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Methane synthesis from CO2 is an important process for transforming and storing renewable electrical energy, and one of the main issues facing methanation catalysts is stability. Herein, a plate-and-tube structured porous metal-ceramic Ni-YSZ reactor with high-temperature sintering was designed to produce CH4 from CO2 at atmospheric pressure and 325°C. The reactor was steadily operated for 1000 hours. The results showed that both the CO2 conversion and the CH4 selectivity continuously stayed over 90 % and 99.9 %, respectively. The results of in situ infrared and in situ programmed warming characterizations demonstrated that the hydrogenation of oxygen vacancies on the surface of Ni-O-Zr was the main pathway by which CO2 was converted to CH4 in this reactor. Moreover, the strongly basic adsorbed HCOO* and CO* intermediates facilitated further hydrogenation. This reactor structure decreases the reduction in reaction activity associated with catalyst sintering, coalescence, and carbon accumulation. Moreover, it provides a novel approach to reactor design for the stable operation of CO2-derived methane at high temperatures.

ABSTRACTThe oil content, fatty acid, oil quality and oxidation stability of seeds of four woody oil plants (pecan, Camellia oleifera, Torreya grandis and walnut) were analyzed. The results showed that pecan oil had the strongest antioxidant activity, the variation range of FFA, peroxide value(PV), UV absorption, carbonyl value(CV) and OSI were the lowest; C. oleifera oil and T. grandis oil were the next, and walnut oil had the greatest variation range; besides, pecan oil contained higher tocopherol and total phenol(TP) content. Correlation analysis showed that, OSI was significantly positively correlated with OA, tocopherol and TP, and significantly negatively correlated with PA, LA, LOA and PV. The oxidation stability from superior to inferior is pecan oil, C. oleifera oil, T. grandis oil and walnut oil. Meanwhile, the oil content of pecan kernel was the highest, the fatty acid composition of pecan oil fulfills human dietary needs, it’s an high-quality edible oil.Abbreviations: PA: palmitic acid; POA: palmitoleic acid; SA: stearic acid; OA: oleic acid; LA: linoleic acid; LOA: linolenic acid; AA: arachidic acid; EA: cis-11-eicosenoic acid; UFA: unsaturated fatty acid;SFA: saturated fatty acid; FFA: free fatty acid; PV: peroxide value; CV: carbonyl value; TP: total phenols; OSI: oil stability index; UV: ultraviolet.

Abstract Background Camellia oleifera, an essential woody oil tree in China, propagates through grafting. However, in production, it has been found that the interaction between rootstocks and scions may affect fruit characteristics. Therefore, it is necessary to predict fruit characteristics after grafting to identify suitable rootstock types. Methods This study used Deep Neural Network (DNN) methods to analyze the impact of 106 6-year-old grafting combinations on the characteristics of C.oleifera, including fruit and seed characteristics, and fatty acids. The prediction of characteristics changes after grafting was explored to provide technical support for the cultivation and screening of specialized rootstocks. After determining the unsaturated fat acids, palmitoleic acid C16:1, cis-11 eicosenoic acid C20:1, oleic acid C18:1, linoleic acid C18:2, linolenic acid C18:3, kernel oil content, fruit height, fruit diameter, fresh fruit weight, pericarp thickness, fresh seed weight, and the number of fresh seeds, the DNN method was used to calculate and analyze the model. The model was screened using the comprehensive evaluation index of Mean Absolute Error (MAPE), determinate correlation R 2 and and time consumption. Results When using 36 neurons in 3 hidden layers, the deep neural network model had a MAPE of less than or equal to 16.39% on the verification set and less than or equal to 13.40% on the test set. Compared with traditional machine learning methods such as support vector machines and random forests, the DNN method demonstrated more accurate predictions for fruit phenotypic characteristics, with MAPE improvement rates of 7.27 and 3.28 for the 12 characteristics on the test set and maximum R 2 improvement values of 0.19 and 0.33. In conclusion, the DNN method developed in this study can effectively predict the oil content and fruit phenotypic characteristics of C. oleifera, providing a valuable tool for predicting the impact of grafting combinations on the fruit of C. oleifera.

