Do multisource data matter for NGP prediction? Evidence from the G-LSTM model.

Precisely predicting natural gas prices (NGPs) is important because it can provide the necessary decision-making basis for energy scheduling, planning and control. However, NGPs are affected by many factors and exhibit the characteristics of nonlinearity and randomness, which makes accurate predictions challenging. Therefore, in this paper, the information gain of multisource data and the global optimization ability of the gray wolf algorithm are used to build a multifactor-driven NGP hybrid forecasting model to improve the prediction performance. First, the emotional tendency and readability of news text are extracted and calculated by using VADER and textstat tools, respectively. Then the network search index is filtered and integrated by using the correlation coefficient method and the CRITIC method to form alternative variables of multisource data (news and search index). Second, the gray wolf optimization algorithm is used to find and determine the best key parameter group in long short-term memory model. Finally, the spot price of natural gas in Henry Hub from March 1, 2012 to February 28, 2022 is selected as the prediction object, and multi-scenario numerical experiments are carried out to verify the effectiveness of the proposed model. The ablation experiment results show that the information gain brought by multisource data can effectively improve the prediction effect of NGPs. Furthermore, the proposed model has the best prediction performance in different scenarios and can be regarded as a promising prediction tool.

Quality of evidence supporting the role of probiotics for rheumatoid arthritis: an overview of systematic reviews.

Background: To evaluate the methodological quality, report quality, and evidence quality of meta-analysis (MA) and systematic review (SR) on the efficacy of probiotics in the treatment of rheumatoid arthritis (RA). Methods: Databases were used to identify eligible SRs/MAs until February 12, 2024. The methodological quality of the studies was assessed using AMSTAR-2 tool, the quality of the literature reports was scored using PRISMA checklists, and the quality of the evidence was graded using GRADE system. Results: Seven reviews including 21 outcomes were included. Methodological quality of the included reviews was of general low, and the entries with poor scores were 2, 4, and 7. By PRISMA checklists, there were some reporting deficiencies, and quality problems were mainly reflected in the reporting registration and protocol, comprehensive search strategy and additional analysis. GRADE results elevated the quality of evidence to be low or very low overall. Conclusions: Probiotics may have a therapeutic effect on RA, based on the evidence provided by the SRs/MAs in this overview. Nevertheless, there is still a lack of conclusive evidence due to methodological limitations in the included research. To make trustworthy judgments regarding the efficacy of probiotics in the treatment of RA, more large-scale, high-quality randomized controlled trials are still required.

[Spatiotemporal Pattern and Influencing Factors of Thermal Environment Based on SEM Model: A Case Study in Xi'an Metropolitan Area].

The urban thermal environment is an important indicator for evaluating the ecological environment of a city. It directly affects the health of residents and the sustainable development of the urban economy. However, there is currently a lack of analysis on the impact pathways of the thermal environment considering both natural and human factors. Based on the MODIS MYD11A2 land surface temperature data, meteorological data, and human activity data of Xi'an metropolitan area in 2020, ArcGIS spatial geostatistical analysis was used to study the temporal and spatial distribution pattern of the thermal environment in different seasons, and redundancy analysis was utilized to select the main factors affecting the thermal environment. Then, structural equation modeling was used to quantify the direct and indirect effects of the dominant factors on the urban thermal environment. The results showed that:① The surface temperature in the Xi'an urban area showed a spatial pattern of higher temperatures in the north and lower temperatures in the south, with a decrease in temperature from the city center to the surrounding areas. The most severe heat environment pollution occurred in the summer. ② The redundancy analysis (RDA) results indicated that the main factors that affected the thermal environment were air temperature, impermeable surfaces, vegetation, and precipitation. ③ The results of the structural equation modeling (SEM) indicated that meteorological, surface, and anthropogenic factors affected the urban thermal environment mainly through direct pathways, which were much more important than all indirect pathways. Factors such as temperature, impervious surfaces, and point of interest density had a significant positive effect on the thermal environment (0.10 and 0.33). On the other hand, factors such as water bodies, precipitation, and vegetation had a significant negative effect on the thermal environment (-0.29 and -0.25). Human activities had a greater direct impact on nocturnal surface temperatures than surface and meteorological factors. Increasing economic efficiency is beneficial for mitigating the urban heat island effect. The results of the study can provide a reference for studying local climate change in urban heat islands and for the construction of green and ecologically livable urban environments.

Metal-Loaded Synthetic Melanin via Oxidative Polymerization of Neurotransmitter Norepinephrine Exhibiting High Photothermal Conversion.

Polydopamine (PDA)-derived melanin-like materials exhibit significant photothermal conversion owing to their broad-spectrum light absorption. However, their low near-infrared (NIR) absorption and inadequate hydrophilicity compromise their utilization of solar energy. Herein, we developed metal-loaded poly(norepinephrine) nanoparticles (PNE NPs) by predoping metal ions (Fe3+, Mn3+, Co2+, Ca2+, Ga3+, and Mg2+) with norepinephrine, a neuron-derived biomimetic molecule, to address the limitations of PDA. The chelation between catechol and metal ions induces a ligand-to-metal charge transfer (LMCT) through the formation of donor-acceptor pairs, modulating the light absorption behavior and reducing the band gap. Under 1 sun illumination, the Fe-loaded PNE coated wood evaporator achieved a high seawater evaporation rate and efficiency of 1.75 kg m-2 h-1 and 92.4%, respectively, owing to the superior hydrophilicity and photothermal performance of PNE. Therefore, this study offers a comprehensive exploration of the role of metal ions in enhancing the photothermal properties of synthetic melanins.

Ultrasmall Nanoparticles Regulate Immune Microenvironment by Activating IL-33/ST2 to Alleviate Renal Ischemia-Reperfusion Injury.

Renal ischemia-reperfusion injury (IRI) is a common disease with high morbidity and mortality. Renal IRI can cause the disorder of immune microenvironment and reprograming the immune microenvironment to alleviate excessive inflammatory response is crucial for its treatment. Cytokine IL-33 can improve the immune inflammatory microenvironment by modulating both innate and adaptive immune cells, and serve as an important target for modulating immune microenvironment of renal IRI. Herein, we report that bilobetin-functionalized ultrasmall Cu2- xSe nanoparticles (i.e., CSPB NPs) can activate the PKA/p-CREB/IL-33/ST2 signaling pathway to regulate innate and adaptive immune cells for reprograming the immune microenvironment of IRI-induced acute kidney injury. The biocompatible CSPB NPs can promote the polarization of M1-like macrophages into M2-like macrophages, and the expansion of ILC2 and Treg cells by activating IL-33/ST2 to modulate the excessive immune inflammatory response of renal IRI. More importantly, they can rapidly accumulate at the injured kidney to significantly alleviate IRI. This work demonstrates that modulating the expression of cytokines to reprogram immune microenvironment has great potential in the treatment of renal IRI and other ischemic diseases.

Melanin-Inspired Composite Materials: From Nanoarchitectonics to Applications.

Synthetic melanin is a mimic of natural melanin analogue with intriguing properties such as metal-ion chelation, redox activity, adhesion, and broadband absorption. Melanin-inspired composite materials are formulated by assembly of melanin with other types of inorganic and organic components to target, combine, and build up the functionality, far beyond their natural capabilities. Developing efficient and universal methodologies to prepare melanin-based composite materials with unique functionality is vital for their further applications. In this review, we summarize three types of synthetic approaches, predoping, surface engineering, and physical blending, to access various melanin-inspired composite materials with distinctive structure and properties. The applications of melanin-inspired composite materials in free radical scavenging, bioimaging, antifouling, and catalytic applications are also reviewed. This review also concludes current challenges that must be addressed and research opportunities in future studies.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas.

PURPOSE: To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9). METHODS: This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test. RESULTS: The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076). CONCLUSIONS: Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

Systematic review and integrated analysis of prognostic gene signatures for prostate cancer patients.

Prostate cancer (PC) is one of the most common cancers in men and becoming the second leading cause of cancer fatalities. At present, the lack of effective strategies for prognosis of PC patients is still a problem to be solved. Therefore, it is significant to identify potential gene signatures for PC patients' prognosis. Here, we summarized 71 different prognostic gene signatures for PC and concluded 3 strategies for signature construction after extensive investigation. In addition, 14 genes frequently appeared in 71 different gene signatures, which enriched in mitotic and cell cycle. This review provides extensive understanding and integrated analysis of current prognostic signatures of PC, which may help researchers to construct gene signatures of PC and guide future clinical treatment.

Distributed convex optimization of bipartite containment control for high-order nonlinear uncertain multi-agent systems with state constraints.

This article investigates a penalty-based distributed optimization algorithm of bipartite containment control for high-order nonlinear uncertain multi-agent systems with state constraints. The proposed method addresses the distributed optimization problem by designing a penalty function in the form of a quadratic function, which is the sum of the global objective function and the consensus constraint. Moreover, the observer is presented to address the unmeasurable state of each agent. Radial basis function neural networks (RBFNN) are employed to approximate the unknown nonlinear functions. Then, by integrating RBFNN and dynamic surface control (DSC) techniques, an adaptive backstepping controller based on the barrier Lyapunov function (BLF) is proposed. Finally, the effectiveness of the suggested control strategy is verified under the condition that the state constraints are not broken. Simulation results indicate that the output trajectories of all agents remain within the upper and lower boundaries, converging asymptotically to the global optimal signal.

Fecal microbiota transplantation as a therapy for treating ulcerative colitis: an overview of systematic reviews.

AIM: The current overview on published systematic reviews (SRs) and meta-analysis (MAs) aimed to systematically gather, evaluate, and synthesize solid evidence for using fecal microbiota transplantation (FMT) to treat ulcerative colitis (UC). METHODS: Relevant articles published before January 2023 were collected from Web of Science, Embase, PubMed, and Cochrane Library. Two authors used Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool, PRISMA checklists, and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system were applied by two authors to independently evaluate the methodological quality, reporting quality, and evidence quality, respectively. Re-meta-analysis on the primary RCTs was conducted after excluding overlapping randomized controlled trials (RCTs). RESULTS: Six SRs/MAs involving 12 primary RCTs and 544 participants were included. According to the AMSTAR-2 tool and PRISMA checklist, methodological quality and reporting quality of the included studies was overall satisfactory. The evidence quality of a great majority of outcomes was rated as moderate to high according to the GRADE system. Compared to placebo, the re-meta-analysis found a great advantage of use FMT in inducing combined clinical and endoscopic remission (OR 3.83 [2.31, 6.34]), clinical remission (3.31 [2.09, 5.25]), endoscopic remission (OR 3.75 [2.20, 6.39]), clinical response (OR 2.56 [1.64, 4.00]), and endoscopic response (OR 2.18 [1.12, 4.26]). Pooled data showed no significant difference in serious adverse events between patients receiving FMT and those receiving placebo (OR 1.53 [0.74, 3.19]). Evidence quality of the outcomes derived from re-meta-analysis was significantly higher after overcoming the limitations of previous SRs/MAs. CONCLUSION: In conclusion, moderate- to high-quality evidence supported a promising use of FMT to safely induce remission in UC. However, further trials with larger sample size are still required to comprehensively analyze the delivery route, total dosage, frequency, and donor selection in FMT.

Distribution of potentially toxic elements in soils and sediments in Pearl River Delta, China: Natural versus anthropogenic source discrimination.

Although anthropogenic contamination has been regarded as the most important source of potentially toxic elements (PTEs) in soils of large river delta plains, the extent to which human activities affect PTEs in soils is worth exploring. This study used high density geochemical data to distinguish source patterns of PTEs in soils of the Pearl River Delta Economic Zone, a large industrialized and urbanized area in China. Enrichment factor, discriminant analysis, principal components analysis, cumulative distribution function, and positive matrix factorization were used to identify sources of PTEs in soils. The results indicated that parent material was the most significant factor affecting geochemical characteristics of PTEs in soils. Median concentrations of Cd, Cr, Cu, Hg, Pb, and Zn were 0.400, 88.5, 40.5, 0.143, 43.0, and 116.0 mg/kg for stream sediments, 0.333, 75.7, 39.0, 0.121, 42.6, and 98.5 mg/kg for deep soils, and 0.365, 74.0, 45.1, 0.143, 44.6, and 119.5 mg/kg for surface soils, respectively, all of which exceed relevant reference standards. Compared with stream sediments and deep soils, surface soils exhibit substantial concentrations of PTEs. Chemical weathering and erosion of parent materials distributed in the Pearl River Delta were the main sources of PTEs in soils. Diffuse contamination and many small local contamination sources distributed throughout the study area were the most significant anthropogenic sources of PTEs in surface soils. Intensive human activities failed to change the soil geochemical characteristics derived from the parent material at the regional scale. However, it could induce non-point source pollution and local severe PTEs pollution in surface soils.

Electric field-induced assembly of Au-Ag alloy nanoparticles into nano-reticulation for ultrasensitive SERS.

This paper discusses a method for assembling Au-Ag alloy nanoparticles (NPs) using direct current (DC) electric field to fabricate highly active SERS substrates. Different nanostructures could be obtained by regulating the intensity and action time of DC electric field. Under the condition of 5mA*10 min, we obtained Au-Ag alloy nano-reticulation (ANR) substrate with excellent SERS activity (Enhancement factor on order of magnitude of 106). ANR substrate has excellent SERS performance due to the resonance matching between its LSPR mode and excitation wavelength. The uniformity of the Raman signal on ANR is greatly improved than bare ITO glass. ANR substrate also has the ability to detect multiple molecules: ANR substrate can respectively detect Rh6G and CV molecules with a concentration as low as 10-10 M and 10-9 M and the Raman spectral intensity of the probe molecules on the surface of the ANR substrate has good linear correlation with the molecular concentration (R2 > 0.95). In addition, ANR substrate can detect both thiram and aspartame (APM) molecules far below (thiram for 0.0024 ppm and APM for 0.0625 g/L) the safety standard, which demonstrate its practical application potential.

National resilience assessment and improvement based on multi-source data: Evidence from countries along the belt and road.

National resilience is a consensus benchmark to characterize the ability of disaster resistance of a country. The occurrence of various disasters and the ravages of COVID-19 have created urgent needs in assessing and improving the national resilience of countries, especially for countries along the Belt and Road (i.e., B&R countries) with multiple disasters with high frequency and great losses. To accurately depict the national resilience profile, a three-dimensional assessment model based on multi-source data is proposed, where the diversity of losses, fusion utilization of disaster and macro-indicator data, and several refined elements are involved. Using the proposed assessment model, the national resilience of 64 B&R countries is clarified based on more than 13,000 records involving 17 types of disasters and 5 macro-indicators. However, their assessment results are not optimistic, the dimensional resilience are generally trend-synchronized and individual difference in a single dimension, and approximately one-half of countries do not obtain resilience growth over time. To further explore the applicable solutions for national resilience improvement, a coefficient-adjusted stepwise regression model with 20 macro-indicator regressors is developed based on more than 19,000 records. This study provides the quantified model support and a solution reference for national resilience assessment and improvement, which contributes to addressing the global national resilience deficit and promoting the high-quality development of B&R construction.

Ameliorating Mitochondrial Dysfunction of Neurons by Biomimetic Targeting Nanoparticles Mediated Mitochondrial Biogenesis to Boost the Therapy of Parkinson's Disease.

