Topologically Localized Vibronic Excitations in Second-Layer Graphene Nanoribbons.

It is of fundamental importance to characterize the intrinsic properties, like the topological end states, in the on-surface synthesized graphene nanoribbons (GNRs), but the strong electronic interaction with the metal substrate usually smears out their characteristic features. Here, we report our approach to investigate the vibronic excitations of the topological end states in self-decoupled second-layer GNRs, which are grown using an on-surface squeezing-induced spillover strategy. The vibronic progressions show highly spatially localized distributions at the second-layer GNR ends, which can be ascribed to the decoupling-extended lifetime of charging through resonant electron tunneling at the topological end states. In combination with theoretical calculations, we assign the vibronic progressions to specific vibrational modes that mediate the vibronic excitations. The spatial distribution of each resolved excitation shows evident characteristics beyond the conventional Franck-Condon picture. Our work by direct growth of second-layer GNRs provides an effective way to explore the interplay between the intrinsic electronic, vibrational, and topological properties.

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for clinical treatment. METHOD: The study population was collected from the national claims database in China. A total of 4,532 patients aged 4-18 who began risperidone therapy for mania between September 2013 and October 2019 were identified. The data were randomly divided into two datasets: training (80%) and testing (20%). Five regularly used machine learning methods were employed, in addition to the SuperLearner (SL) algorithm, to develop prediction models for the continuation of atypical antipsychotic therapy. The area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI) was utilized. RESULTS: In terms of discrimination and robustness in predicting risperidone treatment continuation, the generalized linear model (GLM) performed the best (AUC: 0.823, 95% CI: 0.792-0.854, intercept near 0, slope close to 1.0). The SL model (AUC: 0.823, 95% CI: 0.791-0.853, intercept near 0, slope close to 1.0) also exhibited significant performance. Furthermore, the present findings emphasize the significance of several unique clinical and socioeconomic variables, such as the frequency of emergency room visits for nonmental health disorders. CONCLUSIONS: The GLM and SL models provided accurate predictions regarding risperidone treatment continuation in children and adolescents with episodes of mania and hypomania. Consequently, applying prediction models in atypical antipsychotic medicine may aid in evidence-based decision-making.

Neuropathic pain has sex-specific effects on oxycodone-seeking and non-drug-seeking ensemble neurons in the dorsomedial prefrontal cortex of mice.

Approximately 50 million Americans suffer from chronic pain, and nearly a quarter of chronic pain patients have reported misusing opioid prescriptions. Repeated drug seeking is associated with reactivation of an ensemble of neurons sparsely scattered throughout the dorsomedial prefrontal cortex (dmPFC). Prior research has demonstrated that chronic pain increases intrinsic excitability of dmPFC neurons, which may increase the likelihood of reactivation during drug seeking. We tested the hypothesis that chronic pain would increase oxycodone-seeking behaviour and that the pain state would differentially increase intrinsic excitability in dmPFC drug-seeking ensemble neurons. TetTag mice self-administered intravenous oxycodone. After 7 days of forced abstinence, a drug-seeking session was performed, and the ensemble was tagged. Mice received spared nerve injury (SNI) to induce chronic pain during the period between the first and second seeking session. Following the second seeking session, we performed electrophysiology on individual neurons within the dmPFC to assess intrinsic excitability of the drug-seeking ensemble and non-ensemble neurons. SNI had no impact on sucrose seeking or intrinsic excitability of dmPFC neurons from these mice. In females, SNI increased oxycodone seeking and intrinsic excitability of non-ensemble neurons. In males, SNI had no impact on oxycodone seeking or neuron excitability. Data from females are consistent with clinical reports that chronic pain can promote drug craving and relapse and support the hypothesis that chronic pain itself may lead to neuroadaptations which promote opioid seeking.

[Correlation of environment temperature with the incidence of testicular torsion].

