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As a new type of two-dimensional semiconductor material, violet phosphorus (VP) has recently attracted much attention for applications in the field of optoelectronics. Although mechanical exfoliation has been used to prepare VP nanoribbons or nanosheets, production of the high quantum yield VP quantum dots (VPQDs) remains a challenge. Herein, the VPQDs are prepared via liquid exfoliation in ethanol and subsequent solvothermal treatment under 180 °C in dimethylformamide. The prepared VPQDs have a mean size of about 2 nm and can emit a strong blue photoluminescence (PL) when exchanged in ethanol solution. The quantum yield can reach 8.6%. The strong PL arises from both the band-to-band recombination related to quantum confinement effects and P-O-C related surface bonding state. Furthermore, the VPQDs solution has a good photostability under ambient conditions, suggesting their possible potential in fluorescent biological imaging and photocatalytic reactions.

Background Recent genome-wide association meta-analysis for melanoma doubled the number of previously identified variants. We assessed the performance of an updated polygenic risk score (PRS) in a population of older individuals, where melanoma incidence and cumulative ultraviolet radiation exposure is greatest. Methods We assessed a PRS for cutaneous melanoma comprising 55 variants in a prospective study of 12 712 individuals in the ASPirin in Reducing Events in the Elderly Trial. We evaluated incident melanomas diagnosed during the trial and prevalent melanomas diagnosed preenrolment (self-reported). Multivariable models examined associations between PRS as a continuous variable (per SD) and categorical (low-risk [0%-20%], medium-risk [21%-80%], high-risk [81%-100%] groups) with incident melanoma. Logistic regression examined the association between PRS and prevalent melanoma. Results At baseline, mean participant age was 75 years; 55.0% were female, and 528 (4.2%) had prevalent melanomas. During follow-up (median = 4.7 years), 120 (1.0%) incident cutaneous melanomas occurred, 98 of which were in participants with no history. PRS was associated with incident melanoma (hazard ratio = 1.46 per SD, 95% confidence interval [CI] = 1.20 to 1.77) and prevalent melanoma (odds ratio [OR] = 1.55 per SD, 95% CI = 1.42 to 1.69). Participants in the highest-risk PRS group had increased risk compared with the low-risk group for incident melanoma (OR = 2.51, 95% CI = 1.28 to 4.92) and prevalent melanoma (OR = 3.66, 95% CI = 2.69 to 5.05). When stratifying by sex, only males had an association between the PRS and incident melanoma, whereas both sexes had an association between the PRS and prevalent melanoma. Conclusions A genomic risk score is associated with melanoma risk in older individuals and may contribute to targeted surveillance.

Fast radio bursts (FRBs) are millisecond-duration radio transients and can be used as a cosmological probe. However, the dispersion measure (DM) contributed by intergalactic medium (IGM) is hard to be distinguished from other components. In this paper, we use the IllustrisTNG simulation to realistically estimate the $DM_{\rm IGM}$ up to $z\sim 9$. We find $DM_{\rm IGM} = 892^{+721}_{-270}$ pc cm$^{-3}$ at $z=1$. The probability distribution of $DM_{\rm IGM}$ can be well fitted by a quasi-Gaussian function with a long tail. The tail is caused by the structures along the line of sight in IGM. Subtracting DM contributions from the Milky Way and host galaxy for localized FRBs, the $DM_{\rm IGM}$ value is close to the derived $DM_{\rm IGM}-z$ relation. We also show the capability to constrain the cosmic reionization history with the $DM_{\rm IGM}$ of high-redshift FRBs in the IllustrisTNG universe. The derived $DM_{\rm IGM}-z$ relation at high redshifts can be well fitted by a $tanh$ reionization model with the reionization redshift $z=5.95$, which is compatible with the reionization model used by the IllustrisTNG simulation. The $DM_{\rm IGM}$ of high-redshift FRBs also provides an independent way to measure the optical depth of cosmic microwave background (CMB). Our result can be used to derive the pseudo-redshifts of non-localized FRBs for $DM_{\rm IGM}, 10 pges, 1 table, accepted for publication in ApJ

The GUM Supplement 2 describes a Monte Carlo Method (MCM) for evaluating measurement models with more than one output quantity. Such models are common in electrical metrology where the measurands m...

