PTEN and P-4E-BP1 might be associated with postoperative recurrence of rectal cancer patients undergoing concurrent radiochemotherapy.

BACKGROUND: Local recurrence after surgery and radiochemotherapy seriously affects the prognosis of locally advanced rectal cancer (LARC) patients. Studies on molecular markers related to the radiochemotherapy sensitivity of cancers have been widely carried out, which might provide valued information for clinicians to carry out individual treatment. AIM: To find potential biomarkers of tumors for predicting postoperative recurrence. METHODS: In this study, LARC patients undergoing surgery and concurrent radiochemotherapy were enrolled. We focused on clinicopathological factors and PTEN, SIRT1, p-4E-BP1, and pS6 protein expression assessed by immunohistochemistry in 73 rectal cancer patients with local recurrence and 76 patients without local recurrence. RESULTS: The expression of PTEN was higher, while the expression of p-4E-BP1 was lower in patients without local recurrence than in patients with local recurrence. Moreover, TNM stage, lymphatic vessel invasion (LVI), PTEN and p-4E-BP1 might be independent risk factors for local recurrence after LARC surgery combined with concurrent radiochemotherapy. CONCLUSIONS: This study suggests that PTEN and p-4E-BP1 might be potential biomarkers for prognostic prediction and therapeutic targets for LARC.

Pharmacokinetic/Pharmacodynamic assessment of the structural refinement of clopidogrel focusing on the balance between bioactivation and deactivation.

The delicate balance between ischemic and bleeding risks is a significant consideration in the administration of antiplatelet therapy. Clopidogrel and prasugrel, both members of the thienopyridine class of antiplatelet drugs, are well established for their variability in individual responsiveness and for a high number of bleeding events, respectively. The current study focuses on evaluating the pharmacokinetics and pharmacodynamics of a series of deuterated clopidogrel derivatives, leveraging insights gained from the structure-pharmacokinetic relationships in the development of thienopyridine drugs. Our approaches were based on the molecular skeleton of clopidogrel and adopted the C2-pharmacophore design from prasugrel. The selected C2-pharmacophore distinguishes itself from the acetyloxy substituent of prasugrel by exhibiting a moderated hydrolysis rate, resulting in a gentler formation of the active metabolite. An excessive and burst release of the active metabolite are therefore to be avoided, as it is believed to be associated with an increased risk of bleeding. Our proposed structural modification maintains the hydrolysis-sensitive methyl ester of clopidogrel but replaces it with a deuterated methyl group, which has been shown to effectively reduce metabolic deactivation. The evaluation of the clopidogrel derivatives has been primarily based on the criteria related to the exposure to active metabolites. Three promising compounds demonstrate higher biotransformation efficiency, similar Cmax, delayed Tmax, enhanced antiplatelet activity, and a lower risk of bleeding compared to clopidogrel, when administered at a dosage resulting in a similar exposure to the active metabolites. Significance Statement The pharmacokinetics and pharmacodynamics of a series of newly designed clopidogrel derivatives were assessed to validate the rationale for their structural modifications. Three promising compounds displayed balanced pharmacokinetics, characterized by slower deactivation compared to clopidogrel and a more gradual bioactivation than prasugrel. Under similar exposure to active metabolites, these compounds have demonstrated enhanced antiplatelet activity and a diminished risk of bleeding compared to clopidogrel. The D3-clopidogrel-ozagrel conjugate was found to exert a synergistic therapeutic effect.

Turning Ultra-Low Coercivity and Ultra-High Temperature Stability Within 897 K via Continuous Crystal Ordering Fluctuations.

High-performance soft magnetic materials are important for energy conservation and emission reduction. One challenge is achieving a combination of reliable temperature stability, high resistivity, high Curie temperature, and high saturation magnetization in a single material, which often comes at the expense of intrinsic coercivity-a typical trade-off in the family of soft magnetic materials with homogeneous microstructures. Herein, a nanostructured FeCoNiSiAl complex concentrated alloy is developed through a hierarchical structure strategy. This alloy exhibits superior soft magnetic properties up to 897 K, maintaining an ultra-low intrinsic coercivity (13.6 A m-1 at 297 K) over a wide temperature range, a high resistivity (138.08 µΩ cm-1 at 297 K) and the saturation magnetization with only a 16.7% attenuation at 897 K. These unusual property combinations are attributed to the dual-magnetic-state nature with exchange softening due to continuous crystal ordering fluctuations at the atomic scale. By deliberately controlling the microstructure, the comprehensive performance of the alloy can be tuned and controlled. The research provides valuable guidance for the development of soft magnetic materials for high-temperature applications and expands the potential applications of related functional materials in the field of sustainable energy.

Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions.

Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today can meet the clinical requirements, with the mean Dice score - the most important metric in medical image analysis - hardly exceeding 0.75. In this paper, we present a novel deep learning approach for segmenting EEC lesions. Our method stands out for its uniqueness, as it relies solely on a single input image from a patient, forming the so-called "You-Only-Have-One" (YOHO) framework. On one hand, this "one-image-one-network" learning ensures complete patient privacy as it does not use any images from other patients as the training data. On the other hand, it avoids nearly all generalization-related problems since each trained network is applied only to the same input image itself. In particular, we can push the training to "over-fitting" as much as possible to increase the segmentation accuracy. Our technical details include an interaction with clinical doctors to utilize their expertise, a geometry-based data augmentation over a single lesion image to generate the training dataset (the biggest novelty), and an edge-enhanced UNet. We have evaluated YOHO over an EEC dataset collected by ourselves and achieved a mean Dice score of 0.888, which is much higher as compared to the existing deep-learning methods, thus representing a significant advance toward clinical applications. The code and dataset are available at: https://github.com/lhaippp/YOHO.

Atomic-Level Catalyst Coupled with Metal Oxide Heterostructure for Promoting Kinetics of Lithium-Sulfur Batteries.

Despite the low competitive cost and high theoretical capacity of lithium-sulfur (Li-S) batteries, their practical application is severely hindered by the lithium polysulfide (LiPS) shuttling and low conversion efficiency. Herein, the electronic structure of hollow Titanium dioxide nanospheres is tunned by single Iron atom dopants that can cooperatively enhance LiPS absorption and facilitate desired redox reaction in practical Li-S batteries, further suppressing the notorious shuttle effect, which is consistent with theoretical calculations and in situ UV/vis investigation. The obtained electrode with massive active sites and lower energy barrier for sulfur conversions exhibits exceptional cycling stability after 500 cycles and high capacity under the sulfur loading of 10.53 mg cm-2 . In particular, an Ah-level Li-S pouch cell is fabricated, further demonstrating that the synthetic strategy based on atomic-level design offers a promising route toward practical high-energy-density Li-S batteries.

The influence of hydrocarbon generation on the sealing capability of mudstone caprock rich in organic matter.

To investigate the sealing capability of mudstone caprock during the evolution of organic matter (OM)-rich mudstone, a series of hydrous pyrolysis experiments were first conducted to examine the impact of hydrocarbon generation. The pore type, pore structure, porosity, and gas breakthrough pressure of pyrolytic residual samples were analyzed by field emission scanning electron microscopy, low pressure nitrogen adsorption measurements, porosimetry, and gas breakout core experiments. To model the environment at different depths, these six experiments on hydrous pyrolysis were performed at different temperatures, lithostatic pressures, and hydrodynamic pressures, while other experimental factors such as the original sample, heating time, and rate were kept constant. The results showed that during the thermal evolution process, hydrocarbons were generated from OM in mudstone, resulting in the formation of pores within the OM. Organic acids produced by hydrocarbon generation effectively dissolved minerals, leading to the creation of numerous dissolution pores. Changes in pore type led to changes in pore structure and porosity. The volume of micropores and macropores showed an increasing trend before reaching a Ro value of 1.41%. However, after passing this threshold, they began to decrease. The volume of mesopores showed a decreasing trend before reaching a Ro value of 1.32%. After 1.32%, they began to increase. The porosity was mainly affected by the pore volumes of the mesopores and macropores. The porosity exhibited two peaks: the first occurred at a Ro value of 0.72%, with a porosity level of 4.6%. The second occurred at a Ro value of 1.41% and a porosity level of 10.3%. The breakthrough pressure was a comprehensive reflection of these influences, and its trend exhibited a negative correlation with porosity (R2 = 0.886). For two high values of porosity, the breakthrough pressure corresponded to two low values. Smaller values of the breakthrough pressure indicated a poorer sealing capability of the mudstone caprock. Overall, hydrocarbon generation in the mudstone affected the sealing capability. The mudstone in the studied area exhibited good sealing at Ro below 1.32%. However, once above the 1.32% threshold, the fluctuations of the breakthrough pressure values exhibited considerable variability, requiring a comprehensive evaluation to assess its sealing capability.