Objective： To explore the influence of environment temperature on the incidence of testicular torsion. METHODS: We collected the clinical data on 172 cases of testicular torsion diagnosed in the Second Hospital of Hebei Medical University from December 2013 to December 2020. According to the local environment temperature on the day of onset, we divided the patients into groups A (below 0℃), B (0－10℃), C (10－20℃) and D (above 20℃), and compared the incidence rates of testicular torsion among the four groups, followed by correlation analysis. RESULTS: The incidence rate of testicular torsion was 12.8% (n = 22) in group A, 35.5% (n = 61) in B, 34.9% (n = 60) in C and 16.9% (n = 29) in D, the highest at 0－10℃ in group B, with statistically significant difference among the four groups (χ2 = 29.07, P <0.001). Spearman correlation analysis indicated that the incidence of testicular torsion was negatively correlated with the environment temperature (r = －0.261, P <0.01), with no statistically significant difference among different seasons (χ2 = 5.349, P >0.05), but higher in autumn and winter than in the other two seasons. CONCLUSION: The incidence of testicular torsion is negatively correlated with the environment temperature, elevated when the temperature decreases, but has no statistically significant difference among different seasons, though relatively higher in autumn and winter.

Development of a machine learning-based model to predict major adverse events after surgery for type A aortic dissection complicated by malnutrition.

Objective: This study aims to develop a predictive model for the risk of major adverse events (MAEs) in type A aortic dissection (AAAD) patients with malnutrition after surgery, utilizing machine learning (ML) algorithms. Methods: We retrospectively collected clinical data from AAAD patients with malnutrition who underwent surgical treatment at our center. Through least absolute shrinkage and selection operator (LASSO) regression analysis, we screened for preoperative and intraoperative characteristic variables. Based on the random forest (RF) algorithm, we constructed a ML predictive model, and further evaluated and interpreted this model. Results: Through LASSO regression analysis and univariate analysis, we ultimately selected seven feature variables for modeling. After comparing six different ML models, we confirmed that the RF model demonstrated the best predictive performance in this dataset. Subsequently, we constructed a model using the RF algorithm to predict the risk of postoperative MAEs in AAAD patients with malnutrition. The test set results indicated that this model has excellent predictive efficacy and clinical applicability. Finally, we employed the Shapley additive explanations (SHAP) method to further interpret the predictions of this model. Conclusion: We have successfully constructed a risk prediction model for postoperative MAEs in AAAD patients with malnutrition using the RF algorithm, and we have interpreted the model through the SHAP method. This model aids clinicians in early identification of high-risk patients for MAEs, thereby potentially mitigating adverse clinical outcomes associated with malnutrition.

Glutathione-activated biotin-targeted dual-modal imaging probe with improved PDT/PTT synergistic therapy.

BACKGROUND: Glutathione (GSH), a highly abundant thiol compound within cells, plays a critical role in physiological processes and exhibits close correlation with cancer. Among molecular imaging technologies, most probes have relatively short emission wavelengths and lack photoacoustic imaging (PA) capability, resulting in the inability to obtain tissue images with high penetration depth. The presence of GSH in the tumor microenvironment neutralizes ROS, diminishing the therapeutic effect of PDT, thus resulting in often unsatisfactory therapeutic efficacy. Therefore, it is imperative to develop a dual-modal probe for the detection of GSH and the diagnosis and treatment of cancer. RESULTS: In this study, we synthesized a novel dual-modal probe, Cy-Bio-GSH, utilizing near-infrared fluorescence (NIRF) and photoacoustic (PA) imaging techniques for GSH detection. The probe integrates cyanine dye as the fluorophore, nitroazobenzene as the recognition moiety, and biotin as the tumor-targeting moiety. Upon reacting with GSH, the probe emits NIR fluorescence at 820 nm and generates a PA signal. Significantly, this reaction activates the photodynamic and photothermal properties of the probe. By depleting GSH and employing a synergistic photothermal therapy (PTT) treatment, the therapeutic efficacy of photodynamic therapy (PDT) is remarkably enhanced. In-vivo experiments confirm the capability of the probe to detect GSH via NIRF and PA imaging. Notably, the combined tumor-targeting ability and PDT/PTT synergistic therapy enhance therapeutic outcomes for tumors and facilitate their ablation. SIGNIFICANCE: A novel tumor-targeting and dual-modal imaging probe (Cy-Bio-GSH) is synthesized, exhibiting remarkable sensitivity and selectivity to GSH, enabling the visualization of GSH in cells and the differentiation between normal and cancer cells. Cy-Bio-GSH enhances PDT/PTT with effective killing of cancer cells and makes the ablation of tumors in mice. This work represents the first tumor-targeting probe for GSH detection, and provides crucial tool for cancer diagnosis and treatment by dual-modal imaging with improved PDT/PTT synergistic therapy.

Risk prediction and prognostic analysis of post-implantation syndrome after thoracic endovascular aortic repair.

This study aimed to establish a predictive model for the risk of post-thoracic endovascular aortic repair (TEVAR) post-implantation syndrome (PIS) in type B aortic dissection (TBAD) patients, assisting clinical physicians in early risk stratification and decision management for high-risk PIS patients. This study retrospectively analyzed the clinical data of 547 consecutive TBAD patients who underwent TEVAR treatment at our hospital. Feature variables were selected through LASSO regression and logistic regression analysis to construct a nomogram predictive model, and the model's performance was evaluated. The optimal cutoff value for the PIS risk nomogram score was calculated through receiver operating characteristic (ROC) curve analysis, further dividing patients into high-risk group (HRG) and low-risk group (LRG), and comparing the short to midterm postoperative outcomes between the two groups. In the end, a total of 158 cases (28.9%) experienced PIS. Through LASSO regression analysis and multivariable logistic regression analysis, variables including age, emergency surgery, operative time, contrast medium volume, and number of main prosthesis stents were selected to construct the nomogram predictive model. The model achieved an area under the curve (AUC) of 0.86 in the training set and 0.82 in the test set. Results from calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated that the predictive model exhibited good performance and clinical utility. Furthermore, after comparing the postoperative outcomes of HRG and LRG patients, we found that the incidence of postoperative PIS significantly increased in HRG patients. The duration of ICU stay and mechanical assistance time was prolonged, and the incidence of postoperative type II entry flow and acute kidney injury (AKI) was higher. The risk of aortic-related adverse events (ARAEs) and major adverse events (MAEs) at the first and twelfth months of follow-up also significantly increased. However, there was no significant difference in the mortality rate during hospitalization. This study established a nomogram model for predicting the risk of PIS in patients with TBAD undergoing TEVAR. It serves as a practical tool to assist clinicians in early risk stratification and decision-making management for patients.

Orthogonal magnetic orbitals in high spin Cu-VO units: structure, magnetism and EPR study of anisotropic heterometallic complexes.

Molecular-based magnetic materials are expected to serve as building blocks for quantum bits. To realize high-dimensional Hilbert space and addressability, we constructed anisotropic multi-level systems based on CuII and VIV with orthogonal magnetic orbitals. The crystal structures and intramolecular magnetic couplings of four CuIIVOII complexes [{CuVO(appen)2}2], [{CuVO(fhma)2EDA}2], [{CuVO(hfca)2EDA}2] and [CuVO(hfca)2DPEDA]n are characterized. Due to the orthogonal magnetic orbitals of CuII and VIV, the Cu-V pairs in the four complexes have strong ferromagnetic couplings, and the coupling strength is linearly related to the dihedral angle between the two equatorial planes of the two coordination polyhedra. Because of the triplet ground state, the system can be described by an effective Hamiltonian model consisting of two S = 1 spins coupled together. The anisotropy parameters of [{CuVO(hfca)2EDA}2] and [CuVO(hfca)2DPEDA]n were obtained by the simulation of X-band continuous wave electron paramagnetic resonance (cw-EPR) spectra, confirming that both complexes have zero-field splitting addressable on the relative energy scale. The results indicate that constructing multi-centre complexes based on orthogonal magnetic orbitals is a promising strategy for designing multidimensional quantum bits.

Double domain fusion improves the reverse transcriptase activity and inhibitor tolerance of Bst DNA polymerase.

To enhance the DNA/RNA amplification efficiency and inhibitor tolerance of Bst DNA polymerase, four chimeric Bst DNA polymerase by fusing with a DNA-binding protein Sto7d and/or a highly hydrophobic protein Hp47 to Bst DNA polymerase large fragment. One of chimeric protein HpStBL exhibited highest inhibitor tolerance, which retained high active under 0.1 U/µL sodium heparin, 0.8 ng/µL humic acid, 2.5× SYBR Green I, 8 % (v/v) whole blood, 20 % (v/v) tissue, and 2.5 % (v/v) stool. Meanwhile, HpStBL showed highest sensitivity (93.75 %) to crude whole blood infected with the African swine fever virus. Moreover, HpStBL showed excellent reverse transcriptase activity in reverse transcription loop-mediated isothermal amplification, which could successfully detect 0.5 pg/µL severe acute respiratory syndrome coronavirus 2 RNA in the presence of 1 % (v/v) stools. The fusion of two domains with different functions to Bst DNA polymerase would be an effective strategy to improve Bst DNA polymerase performance in direct loop-mediated isothermal amplification and reverse transcription loop-mediated isothermal amplification detection, and HpStBL would be a promising DNA polymerase for direct African swine fever virus/severe acute respiratory syndrome coronavirus 2 detection due to simultaneously increased inhibitor tolerance and reverse transcriptase activity.

