A Genetic Algorithm for Universal Optimization of Ultrasensitive Surface Plasmon Resonance Sensors with 2D Materials

We present a general optimization technique for surface plasmon resonance, (SPR) yielding a range of ultrasensitive SPR sensors from a materials database with an enhancement of ∼100%. Applying the algorithm, we propose and demonstrate a novel dual-mode SPR structure coupling SPP and a waveguide mode within GeO₂ featuring an anticrossing behavior and an unprecedented sensitivity of 1364 deg/RIU. An SPR sensor operating at wavelengths of 633 nm having a bimetal Al/Ag structure sandwiched between hBN can achieve a sensitivity of 578 deg/RIU. For a wavelength of 785 nm, we optimized a sensor as a Ag layer sandwiched between hBN/MoS₂/hBN heterostructures achieving a sensitivity of 676 deg/RIU. Our work provides a guideline and general technique for the design and optimization of high sensitivity SPR sensors for various sensing applications in the future

ニホンゴ フクゴウ ドウシ V1 コム ノ タギコウゾウ ニ カンスル ニンチ ゲンゴガク テキ ケンキュウ

“V1 ＋込む”作为词汇型复合动词，其结合规则却并不符合影山（1993）所提出的“他动性调和原则”，可与“～込む”结合的前项动词高达200 多个，是词汇型复合动词之最。另外我们发现，“～込む”与其前项动词之间包含了“手段型”（投げ込む）、“样态型”（流れ込む）、“V2 补助型”（老け込む）等多种语义关系。基于其语义关系的复杂性与多样性，在日语教学方面，如何把握复合动词“V1 ＋込む”的多义结构成为一大难点。本文试图从认知语言学的角度出发阐明以下三个问题。a. “ V1 ＋込む”的前项动词具有怎样的词义特征？其与后项动词“～込む”之间又有怎样的语义关系？b. 如何把握“V1 ＋込む”的语义扩张机制？c. 如何构建“V1 ＋込む”的多义结构？首先，基于前后项动词的语义关系，本文将“V1 ＋込む”的语义分为“向某领域的内部移动，并固着”（类型1），“充分行使V1 所表示的行为”（类型2），“V1 所指状态的程度深，激烈”（类型3）三大类。类型1 的前项动词多为动作性动词，类型2 的前项动词可分为“由量变易引起质变的动词”和“由量变不易引起质变的动词”两类，类型3 的前项动词多为安定的状态性动词，具有未完了动词的性质特征。以往研究指出，类型1 在使用中隐含有特殊语感，但对其产生的理由并未给予解释。本文认为，对于 “V1 ＋込む”语义特征的深层次阐释离不开“容器”这一建立于身体经验之上的意象图式。基于“容器图式”的性质及“固着”这一语义要素我们分析发现，某容器内部要达到“固着”这一“结果状态”，除了“向某领域的内部移动”之外，还需“移动物数量大”，“时间长”，“向容器深处移动”，“内部移动行为伴随某种意图”，中至少1 种要素的介入。此发现可对“V1＋込む”隐含特殊语感的原因进行解释说明。再次我们认为，类型1 为原型语义，类型2、3 为其扩张语义。其中，类型1 至类型2的扩张与语用强化密切关联。类型1 和类型3 之间存在［CHANGES ARE MOVEMENTS］这一概念性隐喻。此外我们发现，“～込む”所对应的本动词为古语“こむ”，背后潜藏着自动词，他动词两种语义。基于此发现，我们认为类型1 为“空间浓密状态”，类型2 为“行为浓密状态”，类型3 为“抽象浓密状态”，从而将“V1 ＋込む”的超级上位语义定义为“达到某种浓密状态”。基于以上三种语义类型之间的水平关联性以及与超级上位语义之间的垂直关联性，本文利用Langacker（1991）所提出的多义网络模型搭建出了“V1 ＋込む”的多义结构体系