Codon usage bias analysis of the spike protein of human coronavirus 229E and its host adaptability.

Human coronavirus 229E (HCoV-229E) represents one of the known coronaviruses capable of infecting humans and causes mild respiratory symptoms. It is also considered to have a zoonotic source, originating from animals and being transmitted the humans. In this study, a comprehensive phylogenetic and codon usage analysis of the spike (S) gene of HCoV-229E was conducted. Utilizing phylogenetic analysis and principal component analysis, HCoV-229E was categorized into four distinct clusters, each demonstrating unique host affiliations. Furthermore, it was observed that the codon usage bias within the S gene of HCoV-229E is relatively low, primarily influenced by natural selection patterns, with contributions from mutation pressure and dinucleotide abundance. Comparative analysis involving Codon Adaptation Index (CAI) and Relative Codon Deoptimization Index (RCDI) revealed that the codon usage pattern of HCoV-229E mirrors more closely that of camels, as opposed to alpacas and humans. The elucidation of the codon usage pattern within HCoV-229E, which we have meticulously examined, offers valuable insights for a more comprehensive comprehension of viral features, history, and evolutionary trajectory.

Toxicity of chromium to wheat (Triticum aestivum L.) in two soils: influence of soil properties and chromium form.

The toxicity of Cr to plants depends on Cr form and soil properties. Currently, the phytotoxicity differences of Cr(VI) and Cr(III) in different soils are not clear. In this study, the toxicity of Cr(VI) and Cr(III) to root growth and root morphology of wheat (Triticum aestivum L.) were compared in Shandong fluvo-aquic soil (SD soil) and Jiangxi red soil (JX soil) that is differing in soil properties. The toxicity thresholds of Cr(VI) and Cr(III) on wheat root elongation were determined by fitting the dose-effect curves. Results showed that the 10% and 50% root length inhibitory concentrations (EC10 and EC50) of Cr(III) were 53.1 and 125 times of Cr(VI) in SD soil and 8.11 and 1.36 times of Cr(VI) in JX soil, indicating that Cr(VI) was more toxic to wheat roots than Cr(III) in both soils and the toxicity discrepancy of the two forms of Cr was more prominent in SD soil. Cr(VI) exhibited higher toxicity in SD soil (alkaline) than in JX soil (acidic), whereas Cr(III) showed the opposite pattern. In addition, the ethylene diamine tetraacetic acid extractable Cr (EDTA-Cr) concentrations in soils were correlated well with the relative wheat root elongation (R2=0.854, P<0.01), indicating that soil EDTA-Cr concentration can be used as a predictor of Cr phytotoxicity. Both Cr(VI) and Cr(III) showed significant biphasic dose effects on wheat root morphology (root length, root surface area, root volume, and root tip number) in JX soil. These findings are helpful for the risk evaluation of Cr contamination in agricultural soils.

Genomic inference of a severe human bottleneck during the Early to Middle Pleistocene transition.

Population size history is essential for studying human evolution. However, ancient population size history during the Pleistocene is notoriously difficult to unravel. In this study, we developed a fast infinitesimal time coalescent process (FitCoal) to circumvent this difficulty and calculated the composite likelihood for present-day human genomic sequences of 3154 individuals. Results showed that human ancestors went through a severe population bottleneck with about 1280 breeding individuals between around 930,000 and 813,000 years ago. The bottleneck lasted for about 117,000 years and brought human ancestors close to extinction. This bottleneck is congruent with a substantial chronological gap in the available African and Eurasian fossil record. Our results provide new insights into our ancestry and suggest a coincident speciation event.

Enhancing the Mechanical Stability of 2D Fullerene with a Graphene Substrate and Encapsulation.

Recent advancements have led to the synthesis of novel monolayer 2D carbon structures, namely quasi-hexagonal-phase fullerene (qHPC60) and quasi-tetragonal-phase fullerene (qTPC60). Particularly, qHPC60 exhibits a promising medium band gap of approximately 1.6 eV, making it an attractive candidate for semiconductor devices. In this study, we conducted comprehensive molecular dynamics simulations to investigate the mechanical stability of 2D fullerene when placed on a graphene substrate and encapsulated within it. Graphene, renowned for its exceptional tensile strength, was chosen as the substrate and encapsulation material. We compared the mechanical behaviors of qHPC60 and qTPC60, examined the influence of cracks on their mechanical properties, and analyzed the internal stress experienced during and after fracture. Our findings reveal that the mechanical reliability of 2D fullerene can be significantly improved by encapsulating it with graphene, particularly strengthening the cracked regions. The estimated elastic modulus increased from 191.6 (qHPC60) and 134.7 GPa (qTPC60) to 531.4 and 504.1 GPa, respectively. Moreover, we observed that defects on the C60 layer had a negligible impact on the deterioration of the mechanical properties. This research provides valuable insights into enhancing the mechanical properties of 2D fullerene through graphene substrates or encapsulation, thereby holding promising implications for future applications.

A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs.

Three prevalent SARS-CoV-2 variants of concern (VOCs) emerged and caused epidemic waves. It is essential to uncover advantageous mutations that cause the high transmissibility of VOCs. However, viral mutations are tightly linked, so traditional population genetic methods, including machine learning-based methods, cannot reliably detect mutations conferring a fitness advantage. In this study, we developed an approach based on the sequential occurrence order of mutations and the accelerated furcation rate in the pandemic-scale phylogenomic tree. We analyzed 3,777,753 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata using the Coronavirus GenBrowser. We found that two noncoding mutations at the same position (g.a28271-/u) may be crucial to the high transmissibility of Alpha, Delta, and Omicron VOCs although the noncoding mutations alone cannot increase viral transmissibility. Both mutations cause an A-to-U change at the core position -3 of the Kozak sequence of the N gene and significantly reduce the protein expression ratio of ORF9b to N. Using a convergent evolutionary analysis, we found that g.a28271-/u, S:p.P681H/R, and N:p.R203K/M occur independently on three VOC lineages, suggesting that coordinated changes of S, N, and ORF9b proteins are crucial to high viral transmissibility. Our results provide new insights into high viral transmissibility co-modulated by advantageous noncoding and nonsynonymous changes.

Bibliometric Analysis of Hotspots and Frontiers of Immunotherapy in Pancreatic Cancer.

BACKGROUND: Pancreatic cancer is one of the most common malignant neoplasms with an increasing incidence, low rate of early diagnosis, and high degree of malignancy. In recent years, immunotherapy has made remarkable achievements in various cancer types including pancreatic cancer, due to the long-lasting antitumor responses elicited in the human body. Immunotherapy mainly relies on mobilizing the host's natural defense mechanisms to regulate the body state and exert anti-tumor effects. However, no bibliometric research about pancreatic cancer immunotherapy has been reported to date. This study aimed to assess research trends and offer possible new research directions in pancreatic cancer immunotherapy. METHODS: The articles and reviews related to pancreatic cancer immunotherapy were collected from the Web of Science Core Collection. CiteSpace, VOSviewer, and an online platform, and were used to analyze co-authorship, citation, co-citation, and co-occurrence of terms retrieved from the literature highlighting the scientific advances in pancreatic cancer immunotherapy. RESULTS: We collected 2475 publications and the number of articles was growing year by year. The United States had a strong presence worldwide with the most articles. The most contributing institution was Johns Hopkins University (103 papers). EM Jaffee was the most productive researcher with 43 papers, and L Zheng and RH Vonderheide ranked second and third, with 34 and 29 papers, respectively. All the keywords were grouped into four clusters: "immunotherapy", "clinical treatment study", "tumor immune cell expression", "tumor microenvironment". In the light of promising hotspots, keywords with recent citation bursts can be summarized into four aspects: immune microenvironment, adaptive immunotherapy, immunotherapy combinations, and molecular and gene therapy. CONCLUSIONS: In recent decades, immunotherapy showed great promise for many cancer types, so various immunotherapy approaches have been introduced to treat pancreatic cancer. Understanding the mechanisms of immunosuppressive microenvironment, eliminating immune suppression and blocking immune checkpoints, and combining traditional treatments will be hotspots for future research.

De-Linker-Enabled Exceptional Volumetric Acetylene Storage Capacity and Benchmark C2 H2 /C2 H4 and C2 H2 /CO2 Separations in Metal-Organic Frameworks.

An ideal adsorbent for separation requires optimizing both storage capacity and selectivity, but maximizing both or achieving a desired balance remain challenging. Herein, a de-linker strategy is proposed to address this issue for metal-organic frameworks (MOFs). Broadly speaking, the de-linker idea targets a class of materials that may be viewed as being intermediate between zeolites and MOFs. Its feasibility is shown here by a series of ultra-microporous MOFs (SNNU-98-M, M=Mn, Co, Ni, Zn). SNNU-98 exhibit high volumetric C2 H2 uptake capacity under low and ambient pressures (175.3 cm3 cm-3 @ 0.1 bar, 222.9 cm3 cm-3 @ 1 bar, 298 K), as well as extraordinary selectivity (2405.7 for C2 H2 /C2 H4 , 22.7 for C2 H2 /CO2 ). Remarkably, SNNU-98-Mn can efficiently separate C2 H2 from C2 H2 /CO2 and C2 H2 /C2 H4 mixtures with a benchmark C2 H2 /C2 H4 (1/99) breakthrough time of 2325 min g-1 , and produce 99.9999 % C2 H4 with a productivity up to 64.6 mmol g-1 , surpassing values of reported MOF adsorbents.

Rational regulation of acetylene adsorption and separation for ultra-microporous copper-1,2,4-triazolate frameworks by halogen hydrogen bonds.

It is well known that the introduction of exposed fluorine (F) sites into metal-organic frameworks (MOFs) can effectively promote acetylene (C2H2) adsorption via C-H⋯F hydrogen bonds. However, such super strong hydrogen bonding interactions usually lead to very high acetylene adsorption enthalpy and thus require more energy during the adsorbent regeneration process. As the same group elements, chlorine (Cl), bromine (Br) and iodine (I) also can act as hydrogen bond acceptors but with relatively weak forces. So, it is speculated that the decoration of Cl, Br or I sites on the pore surface of MOF adsorbents may enhance acetylene adsorption but with lower energy consumption. Herein, ultra-microporous MOFs constructed by Cu4X4 (X = Cl, Br, I) motifs and 1,2,4-triazolate linkers, namely, [Cu8X4(TRZ)4]n (TRZ = 3,5-diethyl-1,2,4-triazole or detrz for SNNU-313-X, and 3,5-dipropyl-1,2,4-triazole or dptrz for SNNU-314-X), provide an ideal platform to investigate the effect of C-H⋯X (X = Cl, Br, I) hydrogen bonding on C2H2 adsorption and purification performance. Benefiting from the small pore size and pore environment, the C2H2 uptake and separation properties of this series of MOFs are systematically regulated. Detailed gas adsorption results show that with the same organic linker, the C2H2 uptake and separation (C2H2/C2H4 and C2H2/CO2) performance decrease clearly with the electronegativity of halogen ions (SNNU-313-Cl > SNNU-313-Br > SNNU-313-I). With the same halogen ion, the gas adsorption decreases with the bulk of decorated alkyl groups (SNNU-313-Cl > SNNU-314-Cl). Remarkably, SNNU-313/314 series MOF adsorbents exhibit moderate C2H2 uptake capacity and high separation ability, but the C2H2 adsorption enthalpies are much lower than those of MOF materials with exposed F sites. Dynamic fixed-bed column breakthrough experiments and Grand Canonical Monte Carlo (GCMC) simulations further indicate the critical effects of halogen hydrogen bonds on acetylene adsorption and separation. Overall, this work demonstrated an effective regulation of acetylene adsorption and separation by rational C-H⋯X hydrogen bonding, which may provide a new route for the exploration of energy-efficient acetylene adsorbent materials.

Cis-eQTL Analysis and Functional Validation of Candidate Genes for Carcass Yield Traits in Beef Cattle.

Carcass yield traits are of considerable economic importance for farm animals, which act as a major contributor to the world's food supply. Genome-wide association studies (GWASs) have identified many genetic variants associated with carcass yield traits in beef cattle. However, their functions are not effectively illustrated. In this study, we performed an integrative analysis of gene-based GWAS with expression quantitative trait locus (eQTL) analysis to detect candidate genes for carcass yield traits and validate their effects on bovine skeletal muscle satellite cells (BSCs). The gene-based GWAS and cis-eQTL analysis revealed 1780 GWAS and 1538 cis-expression genes. Among them, we identified 153 shared genes that may play important roles in carcass yield traits. Notably, the identified cis-eQTLs of PON3 and PRIM2 were significantly (p < 0.001) enriched in previous GWAS loci for carcass traits. Furthermore, overexpression of PON3 and PRIM2 promoted the BSCs' proliferation, increased the expression of MYOD and downregulated the expression of MYOG, which indicated that these genes may inhibit myogenic differentiation. In contrast, PON3 and PRIM2 were significantly downregulated during the differentiation of BSCs. These findings suggested that PON3 and PRIM2 may promote the proliferation of BSCs and inhibit them in the pre-differentiation stage. Our results further contribute to the understanding of the molecular mechanisms of carcass yield traits in beef cattle.

Effect of NaNO2 Reductant Pretreatment on Low-Rank Coal Flotation.

As the reserves of high-quality coal resources in China are decreasing, it is imperative to improve the processing and comprehensive utilization of low-rank coal. In this study, NaNO2 was used for the flotation pretreatment test of the low-rank coal obtained from Majialiang, and the mechanism was discussed by contact angle analysis, zeta potential measurements, and XPS peak fitting analysis. The results showed that when the dosage of NaNO2 was 2000 g/t and the pretreatment time was 5 min, the flotation effect was the best, the ash contents of concentrate ash and tailings and the combustible recovery were 17.15, 37.12, and 42.23%, respectively; the combustible recovery increased by 12%. The contact angle, surface functional group content, and zeta potential measurements showed that with the change of NaNO2 dosage, the content of the hydrophobic functional group and the zeta potential value were consistent with the change of combustible recovery. The increase of hydrophobic functional groups can effectively enhance the hydrophobic interaction on the surface of the coal, which is conducive to the combination of collector and coal, and improve the efficiency of the collector. The NaNO2 pretreatment test can promote flotation efficiency, and the addition of reductant is an effective method for the flotation efficiency of low-rank coal in reducing oxygen-containing functional groups on the surface of low-rank coal to improve the poor floatability. In this study, the method of chemical pretreatment is put forward to provide a new idea for slime flotation.

A Deep Machine Learning-Based Assistive Decision System for Intelligent Load Allocation under Unknown Credit Status.

Nowadays, the banks are facing increasing business pressure in loan allocations, because more and more enterprises are applying for it and financial risk is becoming vaguer. To this end, it is expected to investigate effective autonomous loan allocation decision schemes that can provide guidance for banks. However, in many real-world scenarios, the credit status information of enterprises is unknown and needs to be inferred from business status. To handle such an issue, this paper proposes a two-stage loan allocation decision framework for enterprises with unknown credit status. And the proposal is named as TLAD-UC for short. For the first stage, the idea of deep machine learning is introduced to train a prediction model that can generate credit status prediction results for enterprises with unknown credit status. For the second stage, a dynamic planning model with both optimization objective and constraint conditions is established. Through such model, both the profit and risk of banks can be well described. Solving such a dynamic planning model via computer simulation programs, the optimal allocation schemes can be suggested.

Phase space partition with Koopman analysis.

Symbolic dynamics is a powerful tool to describe topological features of a nonlinear system, where the required partition, however, remains a challenge for some time due to the complications involved in determining the partition boundaries. In this article, we show that it is possible to carry out interesting symbolic partitions for chaotic maps based on properly constructed eigenfunctions of the finite-dimensional approximation of the Koopman operator. The partition boundaries overlap with the extrema of these eigenfunctions, the accuracy of which is improved by including more basis functions in the numerical computation. The validity of this scheme is demonstrated in well-known 1D and 2D maps.

SERS Hotspot Engineering by Aerosol Self-Assembly of Plasmonic Ag Nanoaggregates with Tunable Interparticle Distance.

Surface-enhanced Raman scattering (SERS) is a powerful sensing technique. However, the employment of SERS sensors in practical applications is hindered by high fabrication costs from processes with limited scalability, poor batch-to-batch reproducibility, substrate stability, and uniformity. Here, highly scalable and reproducible flame aerosol technology is employed to rapidly self-assemble uniform SERS sensing films. Plasmonic Ag nanoparticles are deposited on substrates as nanoaggregates with fine control of their interparticle distance. The interparticle distance is tuned by adding a dielectric spacer during nanoparticle synthesis that separates the individual Ag nanoparticles within each nanoaggregate. The dielectric spacer thickness dictates the plasmonic coupling extinction of the deposited nanoaggregates and finely tunes the Raman hotspots. By systematically studying the optical and morphological properties of the developed SERS surfaces, structure-performance relationships are established and the optimal hot-spots occur for interparticle distance of 1 to 1.5 nm among the individual Ag nanoparticles, as also validated by computational modeling, are identified for the highest signal enhancement of a molecular Raman reporter. Finally, the superior stability and batch-to-batch reproducibility of the developed SERS sensors are demonstrated and their potential with a proof-of-concept practical application in food-safety diagnostics for pesticide detection on fruit surfaces is explored.