Mitochondrial dysfunction of neurons is the core pathogenesis of incurable Parkinson's disease (PD). It is crucial to ameliorate the mitochondrial dysfunction of neurons for boosting the therapy of PD. Herein, the remarkable promotion of mitochondrial biogenesis to ameliorate mitochondrial dysfunction of neurons and improve the treatment of PD by using mitochondria-targeted biomimetic nanoparticles, which are Cu2- x Se-based nanoparticles functionalized with curcumin and wrapped with DSPE-PEG2000 -TPP-modified macrophage membrane (denoted as CSCCT NPs), is reported. These nanoparticles can efficiently target mitochondria of damaged neurons in an inflammatory environment, and mediate the signaling pathway of NAD+ /SIRT1/PGC-1α/PPARγ/NRF1/TFAM to alleviate 1-methyl-4-phenylpyridinium (MPP+ )-induced neuronal toxicity. They can reduce the mitochondrial reactive oxygen species, restore mitochondrial membrane potential (MMP), protect the integrity of mitochondrial respiratory chain, and ameliorate mitochondrial dysfunction via promoting mitochondrial biogenesis, which synergistically improve the motor disorders and anxiety behavior of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mice. This study demonstrates that targeting mitochondrial biogenesis to ameliorate mitochondrial dysfunction has a great potential in the treatment of PD and mitochondria-related diseases.

Changes in air pollution, land surface temperature, and urban heat islands during the COVID-19 lockdown in three Chinese urban agglomerations.

COVID-19 has notably impacted the world economy and human activities. However, the strict urban lockdown policies implemented in various countries appear to have positively affected pollution and the thermal environment. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and aerosol optical depth (AOD) data were selected, combined with Sentinel-5P images and meteorological elements, to analyze the changes and associations among air pollution, LST, and urban heat islands (UHIs) in three urban agglomerations in mainland China during the COVID-19 lockdown. The results showed that during the COVID-19 lockdown period (February 2020), the levels of the AOD and atmospheric pollutants (fine particles (PM2.5), NO2, and CO) significantly decreased. Among them, PM2.5 and NO2 decreased the most in all urban agglomerations, by >14 %. Notably, the continued improvement in air pollution attributed to China's strict control policies could lead to overestimation of the enhanced air quality during the lockdown. The surface temperature in all three urban agglomerations increased by >1 °C during the lockdown, which was mainly due to climate factors, but we also showed that the lockdown constrained positive LST anomalies. The decrease in the nighttime urban heat island intensity (UHIInight) in the three urban agglomerations was greater than that in the daytime quantity by >25 %. The reduction in surface UHIs at night was mainly due to the reduced human activities and air pollutant emissions. Although strict restrictions on human activities positively affected air pollution and UHIs, these changes were quickly reverted when lockdown policies were relaxed. Moreover, small-scale lockdowns contributed little to environmental improvement. Our results have implications for assessing the environmental benefits of city-scale lockdowns.

Identification and Characteristics of Novel Mutations in Nonsyndromic Monogenic Obesity.

Nonsyndromic monogenic obesity (NSMO) is a class of individual obesity that is independent of the environment and caused by a single gene mutation. It is mostly caused by mutations in LEP, LEPR, PCSK1, as well as some rare mutations in UCP3, NR0B2, and PPARG. Among 30 obesity patients, five patients are identified with positive gene detection. For the first time, the c.624C>T mutation associated with PCSK1, and the c.50G>A and c.293_301delinsAC mutations associated with NR0B2, as well as the obesity phenotype mutation (c.284A>G) associated with PPARG is confirmed. Following this, the genotype-clinical phenotype, mutation hotspots, and mutation distributions of each gene are summarized, and the genetic characteristics of NSMO are analyzed. The locations of mutation c.50G>A, and c.284A>G are highly conserved according to the sequencing alignment. According to the findings, the c.624C>T mutation in PCSK1 is a newly discovered synonymous mutation, but it can result in significant early-onset obesity. Additionally, the mutation of c.284A>G(PPARG) can lead to a variety of clinical phenotypes and the mutation of UCP3 and NR0B2 may increase the risk of type 2 diabetes mellitus. This study enriches the human NSMO gene mutation database and provides a scientific basis for clinically accurate diagnosis and treatment.

Balancing Volmer Step by Superhydrophilic Dual-Active Domains for Enhanced Hydrogen Evolution.

The reaction kinetics of hydrogen evolution reaction (HER) is largely determined by balancing the Volmer step in alkaline media. Bifunctionality as a proposed strategy can divide the work of water dissociation and intermediates (OH* and H*) adsorption/desorption. However, sluggish OH* desorption plagues water re-adsorption, which leads to poisoning effects of active sites. Some active sites may even directly act as spectators and do not participate in the reaction. Furthermore, the activity comparison under approximate nanostructure between bifunctional effect and single-exposed active sites is not fully understood. Here, a facile three-step strategy is adopted to successfully grow molybdenum disulfide (MoS2 ) on cobalt-containing nitrogen-doped carbon nanotubes (Co-NCNTs), forming obvious dual active domains. The active sites on domains of Co-NCNTs and MoS2  and the tuned electronic structure at the heterointerface trigger the bifunctional effect to balance the Volmer step and improve the catalytic activity. The HER driven by the bifunctional effect can significantly optimize the Gibbs free energy of water dissociation and hydrogen adsorption, resulting in fast reaction kinetics and superior catalytic performance. As a result, the Co-NCNTs/MoS2  catalyst outperforms other HER electrocatalysts with low overpotential (58 and 84 mV at 10 mA cm-2  in alkaline and neutral conditions, respectively), exceptional stability, and negligible degradation.

Low-cost and flexible paper-based plasmonic nanostructure for a highly sensitive SERS substrate.

The application of a noble-metal-based plasmon-enhanced substrate to detect low-concentration analytes has attracted extensive attention. Most of the substrates used in recently reported researches are based on two-dimensional structures. Hence, we prepared a higher efficiency Raman activity substrate with a filter paper structure, which not only provides more plasmonic "hot spots," but also facilitates analyte extraction and detection due to the flexibility of the paper. The preparation of the plasmonic paper substrate adopted centrifugation to deposit the alloy nanoparticles onto the paper base. The optimal particle deposition condition was found by adjusting the centrifugal force and centrifugation time. Then, the surface-enhanced Raman spectroscopy (SERS) performance of the substrate was enhanced by altering the plasmon resonance peak on the surface of the nanoparticles. The enhancement factor of this paper-based substrate was 1.55×107, with high detection uniformity (10-6 M, rhodamine 6G) and a low detection limit (10-11 M, rhodamine 6G). Then, we applied the SERS substrate to pesticide detection; the detection limit of the thiram reached 10-6 M. As a result, the simple and cost-effective paper-based SERS substrate obtained in this way has high detection performance for pesticides and can be used for rapid detection in the field, which is beneficial to food safety and environmental safety.

Capillary-force-assisted self-assembly of gold nanoparticles into highly ordered plasmonic thin films for ultrasensitive SERS.

In this study, a capillary device based on the surface plasmon-enhanced Raman scattering effect was prepared by a simple and easy method. First, the capillary was treated with APTES solution. Due to the electrostatic effect, gold nanoparticles could be easily and tightly assembled in the capillary inner wall. On this basis, the effects of changing the concentration of APTES, the concentration of colloids and the soaking time of the capillary in the colloids on the assembly of gold nanoparticles on the inner wall of the capillary were studied, and the SERS enhancement effect under different conditions was analyzed, and the optimal solution was successfully found. At the same time, the reason why the capillary substrate shows better SERS performance than the traditional planar substrate is deeply discussed. Since the nanoparticles can be attached to the upper and lower surfaces of the inner wall of the capillary, the utilization rate of nanoparticles and laser is improved, thereby achieving higher enhancement. For the detection of the probe molecule rhodamine 6G, it was proved that the substrate has good uniformity and the lowest detection limit can reach 10-10 M. Finally, the real-life pesticide thiram and the food additive aspartame were tested, and the detection limits could reach 10-6 M and 0.25 g L-1. It is confirmed that the prepared capillary shows excellent SERS performance and can be used for rapid detection in various fields.

Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms.

PURPOSE: To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection. METHODS: This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale. RESULTS: The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI40keV (P < 0.05). The detection performance of DLCT images was better than conventional images. CONCLUSIONS: The VMI40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.