A market decision-making model for load aggregators with flexible load

The fast development of renewable energy has resulted in great challenges to the power system, which urgently needs more flexible resources to maintain a system supply/demand balance. This paper established a multi-stage electricity market framework in the presence of a load aggregator (LA) including a day-ahead energy/reserve market and a real-time balanced market. To actively participate in the day-ahead energy market and reserve market, a load profile perception model for LA is proposed to evaluate in detail the response performance of consumers. Meanwhile, a market-bidding model of LA and a market-clearing model of the system operator for the day-ahead market are also established. To actively join the real-time balance market, a market-bidding model of LA for the real-time balance market based on surplus flexible resources is established. The system operator further clears the real-time balance market and dispatches the collected flexible resources according to the system supply-demand state. A modified IEEE 30 bus system is tested and shows that the proposed market framework can effectively promote consumers to respond to system regulation requirements and lowers the system supply-demand imbalance risk

Rv1985c, a promising novel antigen for diagnosis of tuberculosis infection from BCG-vaccinated controls

<p>Abstract</p> <p>Background</p> <p>Antigens encoded in the region of difference (RD) of <it>Mycobacterium tuberculosis </it>constitute a potential source of specific antigens for immunodiagnosis. In the present study, recombinant protein Rv1985c from RD2 was cloned, expressed, purified, immunologically characterized and investigated for its potentially diagnostic value for tuberculosis (TB) infection among BCG-vaccinated individuals.</p> <p>Methods</p> <p>T-cell response to Rv1985c was evaluated by IFN-γ ELISPOT in 56 TB patients, 20 latent TB infection (LTBI) and 30 BCG-vaccinated controls in comparison with the commercial T-SPOT. <it>TB </it>kit. Humoral response was evaluated by ELISA in 117 TB patients, 45 LTBI and 67 BCG-vaccinated controls, including all those who had T-cell assay, in comparison with a commercial IgG kit.</p> <p>Results</p> <p>Rv1985c was specifically recognized by cellular and humoral responses from both TB and LTBI groups compared with healthy controls. Rv1985c IgG-ELISA achieved 52% and 62% sensitivity respectively, which outperformed the sensitivity of PATHOZYME-MYCO kit (34%) in detecting active TB (P = 0.011), whereas IFN-γ Rv1985c-ELISPOT achieved 71% and 55% sensitivity in detecting active and LTBI, respectively. Addition of Rv1985c increased sensitivities of ESAT-6, CFP-10 and ESAT-6/CFP-10 combination in detecting TB from 82.1% to 89.2% (P = 0.125), 67.9% to 87.5% (P < 0.001) and 85.7% to 92.9% (P = 0.125), respectively.</p> <p>Conclusions</p> <p>In conclusion, Rv1985c is a novel antigen which can be used to immunologically diagnose TB infection along with other immunodominant antigens among BCG-vaccinated population.</p

Interferon-γ Regulates Cellular Metabolism and mRNA Translation to Potentiate Macrophage Activation

Interferon-γ (IFN-γ) primes macrophages for enhanced inflammatory activation by Toll-like receptors (TLRs) and microbial killing, but little is known about the regulation of cell metabolism or mRNA translation during priming. We found that IFN-γ regulates human macrophage metabolism and translation by targeting the kinases mTORC1 and MNK that both converge on the selective regulator of translation initiation eIF4E. Physiological downregulation of mTORC1 by IFN-γ was associated with autophagy and translational suppression of repressors of inflammation such as HES1. Genome-wide ribosome profiling in TLR2-stimulated macrophages revealed that IFN-γ selectively modulates the macrophage translatome to promote inflammation, further reprogram metabolic pathways, and modulate protein synthesis. These results add IFN-γ-mediated metabolic reprogramming and translational regulation as key components of classical inflammatory macrophage activation

Multiplatform genome-wide identification and modeling of functional human estrogen receptor binding sites