The nuclear and mitochondrial genome assemblies of Tetragonisca angustula (Apidae: Meliponini), a tiny yet remarkable pollinator in the Neotropics.

BACKGROUND: The field of bee genomics has considerably advanced in recent years, however, the most diverse group of honey producers on the planet, the stingless bees, are still largely neglected. In fact, only eleven of the ~ 600 described stingless bee species have been sequenced, and only three using a long-read (LR) sequencing technology. Here, we sequenced the nuclear and mitochondrial genomes of the most common, widespread and broadly reared stingless bee in Brazil and other neotropical countries-Tetragonisca angustula (popularly known in Brazil as jataí). RESULTS: A total of 48.01 Gb of DNA data were generated, including 2.31 Gb of Pacific Bioscience HiFi reads and 45.70 Gb of Illumina short reads (SRs). Our preferred assembly comprised 683 contigs encompassing 284.49 Mb, 62.84 Mb of which (22.09%) corresponded to 445,793 repetitive elements. N50, L50 and complete BUSCOs reached 1.02 Mb, 91 contigs and 97.1%, respectively. We predicted that the genome of T. angustula comprises 17,459 protein-coding genes and 4,108 non-coding RNAs. The mitogenome consisted of 17,410 bp, and all 37 genes were found to be on the positive strand, an unusual feature among bees. A phylogenomic analysis of 26 hymenopteran species revealed that six odorant receptor orthogroups of T. angustula were found to be experiencing rapid evolution, four of them undergoing significant contractions. CONCLUSIONS: Here, we provided the first nuclear and mitochondrial genome assemblies for the ecologically and economically important T. angustula, the fourth stingless bee species to be sequenced with LR technology thus far. We demonstrated that even relatively small amounts of LR data in combination with sufficient SR data can yield high-quality genome assemblies for bees.

The complete mitochondrial genome of Zaomma eriococci (hymenoptera: encyrtidae).

The complete mitochondrial genome of the Zaomma eriococci (Ferrière, 1955) (Hymenoptera: Encyrtidae) was obtained through next-generation sequencing, making the first reported complete mitochondrial genome of the genus Zaomma. The mitochondrial genome is 15,648 bp in length and includes 37 classical eukaryotic mitochondrial genes along with an A + T rich region. All 13 protein-coding genes (PCGs) initiate with typical ATN codons. Of these, 10 PCG genes terminate with TAA, while three terminate with TAG. Additionally, there are 22 tRNA genes, ranging in size from 62 to 70 bp. The maximum likelihood phylogenetic tree was constructed based on 13 PCGs, indicates that Z. eriococci is closely related to Tassonia gloriae. This mitochondrial genome will serve as a valuable molecular resource for species identification, genetic analysis, and comparative genomic studies of Z. eriococci, contributing to the growing collection of mitochondrial genomes within the family Encyrtidae.

[Research Advances of Groundwater Nitrate Pollution and Source Apportionment in China].

Groundwater nitrate (NO3-) contamination in China has become a serious environmental problem, especially in agricultural production areas, which greatly affects the safety of drinking groundwater and requires urgent attention. In this study, the main sources of groundwater nitrate in China were reviewed, including atmospheric deposition, soil nitrogen, agricultural fertilization, and fecal sewage, among which fecal sewage and agricultural fertilization were the main reasons for the excessive groundwater nitrate. The application of hydrochemical analysis, multivariate statistical analysis, stable isotope tracer method, and microbial source tracking in the source apportionment of groundwater nitrate was summarized. All types of source apportionment methods had certain limitations. It is suggested that a variety of methods should be used to identify the source of groundwater nitrate, and the contribution rate of different pollution sources should be calculated using multivariate statistical analysis and isotope quantitative analysis models. The source apportionment of nitrate pollution has undergone a process from qualitative to quantitative research. At present, the SIAR and MixSIAR models based on δ15N-NO3-and δ18O-NO3- have been used widely to analyze the source of nitrate. However, due to the overlap of isotope characteristic values of different input end-members, the difference in δ15N-NO3-and δ18O-NO3- values under different spatial and temporal changes, and the influence of isotope fractionation in the process of nitrogen migration and transformation, the results calculated by the model remain uncertain. It is necessary to further optimize the analytical method of the model to obtain the source of nitrate pollution and its contribution rate more accurately to further aid in the scientific management of groundwater resources.

[Effect of Integrated Landscape Characteristics Around Chaohu Lake on River Water Quality Based on Watershed Units].

Considering the impact of differences in watershed characteristics on river water quality, with the Chaohu Lake Basin as the research object, based on the data of water quality, meteorology, topography, soil, and remote sensing images of the river monitoring points from October 2019 to September 2020, the watershed unit at each monitoring point was divided through digital terrain analysis, and the comprehensive landscape characteristics based on the watershed unit were explored through the comprehensive use of correlation analysis, redundancy analysis, and multiple regression analysis to investigate the influence of comprehensive landscape characteristics based on watershed units (including land use, climate, topography, soil, etc.) on the water quality of rivers around Chaohu Lake. The results showed that:① the water quality of rivers around Chaohu Lake had large spatial differences, with the main pollutants being total nitrogen and ammonia nitrogen. Most of the rivers had total nitrogen concentrations exceeding the Class V water quality standards, and the areas with serious nitrogen and phosphorus pollution were concentrated in the urban area of Hefei and the surrounding rivers, as well as in the middle and lower reaches of the Fengle and Hangbu Rivers. ② The comprehensive landscape characteristics of the watershed unit had a significant impact on the river water quality. Among them, the proportion of built-up land, the density of patches, the dispersion and juxtaposition index, and the Shannon diversity index were positively correlated with the water quality indicators, whereas the proportion of forest and grassland and the spreading index were negatively correlated with the water quality indicators. ③ In different seasons, the effect of the integrated landscape characteristics of the watershed unit on river water quality was stronger in the wet season than in the dry season, which was mainly caused by the difference in precipitation in the dry and wet seasons.

Clinical predictive value of the age, creatinine, and ejection fraction score in patients in acute type A aortic dissection after total arch replacement.

The age, creatinine, and ejection fraction (ACEF) score has been accepted as a predictor of poor outcome in elective operations. This study aimed to investigate the predictive value of ACEF score in acute type A aortic dissection (AAAD) patients after total arch replacement. A total of 227 AAAD patients from July 2021 and June 2022 were enrolled and divided into Tertiles 1 (ACEF ≤ 0.73), Tertiles 2 (0.73 < ACEF ≤ 0.95), and Tertiles 3 (ACEF > 0.95). Using inverse probability processing weighting (IPTW) to balance the baseline characteristics and compare the outcomes. Cox logistic regression was used to further evaluate the survival prediction ability of ACEF score. The in-hospital mortality was 9.8%. After IPTW, in the baseline characteristics reached an equilibrium, a higher ACEF score before operation still associated with higher in-hospital mortality. After 1 year follow-up, 184 patients (90.6%) survival. Multivariable analysis revealed that ACEF score (adjusted hazard ratio 1.68; 95% confidence interval 1.34-4.91; p = 0.036) and binary ACEF score (adjusted HR 2.26; 95% CI 1.82-6.20; p < 0.001) was independently associated with 1-year survival. In addition, net reclassification improvement (NRI) and integrated differentiation improvement (IDI) verified that the ACEF score and binary ACEF score is an accurate predictive tool in clinical settings. In conclusions, ACEF score could be considered as a useful tool to risk stratification in patients with AAAD before operation in daily clinical work.

The prognostic value of preoperative systemic inflammatory response index in predicting outcomes of acute type A aortic dissection patients underwent surgical treatment.

Background: The systemic inflammatory response index (SIRI) is a novel inflammatory-immune biological marker that has prognostic value in various cardiovascular diseases. This study aims to investigate the relationship between SIRI and short-term and long-term prognosis in patients with acute type A aortic dissection (AAAD) underwent surgical treatment. Methods: We conducted a retrospective analysis of patients with AAAD who underwent emergency surgical treatment at our center. Through multifactorial logistics regression analysis and cox proportional hazards regression analysis, we identified SIRI as an independent risk factor for major adverse events (MAEs) and long-term aorta-related adverse events (ARAEs) post-surgery. The optimal cutoff value of preoperative SIRI was determined using receiver operating characteristic (ROC) curve analysis, and patients were divided into low SIRI group and high SIRI group. The prognostic outcomes at different time points post-surgery for the two groups of patients were analyzed using Kaplan-Meier survival analysis, and the significance was determined by log-rank test. Results: A total of 691 AAAD patients were included in this study. Among them, 50 patients (7.2%) died within 30 days post-surgery, and 175 patients (25.3%) experienced MAEs. A total of 641 patients were followed up, with an average follow-up time of 33.5 ± 17.5 months, during which 113 patients (17.6%) experienced ARAEs. The results of multifactorial logistics regression analysis and cox proportional hazards regression analysis showed that SIRI was an independent risk factor for postoperative MAEs (OR=3.148, 95%CI[1.650-6.006], p<0.001) and ARAEs (HR=2.248, 95%CI[1.050-4.809], p<0.037). Kaplan-Meier analysis demonstrated that the MAEs-free survival in the high SIRI group was significantly lower than that in the low SIRI group, and a similar trend was observed in the ARAEs-free survival during follow-up (log-rank test, p<0.001). Conclusion: Preoperative SIRI is significantly associated with the short-term and long-term prognosis of AAAD patients underwent emergency open surgery, demonstrating its valuable prognostic value. Therefore, preoperative SIRI is a reliable biological marker that can serve as a valuable tool for preoperative risk stratification and decision management.

Minimalistic approach to left atrial appendage occlusion guided by cardiac computed tomography angiography.

OBJECTIVE: To assess the feasibility and safety of the minimalistic approach to left atrial appendage occlusion (LAAO) guided by cardiac computed tomography angiography (CCTA). METHODS: Ninety consecutive patients who underwent LAAO, with or without CCTA-guided, were matched (1:2). Each step of the LAAO procedure in the computed tomography (CT) guidance group (CT group) was directed by preprocedural CT planning. In the control group, LAAO was performed using the standard method. All patients were followed up for 12 months, and device surveillance was conducted using CCTA. RESULTS: A total of 90 patients were included in the analysis, with 30 patients in the CT group and 60 matched patients in the control group. All patients were successfully implanted with Watchman devices. The mean ages for the CT group and the control group were 70.0 ± 9.4 years and 68.4 ± 11.9 years (P = 0.52), respectively. The procedure duration (45.6 ± 10.7 min vs. 58.8 ± 13.0 min, P < 0.001) and hospital stay (7.5 ± 2.4 day vs. 9.6 ± 2.8 day, P = 0.001) in the CT group was significantly shorter compared to the control group. However, the total radiation dose was higher in the CT group compared to the control group (904.9 ± 348.0 mGy vs. 711.9 ± 211.2 mGy, P = 0.002). There were no significant differences in periprocedural pericardial effusion (3.3% vs. 6.3%, P = 0.8) between the two groups. The rate of postprocedural adverse events (13.3% vs. 18.3%, P = 0.55) were comparable between both groups at 12 months follow-up. CONCLUSIONS: CCTA is capable of detailed LAAO procedure planning. Minimalistic LAAO with preprocedural CCTA planning was feasible and safe, with shortened procedure time and acceptable increased radiation and contras consumption. For patients with contraindications to general anesthesia and/or transesophageal echocardiography, this promising method may be an alternative to conventional LAAO.

[Modified QuEChERS method combined with ultra performance liquid chromatography-tandem mass spectrometry for detection of cyclopiazonic acid in feeds].

Mycotoxins are toxic secondary metabolites produced by fungal species that can cause acute, subacute, and chronic toxicity in humans and animals. Thus, these toxins pose a significant threat to health and safety. Owing to the lack of effective antimold measures in the agricultural industry, feed ingredients such as corn, peanuts, wheat, barley, millet, nuts, oily feed, forage, and their byproducts are prone to mold and mycotoxin contamination, which can affect animal production, product quality, and safety. Cyclopiazonic acid (CPA), which is mainly biosynthesized from mevalonate, tryptophan, and diacetate units, is a myotoxic secondary metabolite produced by Penicillium and Aspergillus fungi. CPA is widely present as a copollutant with aflatoxins in various crops. Compared with some common mycotoxins such as aflatoxins, fumonisins, ochratoxins, zearalenones, and their metabolites, CPA has not been well investigated. In the United States, a survey showed that 51% of corn and 90% of peanut samples contained CPA, with a maximum level of 2.9 mg/kg. In Europe, CPA was found in Penicillium-contaminated cheeses as high as 4.0 mg/kg. Some studies have shown that CPA can cause irreversible damage to organs such as the liver and spleen in mice. Therefore, the establishment of a rapid and efficient analytical method for CPA is of great significance for the risk assessment of CPA in feeds, the development of standard limits, and the protection of feed product quality and safety. The QuEChERS method, a sample pretreatment method that is fast, simple, cheap, effective, and safe, is widely used in the analysis of pesticide residues in food. In this study, a modified QuEChERS method combined with ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to determine CPA levels in feeds. The chromatographic separation and MS detection of CPA as well as the key factors affecting the extraction efficiency of CPA, including the type of extraction solvent, type of inorganic salt, and type and dosage of adsorbent, were optimized in detail. During the optimization of the chromatographic-separation step, the acid and salt concentrations of the mobile phase affected the separation and detection of CPA. During the optimization of the QuEChERS method, the addition of a certain amount of acetic acid improved the extraction efficiency of CPA because of its acidic nature; in addition, GCB and PSA significantly adsorbed CPA from the feed extract. Under optimal conditions, the CPA in the feed sample (1.0 g) was extracted with 2 mL of water and 4 mL of acetonitrile (ACN) containing 0.5% acetic acid. After salting out with 0.4 g of NaCl and 1.6 g of MgSO4, 1 mL of the ACN supernatant was purified by dispersive solid-phase extraction using 150 mg of MgSO4 and 50 mg of C18 and analyzed by UPLC-MS/MS. The sample was separated on a Waters HSS T3 column (100 mm×2.1 mm, 1.8 µm) using 2 mmol/L ammonium acetate aqueous solution with 0.5% formic acid and ACN as the mobile phases and then analyzed by positive electrospray ionization in multiple reaction monitoring mode. CPA exhibited good linearity in the range of 2-200 ng/mL, with a high correlation coefficient (r=0.9995). The limits of detection and quantification of CPA, which were calculated as 3 and 10 times the signal-to-noise ratio, respectively, were 0.6 and 2.0 µg/kg, respectively. The average recoveries in feed samples spiked with 10, 100, and 500 µg/kg CPA ranged from 70.1% to 78.5%, with an intra-day precision of less than 5.8% and an inter-day precision of less than 7.2%, indicating the good accuracy and precision of the proposed method. Finally, the modified QuEChERS-UPLC-MS/MS method was applied to the analysis of CPA in 10 feed samples obtained from Wuhan market. The analysis results indicated that the developed method has good applicability for CPA analysis in feed samples. In summary, an improved QuEChERS method was applied to the extraction and purification of CPA from feeds for the first time; this method provides a suitable analytical method for the risk monitoring, assessment, and standard-limit setting of CPA in feed samples.

Glass-Blowing-Inspired Upcycling of Thermosetting Polymer to Neuron-Like Hierarchical Carbon for Microwave Absorption and Conversion.

Upgrading thermosetting polymer waste and harvesting unwanted electromagnetic energy are of great significance in solving environmental pollution and energy shortage problems. Herein, inspired by the glass-blowing art, a spontaneous, controllable, and scalable strategy is proposed to prepare hollow carbon materials by inner blowing and outside blocking. Specifically, hierarchically neuron-like hollow carbon materials (HCMSs) with various sizes are fabricated from melamine-formaldehyde sponge (MS) waste. Benefiting from the synergistic of the hollow "cell body" and the connected "protrusions" networks, HCMSs reveal superior electromagnetic absorption performance with a strong reflection loss of -54.9 dB, electromagnetic-heat conversion ability with a high conversion efficiency of 34.4%, and efficient energy storage performance in supercapacitor. Furthermore, a multifunctional device integrating electromagnetic-heat-electrical energy conversion is designed, and its feasibility is proved by experiments and theoretical calculations. The integrated device reveals an output voltage of 34.5 mV and a maximum output power of 0.89 µW with electromagnetic radiation for 60 s. This work provides a novel solution to recycle polymer waste, electromagnetic energy, and unwanted thermal energy.