Summary Background Almost a third of those undergoing knee replacement for osteoarthritis have poor outcomes despite technically successful surgery. Preoperative neuropathic-like pain and/or pain sensitisation may increase the risk of pain following joint replacement. Objective To examine whether preoperative neuropathic-like pain and pain sensitisation predicts pain, function and satisfaction following joint replacement for knee osteoarthritis. Design Systematic review with meta-analysis. Methods Medline, EMBASE and CINAHL were systematically searched until March 2020. Studies detecting neuropathic-like pain and/or sensitisation using self-report questionnaires prior to knee replacement for osteoarthritis, and relating this to post-operative outcomes were identified. Data extraction, risk of bias assessment and meta-analysis were performed, where appropriate. Results Five manuscripts, including one preprint, examining six cohorts were included: four used painDETECT or modified painDETECT, one the Self-Report Leeds Assessment of Neuropathic Symptoms and Signs, and another the Central Sensitisation Inventory to identify preoperative characteristics. Three studies showed preoperative neuropathic-like pain or sensitisation was associated with more intense post-operative pain. All four studies examining the risk of significant pain after knee replacement suggested it was increased after > 3 months. The only study examining patient satisfaction and function found reduced satisfaction, but no difference in function in those with preoperative sensitisation. Meta-analysis found the relative risk of increased pain following knee replacement in those with neuropathic-like pain(painDETECT > 13) to be 2.05(95% confidence intervals 1.51, 2.79). Conclusion These results provide consistent but limited evidence that self-report tools detecting neuropathic-like pain and/or pain sensitisation, predict patients at higher risk of pain following knee replacement.

Hepatocellular carcinoma is highly resistant to chemotherapy. Here we evaluated the use and efficacy of milk-derived nanovesicles (MNV) as an approach to improve delivery of anticancer agents into HCC cells and intrahepatic tumors. We developed a protocol for isolation of MNVs from skim milk using ultracentrifugation, and characterized using nanoparticle tracking analysis (NTA) and electron microscopy. MNVs were loaded with doxorubicin (dox-MNV) or miR221 antisense oligonucleotides (anti-miR221-MNV), and further evaluated using spectrophotometry, NTA, and zeta potential measurements. HepG2, Hep3B, and PLC/PRF/5 HCC cells in culture were treated with dox-MNV and anti-miR221-MNV and evaluated with drug delivery and anticancer activity. The efficacy of dox-MNV and anti-miR221-MNV to arrest tumor growth in vivo was assessed on intrahepatic tumors induced in nude mice. Cellular uptake studies showed plain and dox-MNV attained saturation within 4 h of treatment. Cytotoxicity studies on HepG2, Hep3B, and PLC/PRF/5 HCC cells with dox-MNV at 1 µM resulted in 20% cell death at 24 h, 50% at 48 h, and 80% at 72 h. HepG2 cells treated with dox-MNV and anti-miR221-MNV exhibited nuclear disintegration, and apoptosis within 24 h. Combination treatment of intrahepatic tumors with dox-MNV and anti-miR221-MNV resulted in marked reduction of tumor size and increased survival rate in nude mice. Our studies demonstrated that MNVs can be effectively used for successful delivery of anticancer agents into HCC cells and intrahepatic tumors. MNV-mediated targeted delivery of anticancer agents could be an efficient modality for the treatment of malignant HCC and might produce a great impact on anticancer therapy.

By leveraging the stroboscopic effect, a new method, namely the Stationary Counting Method, has been developed at the Standards and Calibration Laboratory (SCL) of Hong Kong for calibrating...