BACKGROUND: Transcription factor binding sites (TFBS) impart specificity to cellular transcriptional responses and have largely been defined by consensus motifs derived from a handful of validated sites. The low specificity of the computational predictions of TFBSs has been attributed to ubiquity of the motifs and the relaxed sequence requirements for binding. We posited that the inadequacy is due to limited input of empirically verified sites, and demonstrated a multiplatform approach to constructing a robust model. RESULTS: Using the TFBS for the estrogen receptor (ER)α (estrogen response element [ERE]) as a model system, we extracted EREs from multiple molecular and genomic platforms whose binding to ERα has been experimentally confirmed or rejected. In silico analyses revealed significant sequence information flanking the standard binding consensus, discriminating ERE-like sequences that bind ERα from those that are nonbinders. We extended the ERE consensus by three bases, bearing a terminal G at the third position 3' and an initiator C at the third position 5', which were further validated using surface plasmon resonance spectroscopy. Our functional human ERE prediction algorithm (h-ERE) outperformed existing predictive algorithms and produced fewer than 5% false negatives upon experimental validation. CONCLUSION: Building upon a larger experimentally validated ERE set, the h-ERE algorithm is able to demarcate better the universe of ERE-like sequences that are potential ER binders. Only 14% of the predicted optimal binding sites were utilized under the experimental conditions employed, pointing to other selective criteria not related to EREs. Other factors, in addition to primary nucleotide sequence, will ultimately determine binding site selection

Genome Wide Identification and Expression Profiling of Ethylene Receptor Genes during Soybean Nodulation

It has long been known that the gaseous plant hormone ethylene plays a key role in nodulation in legumes. The perception of ethylene by a family of five membrane-localized receptors is necessary to trigger the ethylene signaling pathway, which regulates various biological responses in Arabidopsis. However, a systematic analysis of the ethylene receptors in leguminous plants and their roles in nodule development is lacking. In this study, we performed a characterization of ethylene receptor genes based on the latest Glycine max genome sequence and a public microarray database. Eleven ethylene receptor family genes were identified in soybean through homology searches, and they were divided into two subgroups. Exon–intron analysis showed that the gene structures are highly conserved within each group. Further analysis of their expression patterns showed that these ethylene receptor genes are differentially expressed in various soybean tissues and organs, including functional nodules. Notably, the ethylene receptor genes showed different responses to rhizobial infection and Nod factors, suggesting a possible role for ethylene receptors and ethylene signaling in rhizobia–host cell interactions and nodulation in soybean. Together, these data indicate the functional divergence of ethylene receptor genes in soybean, and that some of these receptors mediate nodulation, including rhizobial infection, nodule development, and nodule functionality. These findings provide a foundation for further elucidation of the molecular mechanism by which the ethylene signaling pathway regulates nodulation in soybean, as well as other legumes

A Gamma Interferon Independent Mechanism of CD4 T Cell Mediated Control of M. tuberculosis Infection in vivo

CD4 T cell deficiency or defective IFNγ signaling render humans and mice highly susceptible to Mycobacterium tuberculosis (Mtb) infection. The prevailing model is that Th1 CD4 T cells produce IFNγ to activate bactericidal effector mechanisms of infected macrophages. Here we test this model by directly interrogating the effector functions of Th1 CD4 T cells required to control Mtb in vivo. While Th1 CD4 T cells specific for the Mtb antigen ESAT-6 restrict in vivo Mtb growth, this inhibition is independent of IFNγ or TNF and does not require the perforin or FAS effector pathways. Adoptive transfer of Th17 CD4 T cells specific for ESAT-6 partially inhibited Mtb growth while Th2 CD4 T cells were largely ineffective. These results imply a previously unrecognized IFNγ/TNF independent pathway that efficiently controls Mtb and suggest that optimization of this alternative effector function may provide new therapeutic avenues to combat Mtb through vaccination

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead