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Ammonia, with high energy density and easy transportation, holds significant potential to become an integral part of future energy systems. Among tremendous strategies, electrocatalytic ammonia production is no doubt an efficient and eco-friendly method. One particularly intriguing class of electrocatalysts for reducing nitrate to ammonia is transition metal oxides, which have been heavily researched. However, how these catalysts’ oxygen vacancy (VO) affects their performance remains elusive. To address this, taking titania (the most important catalyst) as an example, we carried out experimental investigations and simulations. Contrary to the prevailing belief that the concentrated VOwould increase the catalytic efficiency of nitrate reduction, it was found that a relatively low level of VOis favorable for maximizing catalytic efficiency. At low cathodic voltages, titania with minimal VOdelivered both the highest reduction efficiency and the best selectivity among the different titania samples in this paper. In addition to outlining the merits of lower electron transfer resistance and accelerated reaction dynamics, we also put forth a previously unmentioned factor, the adsorption of hydrogen or the creation of an ordered hydrogen bond network, which put up a hydrogen-rich atmosphere for following nitrate reduction. Further simulation study revealed that within the hydrogen-rich atmosphere isolated VOserves as the ideal active center to enable the lowest energy barriers for the reduction of nitrate into ammonia. These findings offer fresh insights into the working mechanism of oxide-based electrocatalysts for ammonia production.

Atomically thin platinum diselenide (PtSe2) films are promising for applications in the fields of electronics, spintronics, and photodetectors owing to their tunable electronic structure and high carrier mobility. Using terahertz (THz) spectroscopy techniques, we investigated the layer-dependent semiconducting-to-metallic phase transition and associated intrinsic carrier dynamics in large-scale PtSe2films grown by molecular beam epitaxy. The uniformity of large-scale PtSe2films was characterized by spatially and frequency-resolved THz-based sheet conductivity mapping. Furthermore, we use an optical-pump-THz-probe technique to study the transport dynamics of photoexcited carriers and explore light-induced intergrain carrier transport in PtSe2films. We demonstrate large-scale THz-based mapping of the electrical properties of transition metal dichalcogenide films and show that the two noncontact THz-based approaches provide insight in the spatial and temporal properties of PtSe2films.

Recent years have witnessed rapid advances in autonomous driving technologies. Autonomous vehicles are more likely to be accepted if they drive comfortably to avoid potholes, bumps, and other road damage conditions, especially when there are elderly and disabled passengers on board. Traditionally, sensing road damage conditions is either labor-intensive by field investigation and reporting, or inaccurate by surveillance cameras and driving recorders due to limited perspective. In this paper, we propose GoComfort, a crowdsensing-based framework to provide low-cost and fine-grained comfortable navigation for autonomous vehicles with road damage identification leveraging high-precision road sensing data. First, we propose to exploit city-wide autonomous vehicle fleets as crowdsensing participants, and employ an edge-cloud-hybrid computing paradigm to efficiently collect high-precision road damage-related data, including 3D LiDAR point clouds and street view images. Second, we design an accurate road damage identification model fusing spatial structures of point clouds and texture features of street view images, and use an active learning-based method to address the sparse labels issue. Finally, we devise two comfortable navigation scenarios, i.e., fine-grained road damage avoidance and coarse-grained city-wide navigation, and propose a hierarchical road damage assessment diagram for comfortable route planning. Experiments using real-world road sensing data in Xiamen, China show that our approach identifies road damage conditions with an accuracy of 87.5%, and achieves a user acceptance rate of 93.8% in riding comfort evaluation, outperforming the state-of-the-art baselines.

Ultrasensitive sensing to trace atomic and molecular analytes has gained interest for its intimate relation to industrial sectors and human lives. One of the keys to ultrasensitive sensing for many analytical techniques lies in enriching trace analytes onto well-designed substrates. However, the coffee ring effect, nonuniform distribution of analytes onto substrates, in the droplet drying process hinders the ultrasensitive and stable sensing onto the substrates. Here, we propose a substrate-free strategy to suppress the coffee ring effect, enrich analytes, and self-assemble a signal-amplifying (SA) platform for multimode laser sensing. The strategy involves acoustically levitating and drying a droplet, mixed with analytes and core–shell Au@SiO2nanoparticles, to self-assemble an SA platform. The SA platform with a plasmonic nanostructure can dramatically enrich analytes, enabling enormous spectroscopic signal amplification. Specifically, the SA platform can promote atomic detection (cadmium and chromium) to the 10–3mg/L level by nanoparticle-enhanced laser-induced breakdown spectroscopy and can promote molecule detection (rhodamine 6G) to the 10–11mol/L level by surface-enhanced Raman scattering. All in all, the SA platform, self-assembled by acoustic levitation, can intrinsically suppress the coffee ring effect and enrich trace analytes, enabling ultrasensitive multimode laser sensing.

A method of green chemistry approach to synthesize copper oxide nanoparticles (CuONPs) was reported using extracts from the root, stem, and leaves of the Macleaya cordata(Wild.) R.BR as reducing and stabilizing agents. Copper acetate precursor (Cu(CH3COO)2) was used for green synthesis of copper oxide nanoparticles through reduction and oxidation reactions. The synthesized CuONPs were characterized using UV-Vis, XRD, FTIR, SEM, TEM, zeta potential, and energy-dispersive X-ray spectroscopy (EDS). The results of these analyses provided valuable insights into the structure, shape, functional groups, and elemental composition of the synthesized CuONPs. The antibacterial activity of the green synthesized CuONPs was evaluated using an agar diffusion assay. The result shows that the inhibition effect was concentration-dependent, and at the highest concentration (5 mg/mL), the CuONPs exhibited strong antibacterial activity against Escherichia coliand Staphylococcus aureus, with inhibition zones of 21 mm and 23 mm, respectively. The photocatalytic degradation of methylene blue (MB) at a concentration of 10 mg/mL by CuONPs (10 mg/mL) was evaluated using a photochemical reaction apparatus under simulated natural light. The degradation rate was found to be 65% within 3 h and 93% after 24 h. The degradation rate of higher concentrations of MB (100 mg/mL) was 47.9%. These results indicate that the synthesized CuONPs have great potential for rapidly breaking down textile dyes and exhibit exceptional antibacterial properties. This suggests that these nanoparticles could play a significant role in the development of sustainable nanotechnology.

Traffic violations have become one of the major threats to urban transportation systems, undermining human safety and causing economic losses. To alleviate this problem, crowd-based patrol forces including traffic police and voluntary participants have been employed in many cities. To adaptively optimize patrol routes with limited manpower, it is essential to be aware of traffic violation hotspots. Traditionally, traffic violation hotspots are directly inferred from experience, and existing patrol routes are usually fixed. In this paper, we propose a mobile crowdsensing-based framework to dynamically infer traffic violation hotspots and adaptively schedule crowd patrol routes. Specifically, we first extract traffic violation-prone locations from heterogeneous crowd-sensed data and propose a spatiotemporal context-aware self-adaptive learning model (CSTA) to infer traffic violation hotspots. Then, we propose a tensor-based integer linear problem modeling method (TILP) to adaptively find optimal patrol routes under human labor constraints. Experiments on real-world data from two Chinese cities (Xiamen and Chengdu) show that our approach accurately infers traffic violation hotspots with F1-scores above 90% in both cities, and generates patrol routes with relative coverage ratios above 85%, significantly outperforming baseline methods.

AbstractThis study investigated the effects of different doses of rutin on the growth performance, immunity, intestinal barrier, and antioxidant capacity of broilers. A total of two hundred and fifty-six 1-day-old male broilers were divided into 4 groups and fed basal diets supplemented with 0 (control group), 250, 500 and 1,000 mg rutin/kg, respectively, for 42 days. In the starter period (days 1–21) and whole trial period (days 1–42), broilers fed diets containing 500 mg rutin/kg had significantly (p < 0.05) higher average daily feed intake, body weight and average daily gain and better feed conversion ratio. Dietary 500 mg rutin/kg increased the villus height, villus height to crypt depth ratio and villus area, while reducing the B cell lymphoma 2 associated X mRNA expression (p < 0.05). Dietary 500 mg rutin/kg increased the level of IgA in serum and decreased serum tumour necrosis factor-α (TNF-α) content, and the nuclear factor kappa-B, interleukin-2 and TNF-α mRNA expression in jejunal mucosa (p < 0.05). Simultaneously, 500 and 1,000 mg rutin/kg significantly decreased serum diamine oxidase activity, D-lactic acid and lipopolysaccharide concentration, increased activities of total superoxide dismutase and total antioxidant capacity in jejunal mucosa (p < 0.05), and upregulated mRNA expressions of genes related to intestinal barrier and antioxidant capacity in jejunal mucosa (p < 0.05). These findings indicate that dietary rutin, especially at 500 mg/kg, improves broilers’ growth performance, intestinal barrier function, immunity, and antioxidant capability, which may be related to the nuclear factor erythroid-2-related factor 2 (Nrf2) pathway.HighlightsDietary rutin improved growth performance, jejunal morphology, and intestinal barrier function.Dietary rutin enhanced the immunity via inhibiting NF-κB, and improved antioxidant capacity via activating Nrf2/HO-1 pathway in broilers.The optimal dose of rutin was 500 mg/kg in broiler diet.

AbstractDietary zinc oxide nanoparticle (ZnO NP) possessing multiple biological activities might be a potential substitute for the combination of ZnSO4and antibiotic growth promoter in broiler diets. Therefore, this study was conducted to investigate the efficacy of dietary ZnO NP as a substitute to the combination of ZnSO4and xanthomycin for growth, antioxidant capacity, immunity, intestinal barrier and liver function in broilers. Arbor Acres chicks (n = 320) were assigned to 5 treatments with 8 replicates. Birds received a basal diet supplemented with 80 mg/kg ZnSO4plus 5 mg/kg xanthomycin (ZnSO4 + Xanthomycin) or 0 (negative control, NC), 40, 80, and 160 mg/kg ZnO NP for 42 days. The average daily gain, average daily feed intake and feed-to-gain ratio showed dose-dependent increases with the increasing level of dietary ZnO NP during the 21–42 day and 1–42 day stages. The final body weight (42 d) and serum concentrations of insulin-like growth factor 1 and growth hormone increased linearly with the increasing level of dietary ZnO NP. In addition, 80 mg/kg ZnO NP increased the serum concentrations of IgA, IgG, IgM, andinterleukin-10 and peroxidase activity, the jejunal mucosal villus height, villus width and goblet cell numbers. Dietary 80 or 160 mg/kg ZnO NP significantly altered mRNA abundances of genes related to antioxidant status, intestinal barrier and immunity in the jejunal mucosa. These results indicated that dietary supplementation with 40–160 mg/kg ZnO NP caused no obvious negative effects on liver function, but effectively improved growth performance, intestinal barrier function, immunity and antioxidant capacity.HighlightsDietary 40–160 mg/kg zinc oxide nanoparticle (ZnO NP) improved growth performance and enhanced immunity of broilers without obvious negative effects on liver function.Dietary 40–160 mg/kg ZnO NP improved intestinal barrier and intestinal morphology, and enhanced antioxidant capacity via Nrf2/HO-1 pathway.Doses of 40–80 mg/kg ZnO NP were suggested to alternate the combination of 80 mg/kg ZnSO4and 5 mg/kg xanthomycin in diets of broilers.

Traffic violations have become one of the major threats to urban transportation systems, undermining road safety and causing economic losses. Although various methods have been proposed by road authorities and researchers to find out the possible causes of traffic violations, existing methods often fail to diagnose traffic violations from drivers’ perspectives and contexts or consider their visual and comprehension loads while driving. In this work, we propose a driver-centered simulation platform to inspect drivers’ loads in traffic violation hotspots. Specifically, we first build a driving simulator based on the 3D point clouds of real-world traffic violation hotspots. We then recruit drivers to simulate driving in designated traffic scenes. Indicators for drivers’ visual and comprehension loads are derived based on drivers’ feedback. Upon this basis, we build an explainable model to automatically indicate drivers’ visual and comprehension loads under various crowd-sensed traffic scenes. Experiments using real-world data from a Chinese City (Xiamen) and case studies show that our approach successfully derives a set of prominent indicators to effectively diagnose drivers’ visual and comprehension loads in real-world traffic violation hotspots.

Graphical Abstract:

One of the challenges for metasurface research is upscaling. The conventional methods for fabrication of metasurfaces, such as electron-beam or focused ion beam lithography, are not scalable. The use of ultraviolet steppers or nanoimprinting still requires large-size masks or stamps, which are costly and challenging in further handling. This work demonstrates a cost-effective and lithography-free method for printing optical metasurfaces. It is based on resonant absorption of laser light in an optical cavity formed by a multilayer structure of ultrathin metal and dielectric coatings. A nearly perfect light absorption is obtained via interferometric control of absorption and operating around a critical coupling condition. Controlled by the laser power, the surface undergoes a structural transition from random, semiperiodic, and periodic to amorphous patterns with nanoscale precision. The reliability, upscaling, and subwavelength resolution of this approach are demonstrated by realizing metasurfaces for structural colors, optical holograms, and diffractive optical elements.

With the continuous evolution of wearable and mobile devices, flexible electronics, and intelligent thermal management, there is a growing interest in thermal interface materials (TIMs) that combine high thermal conductivity with low modulus for stretchability. However, materials with high thermal conductivity often come with elevated Young's modulus. Here, we have developed a TIMs by combining liquid metal and BN with polydimethylsiloxane (PDMS), achieving a blend of low modulus and high thermal conductivity. To enhance thermal conductivity, we introduced boron nitride sheets as “scalpel”, puncturing the oxide layer of the liquid metal under pressure to establish a continuous thermal path. After pressure induction, the LM-BN/PDMS composite exhibits a thermal conductivity of 4.3 W/(m K), with a Young's modulus of only 193 kPa and a fracture strain of 483%. Furthermore, it demonstrates outstanding thermal stability under multiple thermal shock cycles, indicating significant potential for applications in future thermal management for flexible electronic devices, wearable devices, and beyond.

BackgroundGGC repeat expansion in NOTCH2NLChas been recently linked to neuronal intranuclear inclusion disease (NIID) via unknown disease mechanisms. Herein, we explore the genetic origin of the sporadic cases and toxic RNA gain-of-function mechanism in NIID.MethodsMultiple genetic screenings were performed on NIID individuals and their available family members. Methylation status of blood DNA, NOTCH2NLC mRNA level from muscle biopsies and RNA foci from skin biopsies of NIID individuals or asymptomatic carriers were evaluated and compared.ResultsIn two sporadic NIID families, we identified two clinically and pathologically asymptomatic fathers carrying large GGC repeat expansion, above 300 repeats, with offspring repeat numbers of 172 and 148, respectively. Further evaluation revealed that the GGC repeat numbers in the sperm from two asymptomatic fathers were only 63 and 98, respectively. The CpG island in NOTCH2NLCof the asymptomatic carriers was hypermethylated, and accordingly, the NOTCH2NLC mRNA levels were decreased in the asymptomatic fathers. GGC repeat expansion RNA formed RNA foci and sequestered RNA binding proteins into p62 positive intranuclear inclusions in NIID individuals but not in the control or asymptomatic carrier.ConclusionOur study suggested the GGC repeat expansion in NOTCH2NLC might have a disease-causing number ranging from ~41 to ~300 repeats. The contraction of GGC repeat expansion in sperm could be a possible mechanism for the paternal-biased origin in some sporadic or recessive inherited NIID individuals. The toxic RNA gain-of-function mechanism was identified to be involved in the pathogenicity of this disease.

Crime prediction has attracted increasing attention due to its significance in public safety and growing availability of heterogeneous relevant data. Existing works on crime prediction usually failed to capture its dynamics and inherent non-linear relationships. To address these issues, in this paper, we propose an attentional recurrent neural network for future crime count prediction leveraging heterogeneous urban open data. In particular, we first extract and embed relevant features using multi-source data, e.g. crime records, POIs, demographic data and meteorological data. We then feed all features into a two-layer recurrent neural network to capture temporal relevance. Further, we incorporate an attention mechanism to capture the time-varying dependency. The final prediction results can be generated through a fully connected neural network. Extensive experiments with real-world datasets verify the effectiveness of our proposed framework which outperforms many baseline methods.

Crime has been a complex social problem worldwide, impacting numerous individuals in both property and psychology, and affecting public safety as well. To prevent and avoid crime is of great importance for urban authorities and citizens. Crime prediction using various urban sensing data provides a promising paradigm to cope with this challenging problem. However, previous studies on crime prediction mainly focus on coarse-grained prediction at the region level, which fail in fine-grained road-level crime inference due to data sparsity problems. This article proposes a road-level framework for fine-grained crime risk inference leveraging heterogeneous open data. We first extract a set of features from relevant external datasets and historical crime records, i.e., temporal, spatial, and recurrence crime features. We then establish a spatio-temporal crime pattern using spatio-temporal features, and further infer road-level crime risk incorporating with recurrence crime features. The framework not only considers a useful spatio-temporal pattern but also considers a unique crime near-repeat phenomenon, which helps address the data sparsity. We further present an application crime risk-aware route recommendation to demonstrate the effectiveness of our framework. This application cannot be solved well with coarse-grained (e.g., region-level) crime risk results since it is inconvenient for people to travel while avoiding large regions with potential crime risks. Experiments with the real-world datasets from New York City show that our framework accurately infers road-level crime risk and outperforms other baseline methods.

Traffic violations like illegal parking, illegal turning, and speeding have become one of the greatest challenges in urban transportation systems, bringing potential risks of traffic congestions, vehicle accidents, and parking difficulties. To maximize the utility and effectiveness of the traffic enforcement strategies aiming at reducing traffic violations, it is essential for urban authorities to infer the traffic violation-prone locations in cities. Therefore, we propose a low-cost, comprehensive, and dynamic framework to infer traffic violation-prone locations in cities based on the large-scale vehicle trajectory data and road environment data. First, we normalize the trajectory data by map matching algorithms and extract key driving behaviors, i.e., turning behaviors, parking behaviors, and speeds of vehicles. Second, we restore spatiotemporal contexts of driving behaviors to get corresponding traffic restrictions such as no-parking, no-turning, and speed restrictions. After matching the traffic restrictions with driving behaviors, we get the traffic violation distribution. Finally, we extract the spatiotemporal patterns of traffic violations and build a visualization system to showcase the inferred traffic violation-prone locations. To evaluate the effectiveness of the proposed method, we conduct extensive studies on large-scale, real-world vehicle GPS trajectories collected from two Chinese cities, respectively. Evaluation results confirm that the proposed framework infers traffic violation-prone locations effectively and efficiently, providing comprehensive decision supports for traffic enforcement strategies.

Surface enhanced Raman spectroscopy (SERS) is a powerful spectroscopic technique with unique vibrational fingerprints, making it an ideal candidate for in situ multiphase detection. However, it is a great challenge to determine how to guide the SERS sensor to target molecules of interest in multiphase heterogeneous samples with minimal disturbance. Here, we present a portable ultrasensitive and highly repeatable SERS sensor for in situ multiphase detection. The sensor is composed of commercial Ag acupuncture needle and PVP-Au nanoparticles (Au NPs). The PVP on the Au NPs can adsorb and induce the Au NPs into a highly uniform array on the surface of the Ag needle because of its adhesiveness and steric nature. The Au NPs-Ag Needle system (Au-AgN) holds a huge SERS effect, which is enabled by the multiple plasmonic couplings from particle–film and interparticle. The PVP, as the amphiphilic polymer, promotes the target molecules to adsorb on surface of the Au-AgN whether in the oil phase or in the water phase. In this work, the Au-AgN sensor was directly inserted into the multiphase system with the laser in situ detection, and SERS detection at different spots of the Au-AgN sensor provided Raman signal of targets molecule in the different phase. In situ multiphase detection can minimize the disturbance of sampling and provide more accurate information. The facile fabrication and amphiphilic functionalization make Au-AgN sensor as generalized SERS detection platform for on-site testing of aqueous samples, organic samples, even the multiphase heterogeneous samples.

Micron-sized silicon oxide (SiOx) has been regarded as a promising anode material for new-generation lithium-ion batteries due to its high capacity and low cost. However, the distinct volume expansion during the repeated (de)lithiation process and poor conductivity can lead to structural collapse of the electrode and capacity fading. In this study, SiOxanode materials coated with TiO0.6N0.4layers are fabricated by a facile solvothermal and thermal reduction technique. The TiO0.6N0.4layers are homogeneously dispersed on SiOxparticles and form an intimate contact. The TiO0.6N0.4layers can enhance the conductivity and suppress volume expansion of the SiOxanode, which facilitate ion/electron transport and maintain the integrity of the overall electrode structure. The as-prepared SiOx-TiON-200 composites demonstrate a high reversible capacity of 854 mAh g–1at 0.5 A g–1with a mass loading of 2.0 mg cm–2after 250 cycles. This surface modification technique could be extended to other anodes with low conductivity and large volume expansion for lithium-ion batteries.

A pure silica photonic crystal fiber with a group velocity dispersion (β_2) of 4  ps^2/km at 1.55 μm and less than 7  ps^2/km from 1.32 μm to the zero dispersion wavelength (ZDW) 1.80 μm was designed and fabricated. The dispersion of the fiber was measured experimentally and found to agree with the fiber design, which also provides low loss below 1.83 μm due to eight outer rings with increased hole diameters. The fiber was pumped with a 1.55 μm, 125 fs laser and, at the maximum in-coupled peak power (P_0) of 9 kW, a 1.34–1.82 μm low-noise spectrum with a relative intensity noise below 2.2% was measured. The numerical modeling agreed very well with the experiments and showed that P_0 could be increased to 26 kW before noise from solitons above the ZDW started to influence the spectrum by pushing high-noise dispersive waves through the spectrum.

Phosphorus widely exists in municipal and industrial wastewater effluents and is the primary cause of eutrophication in aqueous environments. Sorption processes can remove phosphorus to a very low concentration and simultaneously recovery the phosphorus resources. Microscale magnetic material shows significant higher adsorption capacity than granular adsorbent. The operation cost of super-conducting magnetic separation is extremely low. Therefore, in this work, FeOOH and magnetized FeOOH (Fe3O4@FeOOH) material was fabricated by a coprecipitation method to capture phosphate from municipal sewage wastewater. Fe3O4@FeOOH with different Fe3O4@FeOOH molar ratios was prepared. Fe3O4/FeOOH with the ratio of greater than 1:8 exhibited a satisfactory magnetization property (>6 emu/g), enabling rapid magnetic separation from water by a superconducting magnet and the recycling of the spent adsorbent. The Langmuir adsorption capacity of Fe3O4/FeOOH reached 4.6–11.7 mg/g in practical sewage wastewater after biological treatment. Fe3O4/FeOOH effectively removed phosphate from real wastewater from 1.8 mg/L to less than 0.1 mg/L. These results were interpreted by the ligand exchange mechanism, that is, the direct coordination of phosphate onto FeOOH by the replacement of hydroxyl groups. Fe3O4/FeOOH could be effectively separated from the sewage wastewater by a superconducting magnetic separator. A greater than 700 column volume was observed with 1/8Fe3O4/FeOOH used at 5 cm/s with a magnetic intensity of 5 T. The adsorbed phosphate could be desorbed with a NaOH treatment and the regenerated Fe3O4/FeOOH could be repeatedly used. Ca5(PO4)3OH and Ca5(PO4)3Cl were produced by adding CaCl2into the desorption solutions, and the P2O5content was measured to be 38.25%

Tumor-specific neoantigenshave attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database(TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutationdata and human leukocyte antigen(HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.

Tumor-specific neoantigenshave attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database(TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutationdata and human leukocyte antigen(HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.

Target analyte detection in complex systems with high selectivity and repeatability is crucial to analytical technology and science. Here we present a two-dimensional (2D) surface-enhanced resonance Raman scattering (SERRS) platform, which takes advantages of the high selectivity of the SERRS sensor as well as the sensitivity and reproducibility of the interfacial SERS platform, for detecting trace epinephrine (EP) in the serum. To realize sensitive and selective detection of EP in a complex system, Au NPs are modified with α,β-nitriloacetic acid and Fe(NO3)3to form the Au NP-(Fe-NTA) sensor, and as a consequence, EP can be rapidly captured by the sensor on the surface of Au NPs and then delivered at the cyclohexane/water interface. More importantly, we synthesized the extremely stable Au NPs (PVP-stabilized Au NPs), where the presence of PVP prevents aggregation of Au NPs during the self-assembly process and then makes a more uniform distribution of Au NPs with analytes at the cyclohexane/water interface, approximately 2 nm interparticle distance between the Au NPs, which has been proved by synchrotron radiation grazing incidence small-angle X-ray scattering (SR-GISAXS) experiments. The self-assembly method not only effectively avoids the aggregation of Au NPs and decreases the influence of the background signal but also can capture and enrich EP molecules in the cyclohexane/water interface, realizing the sensitive and selective detection of EP in complex serum sample. This strategy overcomes the difficulty of bringing nanostructures together to form efficient interparticle distance with simple fabrication and maximum uniformity and also provides a powerful nanosensor for tracing amounts of analyte molecules in a complex system with the advantages of capturing and enriching of target molecules in the liquid/liquid interface during the self-assembly process. Our SERRS platform opens vast possibilities for repeatability, sensitivity, and selectivity detection of targets in various complex fields.

Amyloid-β oligomers (AβOs) are the most important toxic species in the brain of Alzheimer’s disease (AD) patient. AβOs, therefore, are considered reliable molecular biomarkers for the diagnosis of AD. Herein, we reported a simple and sensitive electrochemical method for the selective detection of AβOs using silver nanoparticles (AgNPs) as the redox reporters and PrP(95–110), an AβOs-specific binding peptide, as the receptor. Specifically, adamantine (Ad)-labeled PrP(95–110), denoted as Ad-PrP(95–110), induced the aggregation and color change of AgNPs and the follow-up formation of a network of Ad-PrP(95–110)-AgNPs. Then, Ad-PrP(95–110)-AgNPs were anchored onto a β-cyclodextrin (β-CD)-covered electrode surface through the host–guest interaction between Ad and β-CD, thus producing an amplified electrochemical signal through the solid-state Ag/AgCl reaction by the AgNPs. In the presence of AβOs, Ad-PrP(95–110) interacted specifically with the AβOs, thus losing the capability to bind AgNPs and to induce the formation of an AgNPs-based network on the electrode surface. Consequently, the electrochemical signal decreased with an increase in the concentration of AβOs in the range of 20 pM to 100 nM. The biosensor had a detection limit of 8 pM and showed no response to amyloid-β monomers (AβMs) and fibrils (AβFs). On the basis of the well-defined and amplified electrochemical signal of the AgNPs-based network architecture, these results should be valuable for the design of novel electrochemical biosensors by marrying specific receptors.

We experimentally show octave-spanning supercontinuum generation in a nonstoichiometric silicon-rich nitride waveguide when pumped by femtosecond pulses from an erbium fiber laser. The pulse energy and bandwidth are comparable to results achieved in stoichiometric silicon nitride waveguides, but our material platform is simpler to manufacture. We also observe wave-breaking supercontinuum generation by using orthogonal pumping in the same waveguide. Additional analysis reveals that the waveguide height is a powerful tuning parameter for generating mid-infrared dispersive waves while keeping the pump in the telecom band.

We experimentally observe dispersive waves in the anomalous dispersion regime of a beta-barium-borate (BBO) crystal, induced by a self-defocusing few-cycle temporal soliton. Together the soliton and dispersive waves form an energetic octave-spanning supercontinuum. The soliton was excited in the normal dispersion regime of BBO through a negative cascaded quadratic nonlinearity. Using pump wavelengths from 1.24 to 1.4 μm, dispersive waves are found from 1.9 to 2.2 μm, agreeing well with calculated resonant phase-matching wavelengths due to degenerate four-wave mixing to the soliton. We also observe resonant radiation from nondegenerate four-wave mixing between the soliton and a probe wave, which was formed by leaking part of the pump spectrum into the anomalous dispersion regime. We confirm the experimental results through simulations.

We show numerically that ultrashort self-defocusing temporal solitons colliding with a weak pulsed probe in the near-IR can convert the probe to the mid-IR. A near-perfect conversion efficiency is possible for a high effective soliton order. The near-IR self-defocusing soliton can form in a quadratic nonlinear crystal (beta-barium borate) in the normal dispersion regime due to cascaded (phase-mismatched) second-harmonic generation, and the mid-IR converted wave is formed in the anomalous dispersion regime between λ=2.2–2.4  μm as a resonant dispersive wave. This process relies on nondegenerate four-wave mixing mediated by an effective negative cross-phase modulation term caused by cascaded soliton-probe sum-frequency generation.

Supercontinuum generation (SCG) is most efficient when the solitons can be excited directly at the pump laser wavelength. Quadratic nonlinear waveguides may induce an effective negative Kerr nonlinearity, so temporal solitons can be directly generated in the normal (positive) dispersion regime overlapping with common ultrafast laser wavelengths. There is no need for waveguide dispersion engineering. Here, we experimentally demonstrate SCG in standard lithium niobate (LN) waveguides without quasi-phase matching (QPM), pumped with femtosecond pulses in the normal dispersion regime. The observed large bandwidths (even octave spanning), together with other experimental data, indicate that negative nonlinearity solitons are indeed excited, which is backed up by numerical simulations. The QPM-free design reduces production complexity, extends the maximum waveguide length, and limits undesired spectral resonances. Finally, nonlinear crystals can be used where QPM is inefficient or impossible, which is important for mid-IR SCG. QPM-free waveguides in mid-IR nonlinear crystals can support negative nonlinearity solitons, as these waveguides have a normal dispersion at the emission wavelengths of mid-IR ultrafast lasers.

Formation and interaction of few-cycle solitons in a lithium niobate ridge waveguide are numerically investigated. The solitons are created through a cascaded phase-mismatched second-harmonic generation process, which induces a dominant self-defocusing Kerr-like nonlinearity on the pump pulse. The inherent material self-focusing Kerr nonlinearity is overcome over a wide wavelength range, and self-defocusing solitons are supported from 1100 to 1900 nm, covering the whole communication band. Single cycle self-compressed solitons and supercontinuum generation spanning 1.3 octaves are observed when pumped with femtosecond nanojoule pulses at 1550 nm. The waveguide is not periodically poled, as quasi-phase-matching would lead to detrimental nonlinear effects impeding few-cycle soliton formation.

A naphthalimide-based azo dye (1) used as a colorimetric and ratiometric probe for the detection of CN−was synthesized by incorporating a salicylaldehyde moiety, which acts as a recognition unit, to the naphthalimido diazonium salt. Upon reacting with CN−, probe 1displays dramatic colour changes rapidly from yellowish to red, corresponding to the absorption band shift from 408 nm to 497 nm. The colorimetric probe allows ratiometric detection of CN−with a linear range of 2–45 μM and a LOD (limit of detection) of 0.4 μM. In the optimized H2O/DMSO (7/3, v/v) mixed solvent, probe 1displays excellent selectivity for CN−over other anions. In addition, 1was successfully employed to prepare the filter paper-based test strips which can be used to monitor CN−conveniently, and the discernible concentration of CN−can be as low as 20 μM.