Uncorrected refractive errors are a leading cause of visual impairment across the world. In today's society, laser in situ keratomileusis (LASIK) has become the most commonly performed surgical procedure to correct refractive errors. However, regression of the initially achieved refractive correction has been a widely observed phenomenon following LASIK since its inception more than two decades ago. Despite technological advances in laser refractive surgery and various proposed management strategies, post-LASIK regression is still frequently observed and has significant implications for the long-term visual performance and quality of life of patients. This review explores the mechanism of refractive regression after both myopic and hyperopic LASIK, predisposing risk factors and its clinical course. In addition, current preventative strategies and therapies are also reviewed.

SUMMARY TUC338 is an ultraconserved long non-coding RNA that contributes to transformed cell growth in hepatocellular carcinoma (HCC). Genomic regions of TUC338 occupancy were enriched in unique or known binding motifs homologous to the tumor suppressors Pax6 and p53. Genes involved in cell proliferation were enriched within a 9-kb range of TUC338-binding sites. TUC338 RNA-based purification was used to isolate chromatin for mass spectrometry, and the plasminogen activator inhibitor-1 RNA-binding protein (PAI-RBP1) was identified as a TUC338 RNA-binding partner. The PAI-RBP1 target gene plasminogen activator inhibitor-1 (PAI-1) itself could also be post-transcriptionally regulated by TUC338. Thus modulation of transformed cell growth by TUC338 may involve binding to PAI-RBP1 as well as to sequence-defined cis-binding sites to modulate gene expression. These findings suggest that ultraconserved RNAs such as TUC338 can function in a manner analogous to transcription factors to modulate cell proliferation and transformed cell growth in HCC., Graphical Abstract

患者女，53岁。无明显诱因出现右腹部阵发性隐痛十余天，门诊以"消化道出血"收入院，腹部CT示右半结肠占位性病变，符合恶性肿瘤征象。结肠镜示升结肠近回盲部巨大隆起型肿物，占据3/4肠腔；镜下观察：肿瘤与黏膜上皮界限清晰，细胞呈上皮样，弥漫性实性分布，细胞核呈卵圆形，核大深染，核质比高，核仁清晰可见，胞质红染，核分裂象多见（约15/10 HPF）。免疫组织化学示Calretinin、WT-1、D2-40、CK5/6均阳性。诊断为结肠上皮样恶性间皮瘤。.

Extracellular vesicles are endogenous biological nanoparticles that have potential for use as therapeutic nanoparticles or as delivery vehicles for therapeutic agents. Milk nanovesicles (MNV) are extracellular vesicles isolated from bovine milk that have been explored for use as delivery vehicles for RNA therapeutics such as small interfering RNA (siRNA). We performed in vivo toxicological studies of MNV or therapeutic MNV (tMNV) loaded with siRNA as a prelude to their clinical use. Development toxicity was assessed in zebrafish embryos. Acute toxicity was assessed in both mice and zebrafish whereas safety, biochemical, histological and immune effects after multiple dosing were assessed in mice. Zebrafish embryo hatching was accelerated with MNV and tMNV. While acute toxicity or effects on mortality were not observed in zebrafish, developmental effects were observed at high concentrations of MNV. There was a lack of discernable toxicity, mortality and systemic inflammatory or immunological responses in mice following administration of either MNVs or tMNVs. The tolerability and lack of discernable developmental or systemic in vivo toxicity support their use as biological nano-therapeutics. Adoption of a standardized protocol for systematic analysis of in vivo safety and toxicity will facilitate preclinical assessment of EV based formulations for therapeutic use.

Extracellular vesicles (EVs) can be released from many different cell types and detected in most, if not all, body fluids. EVs can participate in cell-to-cell communication by shuttling bioactive molecules such as RNA or protein from one cell to another. Most studies of EVs have been performed in cell culture models or in EVs isolated from body fluids. There is emerging interest in the isolation of EVs from tissues to study their contribution to physiological processes and how they are altered in disease. The isolation of EVs with sufficient yield from tissues is technically challenging because of the need for tissue dissociation without cellular damage. This method describes a procedure for the isolation of EVs from mouse liver tissue. The method involves a two-step process starting with in situ collagenase digestion followed by differential ultra-centrifugation. Tissue perfusion using collagenase provides an advantage over mechanical cutting or homogenization of liver tissue due to its increased yield of obtained EVs. The use of this two-step process to isolate EVs from the liver will be useful for the study of tissue EVs.

By exploiting their biological functions, the use of biological nanoparticles such as extracellular vesicles can provide an efficient and effective approach for hepatic delivery of RNA‐based therapeutics for the treatment of liver cancers such as hepatocellular cancer (HCC). Targeting liver cancer stem cells (LCSC) within HCC provide an untapped opportunity to improve outcomes by enhancing therapeutic responses. Cells with tumor‐initiating capabilities such as LCSC can be identified by expression of markers such as epithelial cell adhesion molecule (EpCAM) on their cell surface. EpCAM is a target of Wnt/β‐catenin signaling, a fundamental pathway in stem‐cell growth. Moreover, mutations in the β‐catenin gene are frequently observed in HCC and can be associated with constitutive activation of the Wnt/β‐catenin pathway. However, targeting these pathways for the treatment of HCC has been challenging. Using RNA nanotechnology, we developed engineered biological nanoparticles capable of specific and effective delivery of RNA therapeutics targeting β‐catenin to LCSC. Extracellular vesicles isolated from milk were loaded with small interfering RNA to β‐catenin and decorated with RNA scaffolds to incorporate RNA aptamers capable of binding to EpCAM. Cellular uptake of these EpCAM‐targeting therapeutic milk‐derived nanovesicles in vitro resulted in loss of β‐catenin expression and decreased proliferation. The uptake and therapeutic efficacy of these engineered biological nanotherapeutics was demonstrated in vivo using tumor xenograft mouse models. Conclusion: β‐catenin can be targeted directly to control the proliferation of hepatic cancer stem cells using small interfering RNA delivered using target‐specific biological nanoparticles. Application of this RNA nanotechnology–based approach to engineer biological nanotherapeutics provides a platform for developing cell‐surface molecule–directed targeted therapeutics., By exploiting their biological functions, the use of biological nanoparticles such as extracellular vesicles can provide an efficient and effective approach for hepatic delivery of RNA‐based therapeutics for the treatment of hepatocellular cancer.

BackgroundLittle is known about long-term employment outcomes for patients with first-episode schizophrenia-spectrum (FES) disorders who received early intervention services.AimsWe compared the 10-year employment trajectory of patients with FES who received early intervention services with those who received standard care. Factors differentiating the employment trajectories were explored.MethodPatients with FES (N= 145) who received early intervention services in Hong Kong between 1 July 2001 and 30 June 2002 were matched with those who entered standard care 1 year previously. We used hierarchical clustering analysis to explore the 10-year employment clusters for both groups. We used the mixed model test to compare cluster memberships and piecewise regression analysis to compare the employment trajectories of the two groups.ResultsThere were significantly more patients who received the early intervention service in the good employment cluster (early intervention:N= 98 [67.6%]; standard care:N= 76 [52.4%];P= 0.009). In the poor employment cluster, there was a significant difference in the longitudinal pattern between early intervention and standard care for years 1–5 (P< 0.0001). The number of relapses during the first 3 years, months of full-time employment during the first year and years of education were significant in differentiating the clusters of the early intervention group.ConclusionsResults suggest there was an overall long-term benefit of early intervention services on employment. However, the benefit was not sustained for all patients. Personalisation of the duration of the early intervention service with a focus on relapse prevention and early vocational reintegration should be considered for service enhancement.

© 2019 Elsevier Inc. The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data. The Extracellular RNA Communication Consortium (ERCC) presents progress toward understanding the biology of extracellular RNAs and their use as biomarkers and therapeutics.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of ten exRNA isolation methods across five biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNAseq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle- (EV), ribonucleoprotein-(RNP)-, and high-density lipoprotein- (HDL) specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method, and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

Federated learning (FL) rests on the notion of training a global model in a decentralized manner. Under this setting, mobile devices perform computations on their local data before uploading the required updates to the central aggregator for improving the global model. However, a key challenge is to maintain communication efficiency (i.e., the number of communications per iteration) when participating clients implement uncoordinated computation strategy during aggregation of model parameters. We formulate a utility maximization problem to tackle this difficulty, and propose a novel crowdsourcing framework, involving a number of participating clients with local training data to leverage FL. We show the incentive-based interaction between the crowdsourcing platform and the participating client’s independent strategies for training a global learning model, where each side maximizes its own benefit. We formulate a two-stage Stackelberg game to analyze such scenario and find the game’s equilibria. Further, we illustrate the efficacy of our proposed framework with simulation results. Results show that the proposed mechanism outperforms the heuristic approach with up to 22% gain in the offered reward to attain a level of target accuracy.

The grand challenges of contemporary fundamental physics-dark matter, dark energy, vacuum energy, inflation and early universe cosmology, singularities and the hierarchy problem-all involve gravity as a key component. And of all gravitational phenomena, black holes stand out in their elegant simplicity, while harbouring some of the most remarkable predictions of General Relativity: event horizons, singularities and ergoregions. The hitherto invisible landscape of the gravitational Universe is being unveiled before our eyes: the historical direct detection of gravitational waves by the LIGO-Virgo collaboration marks the dawn of a new era of scientific exploration. Gravitational-wave astronomy will allow us to test models of black hole formation, growth and evolution, as well as models of gravitational-wave generation and propagation. It will provide evidence for event horizons and ergoregions, test the theory of General Relativity itself, and may reveal the existence of new fundamental fields. The synthesis of these results has the potential to radically reshape our understanding of the cosmos and of the laws of Nature. The purpose of this work is to present a concise, yet comprehensive overview of the state of the art in the relevant fields of research, summarize important open problems, and lay out a roadmap for future progress. This write-up is an initiative taken within the framework of the European Action on 'Black holes, Gravitational waves and Fundamental Physics'. © 2019 IOP Publishing Ltd.

In Hong Kong, compulsory admission is governed by the Mental Health Ordinance Section 31 (detention of a patient under observation), Section 32 (extension of period of detention for such a patient), Section 36 (detention of certified patients), and the sections in Part IV for hospital order, transfer order, and removal order. Mental health professionals adopt both legal criteria and practice criteria for compulsory admission. The present study discusses the harm principle, the patient's decision-making capacity, the multi-axial framework for compulsory admission, and the balance between paternalism and patient liberty.

Mainstream green has recently swept the construction industry throughout the world. Building envelope and material are two important aspects of green building evaluation. As the growing development of new green building concept “human-orientation design”, raw earth, as a natural, locally sourced, minimally processed, and recyclable material that is very different from concrete, becomes one of the most attractive options. Most architects pay attention to the aesthetic design of the raw earth wall, while other researchers like civil engineers focus on the physical properties of raw earth material itself. Few studies discussed the effect of the raw earth wall in building a thermal environment. This paper firstly conducts a parametric study on the thermal performance of raw earth wall with the consideration of thermophysical properties of materials, application of thermal insulation layer in the wall, and design parameters, i.e. thickness, of each layer of the wall. A naturally ventilated public building in Shanghai is then simulated to discuss the feasibility and the most optimum strategy of raw earth wall applications as building envelope in the sub-tropical high-density cities. Based on comprehensive data analysis, four findings are identified: (1) Compared with common building materials like concrete, raw earth materials have significant advantages in two thermophysical parameters - thermal transmittance and thermal effusivity which directly influence the indoor air temperature; (2) Thickness and structure of both raw earth layer and insulation layer are two important design parameters to meet the requirements of the indoor thermal environment; (3) Raw earth wall performs better than the standardized “Green Wall” based on local green building standards; (4) In terms of thermal performance, “Raw Earth Wall with External Insulation” is more suitable in subtropics. However, “Raw Earth Wall with Sandwich Insulation” is more recommended if pursuing the beauty of raw earth materials, because the thermal performances of “Raw Earth Wall with Sandwich Insulation” and Raw Earth Wall with External Insulation” are almost the same in summer, and very close in winter.

