINC00662 silencing on cell proliferation and migration. Furthermore, POU3F2 was validated as a downstream target of LINC00662/miR107 and was downregulated when LINC00662 was silenced. Overexpressing POU3F2 attenuated the effect of si-LINC00662 on cellular functions. In addition, the results also showed that the ß-catenin pathway was involved in a si-LINC00662-induced function in melanoma. Overall, our results confirmed that LINC00662 promoted melanoma progression by sponging miR107 and inducing POU3F2, highlighting the mechanism of the LINC00662/miR-107/POU3F2 axis in melanoma cell proliferation and invasion.

Compact optical convolution processing unit based on multimode interference.

Convolutional neural networks are an important category of deep learning, currently facing the limitations of electrical frequency and memory access time in massive data processing. Optical computing has been demonstrated to enable significant improvements in terms of processing speeds and energy efficiency. However, most present optical computing schemes are hardly scalable since the number of optical elements typically increases quadratically with the computational matrix size. Here, a compact on-chip optical convolutional processing unit is fabricated on a low-loss silicon nitride platform to demonstrate its capability for large-scale integration. Three 2 × 2 correlated real-valued kernels are made of two multimode interference cells and four phase shifters to perform parallel convolution operations. Although the convolution kernels are interrelated, ten-class classification of handwritten digits from the MNIST database is experimentally demonstrated. The linear scalability of the proposed design with respect to computational size translates into a solid potential for large-scale integration.

Mental health and labor supply: Evidence from Canada.

This study investigates the relationship between mental health and employment using an instrumental variable approach with the 2012 Canadian Community Health Survey-Mental Health. Using a family member's mental health problem(s) as an instrument for poor mental health, the estimates reveal that poor mental health significantly reduces employment outcomes. These findings are robust to various specifications, such as an alternative instrument and a relaxation of the exclusion restriction assumption. In addition, the relationship is driven mainly by men and younger workers. Moreover, the findings suggest that the relationship is mediated by a decline in cognitive abilities, such as difficulties in concentration and motivation, and social relations with acquaintances and friends. Finally, the estimates show that this phenomenon is contagious: poor mental health has a significant spillover effect on coworkers' mental health in workplaces. This study demonstrates the importance of mental health illness in Canada and other developed countries.

Metabolomics analysis of dietary restriction results in a longer lifespan due to alters of amino acid levels in larval hemolymph of Bombyx mori.

Dietary restriction (DR) has been a very important discovery in modern aging biology research. Its remarkable anti-aging effect has been proved in a variety of organisms, including members of Lepidoptera, but mechanisms by which DR increases longevity are not fully understood. By using the silkworm (Bombyx mori), a model of lepidopteran insect, we established a DR model, isolated hemolymph from fifth instar larvae and employed LC-MS/MS metabolomics to analyze the effect of DR on the endogenous metabolites of silkworm, and tried to clarify the mechanism of DR to prolong lifespan. We identified the potential biomarkers by analyzing the metabolites of the DR and control groups. Then, we constructed relevant metabolic pathways and networks with MetaboAnalyst. DR significantly prolonged the lifespan of silkworm. The differential metabolites between the DR and control groups were mainly organic acids (including amino acid), and amines. These metabolites are involved in metabolic pathways such as amino acid metabolism. Further analysis showed that, the levels of 17 amino acids were significantly changed in the DR group, indicating that the prolonged lifespan was mainly due to changes in amino acid metabolism. Furthermore, we identified 41 and 28 unique differential metabolites in males and females, respectively, demonstrating sex differences in biological responses to DR. The DR group showed higher antioxidant capacity and lower lipid peroxidation and inflammatory precursors, with differences between the sexes. These results provide evidence for various DR anti-aging mechanisms at the metabolic level and novel reference for the future development of DR-simulating drugs or foods.

Dynamic recognition and mirage using neuro-metamaterials.

Breakthroughs in the field of object recognition facilitate ubiquitous applications in the modern world, ranging from security and surveillance equipment to accessibility devices for the visually impaired. Recently-emerged optical computing provides a fundamentally new computing modality to accelerate its solution with photons; however, it still necessitates digital processing for in situ application, inextricably tied to Moore's law. Here, from an entirely optical perspective, we introduce the concept of neuro-metamaterials that can be applied to realize a dynamic object- recognition system. The neuro-metamaterials are fabricated from inhomogeneous metamaterials or transmission metasurfaces, and optimized using, such as topology optimization and deep learning. We demonstrate the concept in experiments where living rabbits play freely in front of the neuro-metamaterials, which enable to perceive in light speed the rabbits' representative postures. Furthermore, we show how this capability enables a new physical mechanism for creating dynamic optical mirages, through which a sequence of rabbit movements is converted into a holographic video of a different animal. Our work provides deep insight into how metamaterials could facilitate a myriad of in situ applications, such as illusive cloaking and speed-of-light information display, processing, and encryption, possibly ushering in an "Optical Internet of Things" era.

Roles of Neuropeptides in Sleep-Wake Regulation.

Sleep and wakefulness are basic behavioral states that require coordination between several brain regions, and they involve multiple neurochemical systems, including neuropeptides. Neuropeptides are a group of peptides produced by neurons and neuroendocrine cells of the central nervous system. Like traditional neurotransmitters, neuropeptides can bind to specific surface receptors and subsequently regulate neuronal activities. For example, orexin is a crucial component for the maintenance of wakefulness and the suppression of rapid eye movement (REM) sleep. In addition to orexin, melanin-concentrating hormone, and galanin may promote REM sleep. These results suggest that neuropeptides play an important role in sleep-wake regulation. These neuropeptides can be divided into three categories according to their effects on sleep-wake behaviors in rodents and humans. (i) Galanin, melanin-concentrating hormone, and vasoactive intestinal polypeptide are sleep-promoting peptides. It is also noticeable that vasoactive intestinal polypeptide particularly increases REM sleep. (ii) Orexin and neuropeptide S have been shown to induce wakefulness. (iii) Neuropeptide Y and substance P may have a bidirectional function as they can produce both arousal and sleep-inducing effects. This review will introduce the distribution of various neuropeptides in the brain and summarize the roles of different neuropeptides in sleep-wake regulation. We aim to lay the foundation for future studies to uncover the mechanisms that underlie the initiation, maintenance, and end of sleep-wake states.

Comprehensive Analysis of Circular RNA Expression in ceRNA Networks and Identification of the Effects of hsa_circ_0006867 in Keloid Dermal Fibroblasts.

Circular RNAs (circRNAs) play a crucial role in the pathogenesis of various fibrotic diseases, but the potential biological function and expression profile of circRNAs in keloids remain unknown. Herein, microarray technology was applied to detect circRNA expression in four patient-derived keloid dermal fibroblasts (KDFs) and normal dermal fibroblasts (NDFs). A total of 327 differentially expressed (DE) circRNAs (fold change > 1.5, p < 0.05) were identified with 195 upregulated and 132 downregulated circRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that the upregulated circRNAs were mainly enriched in the cytoskeleton and tight junctions, while the downregulated circRNAs were related to morphogenesis of the epithelium and axonal guidance. To explore the function of DE circRNAs, a circRNA-miRNA-mRNA network, including five circRNAs, nine miRNAs, and 235 correlated mRNAs, was constructed using bioinformatics analyses. The expression of five DE circRNAs was validated by qRT-PCR in 18 pairs of KDFs and NDFs, and hsa_circ_0006867 showed promising regulatory function in keloids in vitro. Silencing hsa_circ_00006867 suppressed the proliferation, migration, and invasion of keloid fibroblasts. RNA-binding protein immunoprecipitation (RIP) assays indicated that hsa_circ_00006867 may serve as a platform for miRNA binding to Argonaute (AGO) 2. In addition, hsa-miR-29a-5p may be a potential target miRNA of hsa_circ_00006867. Taken together, our research provided multiple novel clues to understand the pathophysiologic mechanism of keloids and identified hsa_circ_0006867 as a biomarker of keloids.

Photonic matrix multiplication lights up photonic accelerator and beyond.

Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms. Photonic accelerators are designed to accelerate specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for computing resources and capacity. Photonic matrix multiplication has much potential to expand the domain of telecommunication, and artificial intelligence benefiting from its superior performance. Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors. In this review, we first introduce the methods of photonic matrix multiplication, mainly including the plane light conversion method, Mach-Zehnder interferometer method and wavelength division multiplexing method. We also summarize the developmental milestones of photonic matrix multiplication and the related applications. Then, we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years. Finally, we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.

Enabling Manufacturable Optical Broadband Angular-Range Selective Films.

The ability to control the propagation direction of light has long been a scientific goal. However, the fabrication of large-scale optical angular-range selective films is still a challenge. This paper presents a polymer-enabled large-scale fabrication method for broadband angular-range selective films that perform over the entire visible spectrum. Our approach involves stacking together multiple one-dimensional photonic crystals with various engineered periodicities to enlarge the bandgap across a wide spectral range based on theoretical predictions. Experimental results demonstrate that our method can achieve broadband transparency at a range of incident angles centered around normal incidence and reflectivity at larger viewing angles, doing so at large scale and low cost.

A Brewster route to Cherenkov detectors.

Cherenkov detectors enable a valuable tool to identify high-energy particles. However, their sensitivity and momentum coverage are limited by the refractive index of host materials. Especially, identifying particles with energy above multiple gigaelectronvolts requires host materials with a near-unity refractive index, which are limited to bulky gas chambers. Overcoming this fundamental material limit is important for future particle detectors yet remains a long-standing challenge. Here, we propose a different paradigm for Cherenkov detectors that utilizes the broadband angular filter made from stacks of variable one-dimensional photonic crystals. Owing to the Brewster effect, the angular filter is transparent only to Cherenkov photons from a precise incident angle. Particle identification is achieved by mapping each Cherenkov angle to the peak-intensity position of transmitted photons in the detection plane. Such angular filtering effect, although decreases the photon number collected in the detection plane, enables the realization of a non-dispersive pseudo refractive index over the entire visible spectrum. Moreover, the pseudo refractive index can be flexibly designed to different values close to unity. Our angular-selective Brewster paradigm offers a feasible solution to implement compact and highly sensitive Cherenkov detectors especially in beam lines with a small angular divergence using regular dielectrics.

Microplastics in an agricultural soil following repeated application of three types of sewage sludge: A field study.

Microplastics were investigated in an agricultural soil to which three types of sludge were repeatedly applied: fresh municipal sludge (FSS1), fresh mixed sludge (mainly industrial sludge) (FSS2), and dry heat-treated municipal sludge (DSS). The percentages of microplastics <1.0 mm were 24.3 and 28.7-59.1 % in unamended and amended soils, respectively. Particles of this size accounted for 47.1-60.0 % of microplastics in different sludges and polymers of particle size <100 µm occurred in all soil samples and sludges examined. Fibers were the commonest microplastic type, ranging from 66.7 to 82.5 % in soil and 89.4-97.2 % in sludges. Polyester (PES) and polypropylene (PP) accounted for ~80 % of the total microplastics found in soil and poly-(styrene:acrylate) (PS-AC) microspheres were found in all sludge-amended soil samples examined. There was also a pronounced weathering effect on the surfaces of the microplastics in soil. Nine years of repeated sludge application led to the accumulation of microplastics in the soil. The abundance of microplastics was significantly higher in the municipal sludge (149.2 ± 52.5 particles kg-1) than in the mixed (68.6 ± 21.5 particles kg-1) or dried (73.1 ± 15.4 particles kg-1) sludge and this was related to the microplastic abundance in the sludges. This field study confirms that sludges are drivers of soil microplastic pollution and measures are required to minimize the inputs of microplastics to agricultural land.

Renal Denervation by Noninvasive Stereotactic Radiotherapy Induces Persistent Reduction of Sympathetic Activity in a Hypertensive Swine Model.

Background We have previously reported the feasibility of noninvasive stereotactic body radiotherapy (SBRT) as a novel approach for renal denervation. Methods and Results Herein, from a translational point of view, we assessed the antihypertensive effect and chronological evolution of SBRT-induced renal nerve injury within 6 months in a hypertensive swine model. Hypertension was induced in swine by subcutaneous implantation of deoxycorticosterone acetate pellets in combination with a high-salt diet. A single dose of 25 Gy with SBRT was delivered for renal denervation in 9 swine within 3.4±1.0 minutes. Blood pressure levels at baseline and 1 and 6 months post-SBRT were comparable to control (n=5), whereas renal norepinephrine was significantly lower at 6 months (P<0.05). Abdominal computed tomography, performed before euthanasia and renal function assessment, remained normal. Standard semiquantitative histological assessment showed that compared with control (1.4±0.4), renal nerve injury was greater at 1 month post-SBRT (2.3±0.3) and peaked at 6 months post-SBRT (3.2±0.8) (P<0.05), along with a higher proportion of active caspase-3-positive nerves (P<0.05). Moreover, SBRT resulted in continuous dysfunction of renal sympathetic nerves and low level of nerve regeneration in 6 months by immunohistochemistry analysis. Conclusions SBRT delivering 25 Gy for renal denervation was safe and related to sustained reduction of sympathetic activity by aggravating nerve damage and inhibiting nerve regeneration up to 6 months; however, its translation to clinical trial should be cautious because of the negative blood pressure response in the deoxycorticosterone acetate-salt hypertensive swine model.

Age-related macular degeneration and premorbid allergic diseases: a population-based case-control study.

Evidence indicates that age-related macular degeneration (AMD) is associated with the prior presence of allergic diseases; however, large-scale studies in the literature are limited. A case-control study was conducted to describe the relationship between premorbid allergic diseases and AMD using Taiwan's National Health Insurance database. Eligibility criteria for inclusion of new adult AMD cases from 2000 to 2013 were set up. We defined the year of diagnosis as the index year. Age-, gender-, index year- matched controls who were drawn from the same database. The case control ratio was 1:4. For all participants, all premorbid conditions staring 1996 to index year were documented. Binary logistic regression was used to describe factors related to AMD occurrence. The AMD group consisted of 10,911 patients, and the comparison group consisted of 43,644 individuals. Patients with AMD showed significant associations with premorbid allergic diseases (aOR 1.54, 95% CI 1.47-1.61), specifically with allergic conjunctivitis (aOR 2.07, 95% CI 1.94-2.20), allergic rhinitis (aOR 1.32, 95% CI 1.25-1.39), asthma (aOR 0.99, 95% CI 0.93-1.06), and atopic dermatitis (aOR 1.04, 95% CI 0.94-1.17). Further analyses indicated that patients with more concurrent allergic diseases have higher associations with AMD than those with fewer concurrent diseases. Patients with more annual medical visits for their allergic diseases also showed higher associations with AMD than those with fewer visits. AMD is significantly associated with premorbid allergic diseases. The underlying mechanisms must be further investigated.

The effect of coverage of smoking-cessation aids on tobacco use: Evidence from Canada.

In clinical trials, smoking-cessation aids (SCAs) have proven to be effective at improving the odds of smoking cessation. Because of the effectiveness of SCAs in these settings, many countries have adopted the coverage of SCAs to reduce tobacco use. However, the effect of such coverage on tobacco use is ambiguous. On one hand, the coverage may have the intended effect and reduce tobacco use. On the other hand, the coverage may cause beneficiaries to participate in tobacco use more as the drug coverage protects beneficiaries from future costs associated with tobacco use. To understand the effect of SCA coverage, we examine it using 2008-2012 Canadian Tobacco Use Monitoring Survey and a difference-in-differences approach. We find that SCA coverage increases cigarette and cigarillo use. Moreover, the effect of SCA coverage on tobacco use is stronger in men and in those with at least a college education. Our results point to the unintended consequences of the coverage of SCAs on tobacco use.

Impacts of anticancer drug parity laws on mortality rates.

This study investigates the impacts of anticancer drug parity laws on mortality rates in the United States using a difference-in-differences approach. Using data from 2004 to 2017 Compressed Mortality Files, we show that the anticancer drug parity laws reduce the mortality rate for head/neck malignant cancers but have no impact on malignant cancers of other types. We also rule out an insurance expansion channel that may influence the relationship between anticancer drug parity laws and malignant cancer mortality. Our results are robust to various specifications and falsification tests. Our findings imply that providing equal access to oral anticancer drugs is an effective tool for the prevention of premature mortality.

The best of both worlds? The economic effects of a hybrid fee-for-service and prospective payment reimbursement system.

Countries seeking to move away from a purely fee-for-service (FFS) system may consider a hybrid approach whereby only some procedures are paid by FFS while others are paid prospectively. Yet little evidence exists whether such a hybrid payment system contains overall costs without adverse influences on health outcomes. In 2003, Japan experienced a reform from FFS to a hybrid payment system in which only some inpatient procedures were paid prospectively. We exploit this reform to test how such a hybrid system affects overall costs and health outcomes. Briefly, we find that healthcare providers responded opportunistically to the reform, moving some procedures out of the bundled inpatient setting to FFS services, leading to no reduction in cost. There was some evidence of a moderate deterioration in health outcomes, in terms of a decline in the probability of symptoms being cured at discharge. In sum, our results suggest that in some cases, a hybrid payment system can be non-superior to either FFS or prospective payment system.

Roadmap on emerging hardware and technology for machine learning.

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing. A hardware platform based on emerging devices and new architecture is the hope for future computing with dramatically improved throughput and energy efficiency. Building such a system, nevertheless, faces a number of challenges, ranging from materials selection, device optimization, circuit fabrication and system integration, to name a few. The aim of this Roadmap is to present a snapshot of emerging hardware technologies that are potentially beneficial for machine learning, providing the Nanotechnology readers with a perspective of challenges and opportunities in this burgeoning field.

Heuristic recurrent algorithms for photonic Ising machines.

The inability of conventional electronic architectures to efficiently solve large combinatorial problems motivates the development of novel computational hardware. There has been much effort toward developing application-specific hardware across many different fields of engineering, such as integrated circuits, memristors, and photonics. However, unleashing the potential of such architectures requires the development of algorithms which optimally exploit their fundamental properties. Here, we present the Photonic Recurrent Ising Sampler (PRIS), a heuristic method tailored for parallel architectures allowing fast and efficient sampling from distributions of arbitrary Ising problems. Since the PRIS relies on vector-to-fixed matrix multiplications, we suggest the implementation of the PRIS in photonic parallel networks, which realize these operations at an unprecedented speed. The PRIS provides sample solutions to the ground state of Ising models, by converging in probability to their associated Gibbs distribution. The PRIS also relies on intrinsic dynamic noise and eigenvalue dropout to find ground states more efficiently. Our work suggests speedups in heuristic methods via photonic implementations of the PRIS.

Inverse design of an integrated-nanophotonics optical neural network.

Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations of the above-mentioned tasks are facing performance ceiling because Moore's Law is slowing down. In this article, we propose an optical neural network architecture based on optical scattering units to implement deep learning tasks with fast speed, low power consumption and small footprint. The optical scattering units allow light to scatter back and forward within a small region and can be optimized through an inverse design method. The optical scattering units can implement high-precision stochastic matrix multiplication with mean squared error <10-4 and a mere 4 × 4 µm2 footprint. Furthermore, an optical neural network framework based on optical scattering units is constructed by introducing "Kernel Matrix", which can achieve 97.1% accuracy on the classic image classification dataset MNIST.

Scattered Dose to Ovary From Radiotherapy for Neuroblastoma in Female Children.

PURPOSE: To measure the scattered dose to ovary from radiotherapy for neuroblastoma in female children and to evaluate the relevant risks for radiation-induced ovarian damage. MATERIAL AND METHODS: Radiotherapy for child neuroblastoma was simulated on the water phantom. The scattered dose to ovary is measured by ionization chamber on the linear accelerator with 3-dimensional conformal radiation therapy and intensity-modulated radiation therapy treatment producing 6MV and 10MV X-rays. The treatment planning procedure was carried out on a computer system (TPS, Oncentra). Optimization of the number and orientation of beams were performed in order to minimize the ovarian dose. RESULTS: For the target dose of 21.6 Gy, the scattered dose to ovary was ranged from 1.3 to 46.8 cGy depending on the treatment method and the energy of the beams. The ovarian dose of intensity-modulated radiation therapy is 1.32 to 1.64 times higher than that of 3-dimensional conformal radiation therapy. The ovarian dose of 6MV beam's energy is 1.52 to 1.64 times higher than that of 10MV beam's energy. For the radiotherapy, the scattered dose of ovaries on phantom by ionization chamber was 1.40 to 2.32 times higher than that on TPS calculated. CONCLUSION: The dosimetric data suggest that pediatric radiotherapy is not associated with a risk for permanent damage to the ovaries in female children. Through choosing the beams' energy and treatment plan's method, the scattered dose of ovaries can be reduced. The risk for development of hereditary disorders in offspring conceived after exposure is low.