The concept of virtual water was first proposed by the geographer Tony Allan in 1993, referring to the amount of water needed to produce products and services. Research on virtual water has gradually increased in recent years. This paper explored the current research status of virtual water from the aspects of virtual water accounting methods, impact assessment, and research limitations and gaps. In terms of research methods, in addition to continuing to use traditional virtual water accounting methods, recent research also focuses on the use of input-output model to calculate virtual water content, the scenario analysis methods to predict future virtual water flow trends, and the gravitational model to analyze driving factors. The research content has also gradually diversified, from quantifying the virtual water content of commodities and analyzing virtual water flow paths, it has gradually evolved into “temporal and spatial evolution of virtual water trade, research combined with water footprint, virtual water and economic development, virtual water impact assessment, analysis of virtual water flow driving force” and other research content. The prediction and driving factors analysis of virtual water need further research; the availability and accuracy of data must be ensured. So virtual water research still needs to be improved and perfected. Virtual water research is an interdisciplinary discipline involving hydrology, socio-economy, and the ecological environment, so future research should be conducted in conjunction with relevant knowledge in other disciplines. And researching the impacts of virtual water trade on the formulation of regional trade policies and the regional ecological environment will provide a powerful reference for policy makers on the adjustment of regional trade patterns and management of water resources. This paper can provide reference for virtual water researchers.

Extracellular vesicles (EVs) are membrane-bound vesicles released from cells into the extracellular environment. There is emerging interest in the use of EVs as potential therapeutic interventions. We sought to evaluate the safety of EVs that may be therapeutically used by performing in vitro toxicological assessments. EVs were obtained from mesenchymal stem cells (MSC-EV) or from bovine milk (BM-EV) by differential ultracentrifugation, and quantitated using nanoparticle tracking analysis. Genotoxic effects, hematological effects, immunological effects and endotoxin production were evaluated at two dose levels. Neither MSC-EVs nor BM-EVs elicited detectable genotoxic effects using either the alkaline comet assay or micronucleus assay. Hemolysis was observed with BM-EVs but not with MSC-EVs. MSC-EVs did not have any significant effect on either spontaneous or collagen-induced platelet aggregation. In contrast, BM-EVs were noted to increase collagen-induced platelet aggregation, even though no spontaneous increase in platelet aggregation was noted. Both types of EVs induced leukocyte proliferation, which was greater with BM-EV. Neither MSC-EVs nor BM-EVs induced HL-60 phagocytosis, although BM-EVs decreased zymosan-induced phagocytosis. Furthermore, neither MSC-EVs nor BM-EVs induced nitric oxide production. Unlike MSC-EVs, BM-EVs tested positive for endotoxin and induced complement activation. There are significant differences in toxicological profiles between MSC-EVs and BM-EVs that may reflect variations in techniques for EV isolation, EV content or cross-species differences. The safety of MSC-EV supports their use for disease therapeutics, whereas detailed safety and toxicological assessment will be necessary before the use of BM-EVs. Copyright © 2016 John Wiley & Sons, Ltd.

Trophopods are modified stipe bases that function as starch-storage organs in a wide variety of mainly temperate ferns. Ever since they were first observed, the presence of trophopods has been explained by reference to seasonality and they have been assumed to provide nutrition for the rapidly expanding fern leaves in spring. We present the results of an analysis of the annual variation in starch content in Matteuccia struthiopteris (L.) Todaro, cultivated in the Leiden botanical garden. Our results show a distinct seasonal variation in starch content, suggesting that the presence of trophopods is indeed functionally linked to seasonality, but we do not find a decrease in starch content corresponding to the period of leaf expansion that would clearly link the depletion of stored starch to the expansion of new leaves.

The recognition of functional roles for transcribed long non-coding RNA (lncRNA) has provided a new dimension to our understanding of cellular physiology and disease pathogenesis. LncRNAs are a large group of structurally complex RNA genes that can interact with DNA, RNA, or protein molecules to modulate gene expression and to exert cellular effects through diverse mechanisms. The emerging knowledge regarding their functional roles and their aberrant expression in disease states emphasizes the potential for lncRNA to serve as targets for therapeutic intervention. In this concise review, we outline the mechanisms of action of lncRNAs, their functional cellular roles, and their involvement in disease. Using liver cancer as an example, we provide an overview of the emerging opportunities and potential approaches to target lncRNA-dependent mechanisms for therapeutic purposes.

With improvement in mineral processing, column flotation technology has undergone enormous changes, and various flotation columns have emerged in large numbers. In this study, three types of laboratory-scale flotation columns, including countercurrent, cyclone, and jet flow, were designed, and their bubble sizes were measured by using an image-analysis technique. The effect of circulating rates on bubble distribution was discussed. The bubble sizes decreased as the circulating rate increased. The bubble diameters in the countercurrent and jet flow mineralization environments were the maximum and minimum, respectively, when the circulating rate was the same.

In order to improve the level of line loss management and realize the importance of lean management of municipal power grid enterprises, the method of lean line loss management is proposed, which aims at the current situation of the comprehensive evaluation of line loss management in the municipal power grid enterprises. Constructing multi evaluation sequence information matrix, we optimize the singular value of the network to solve the inconsistent problem of the current line loss management evaluation conclusion and accurately measure the level of municipal power grid. To address the problem of line loss management, we find out the weakness of it, and guide the management construction through analysis. Finally, we evaluate the line loss management level of 61 enterprises of municipal power grid, and illustrate that the proposed method can effectively guide line loss management and achieve lean management of line loss.

With the increasing penetration of renewable energy and the increasing uncertainty, the reactive power optimization of islanded microgrids face increasingly severe challenges. According to the topological structure of the meshed islanded microgrids, the power flow model is convex into a two order cone power flow model. Considering the uncertainties of PV active power and PV inverter reactive power, we establish an adjustable robust reactive power optimization model. Based on the strong duality theorem, the uncertainties in the robust model are eliminated and solved by linear robust optimization. Finally, we use the IEEE 33-bus system to simulated and tested reactive power optimization model which propose in this paper. The results show the robust optimization model still has good robustness after reducing the conservatism. It can ensure the stable operation of the system.

Radiomics is a newly emerging field that involves the extraction of a large number of quantitative features from biomedical images through the use of data-characterization algorithms. Radiomics provides a noninvasive approach for personalized therapy decision by identifying distinctive imaging features for predicting prognosis and therapeutic response. So far, many of the published radiomics studies utilize existing out of the box algorithms to identify the prognostic markers from biomedical images that are not specific to radiomics data. T o better utilize biomedical image, we propose a novel machine learning approach, stability selection supervised principal component analysis (SSSuperPCA) that identify a set of stable features from radiomics big data coupled with dimension reduction for right censored survival outcomes. In this paper, we describe stability selection supervised principal component analysis for radiomics data with right-censored survival outcomes. The proposed approach allows us to identify a set of stable features that are highly associated with the survival outcomes, control the per-family error rate, and predict the survival in a simple yet meaningful manner. We evaluate the performance of SSSuperPCA using simulations and real data sets for non-small cell lung cancer and head and neck cancer, and compare it with other machine learning algorithms. The results demonstrate that our method has a competitive edge over other existing methods in identifying the prognostic markers from biomedical big imaging data for the prediction of right-censored survival outcomes. An R package SSSuperPCA is available at the website: http://web.hku.hk/∼herbpang/SSSuperPCA.html

No Abstract available

Cell-to-cell communication involves the release of biological molecules into the extracellular space and their uptake by recipient cells. These molecules include RNA that can modulate cellular signaling and biological processes. To study extracellular RNA, highly sensitive and precise methods for their detection are needed. Digital polymerase chain reaction (dPCR) can be a useful method for detecting and analyzing extracellular RNA. The sensitivity of digital PCR can exceed that of quantitative PCR for low abundance targets such as extracellular RNA.

The study of extracellular RNA has been recently reported as a tool for biomarker discovery. Extracellular vesicles can be isolated from different types of body fluids which contain protein, mRNA, and noncoding RNA. Extracellular RNA isolated from bile could be a useful tool for analyzing biliary tract diseases or cancer. Herein, we describe protocols based on modifications of commercially available kits for the collection, processing, and isolation of extracellular RNA from bile.

Several different types of RNA molecules such as microRNAs (miRNAs) have been detected within extracellular vesicles in the circulation. The detection and potential utility of these as disease biomarkers requires the ability to detect their presence with adequate sensitivity and to quantitate their expression. The potential for circulating miRNA to serve as biomarkers can be evaluated through their detection in association with specific disease states. Multiplexed detection of several miRNA simultaneously can be useful for discovery studies. We describe the analysis of miRNA from biological fluids like plasma and serum using the Nanostring nCounter platform. Assays can be used to quantitate the expression of miRNA using direct detection based on hybridization to target specific color-coded probes followed by counting each color-coded barcode digitally.

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer related death worldwide. Although HCC can respond to immune checkpoint inhibitors such as monoclonal antibodies against PD-1, many patients fail to respond or develop secondary resistance. Activation of Wnt/β-catenin signaling can contribute to immune evasion. Mutations in β-catenin are amongst the most frequent mutations associated with HCC. Thus, our aim was to directly target β-catenin to enhance the therapeutic response to immune checkpoint inhibition. Methods: A synthetic transgenic mouse of experimental HCC induced by MET/ β-catenin expression, and extracellular vesicles as a therapeutic delivery agent were used to evaluate the efficacy of directly targeting β-catenin on response to anti-PD-1. Findings: These studies show that (1) oncogenic β-catenin could be therapeutically targeted using a biological nanoparticle based delivery approach, (2) targeting β-catenin using siRNA delivered within extracellular vesicles can reduce tumor growth, and (3) the therapeutic response to anti-PD-1 can be enhanced by concomitantly targeting β-catenin using therapeutic extracellular vesicles. These preclinical studies establish the efficacy of use of biological nanoparticles as an endogenous delivery vehicle for therapeutic RNA delivery and support the use of therapeutic strategies targeting tumor-intrinsic β-catenin as an adjunct to anti-PD-1 based therapy. Interpretation: Combination therapy with anti PD-1 and β-catenin siRNA delivered using biological nanoparticles provide an effective strategy for the treatment of HCC. This strategy could be further exploited into targeted approaches for immune potentiation by countering oncogenemediated resistance to immunotherapies. Funding Statement: Supported in part by the National Institutes of Health.TP is funded by NIH (UH3-TR000884). This publication is part of the NIH Extracellular RNA Communication Consortium paper package and was supported by the NIH Common Fund's exRNA Communication Program Declaration of Interests: There are no conflicts for any of the authors related to design, execution or analysis of the experiments presented in this manuscript. Ethics Approval Statement: All studies involving animals were performed in accordance with protocols approved by the Mayo Clinic Institutional Animal Care and Use committee.

Cell-to-cell communication involves the release of biological molecules into the extracellular space and their uptake by recipient cells. These molecules include RNA that can modulate cellular signaling and biological processes. To study extracellular RNA, highly sensitive and precise methods for their detection are needed. Digital polymerase chain reaction (dPCR) can be a useful method for detecting and analyzing extracellular RNA. The sensitivity of digital PCR can exceed that of quantitative PCR for low abundance targets such as extracellular RNA.

Current approaches for collection of extracellular vesicles (EV) are based on classical cell culture media production. This involves collection from cells grown in flasks, and can require multiple rounds of centrifugation or filtration, followed by ultracentrifugation or density gradient centrifugation. There are several limitations of these approaches, for example, they require a large input volume, the yield and concentration is low, and the process is time consuming. Most cell cultures require the use of fetal bovine serum which contains a large amount of endogenous EV that can contaminate isolations of cell-derived EVs. The use of cell cultures within a hollow fiber bioreactor could address many of these limitations and produce a continuous source of highly concentrated EVs without contamination from serum EVs, and that are suitable for downstream applications.