IntroductionAccurately and objectively quantifying the clinical features of Parkinson's disease (PD) is crucial for assisting in diagnosis and guiding the formulation of treatment plans. Therefore, based on the data on multi-site motor features, this study aimed to develop an interpretable machine learning (ML) model for classifying the “OFF” and “ON” status of patients with PD, as well as to explore the motor features that are most associated with changes in clinical symptoms.MethodsWe employed a support vector machine with a recursive feature elimination (SVM-RFE) algorithm to select promising motion features. Subsequently, 12 ML models were constructed based on these features, and we identified the model with the best classification performance. Then, we used the SHapley Additive exPlanations (SHAP) and the Local Interpretable Model agnostic Explanations (LIME) methods to explain the model and rank the importance of those motor features.ResultsA total of 96 patients were finally included in this study. The naive Bayes (NB) model had the highest classification performance (AUC = 0.956; sensitivity = 0.8947, 95% CI 0.6686–0.9870; accuracy = 0.8421, 95% CI 0.6875–0.9398). Based on the NB model, we analyzed the importance of eight motor features toward the classification results using the SHAP algorithm. The Gait: range of motion (RoM) Shank left (L) (degrees) [Mean] might be the most important motor feature for all classification horizons.ConclusionThe symptoms of PD could be objectively quantified. By utilizing suitable motor features to construct ML models, it became possible to intelligently identify whether patients with PD were in the “ON” or “OFF” status. The variations in these motor features were significantly correlated with improvement rates in patients' quality of life. In the future, they might act as objective digital biomarkers to elucidate the changes in symptoms observed in patients with PD and might be used to assist in the diagnosis and treatment of patients with PD.

Camellia chekiangoleosa Hu. is a unique woody oil tree with significant economic and ornamental value in China, but the fruit is easily sunburned in low-altitude areas. However, few studies on their sunburn mechanism, especially the types and content of endogenous hormones with stress resistance, have not been reported, making it challenging to take reasonable preventive measures. Here, we analyzed the endogenous hormones before sunburn and found that salicylic acid (SA) and gibberellins (GAs) were very significantly correlated between pericarp and seed kernel. However, there weren't closely related to abscisic acid (ABA), auxin, jasmonic acids (JAs), and cytokinin. The content of indole-3-carboxylic acid (ICA) and 3-indolebutyric acid (IBA) in the pericarp was higher than in seed kernel, and IBA was only found in the pericarp. GAs in seed kernel were higher than that in pericarp, and GA3 and GA15 may regulate pericarp development. Contents of trans-Zeatin (tZ), indole-3-acetic acid (IAA), and GAs in seed kernel and pericarp gradually decreased to very low, while ABA and indole-3-carboxaldehyde (ICAld) gradually increased. SA was positively correlated with ABA in pericarp and GAs and SA in seed kernel and pericarp. JAs in fruit generally showed a downward trend, and methyl jasmonate (ME-JA) appeared in pericarp.

Abstract Background Camellia oleifera (C.oleifera) is one of the most important wood oil species in the world. C.oleifera was propagated by nurse seedling grafting. Since the morphology of rootstocks has a significant impact on grafting efficiency and seedling quality, it is necessary to understand the molecular mechanism of morphogenesis for cultivating high-quality and controllable rootstocks. However, the genomic resource for this species is relatively limited, which hinders us from fully understanding the molecular mechanisms of seed germination in C.oleifera. Results In this paper, using transcriptome sequencing, we measured the gene expression in the C.oleifera cotyledon in different stages of development and the global gene expression profiles. Approximately 45.4 gigabases (GB) of paired-end clean reads were assembled into 113,582 unigenes with an average length of 396 bp. Six public protein databases annotate 61.5% (68,217) of unigenes. We identified 11,391 differentially expressed genes (DEGs) throughout different stages of germination. Enrichment analysis revealed that DEGs were mainly involved in hormone signal transduction and starch sucrose metabolism pathways. The gravitropism regulator UNE10, the meristem regulators STM, KNAT1, PLT2, and root-specific transcription factor WOX11 all have higher gene expression levels in the CAM2 stage (seed soaking), which indicates that the cotyledon-regulated program for germination had initiated when the seeds were imbibition. Our data showed differentially reprogrammed to multiple hormone-related genes in cotyledons during C.oleifera seed germination. Conclusion Cotyledons play vital roles, both as the main nutrient provider and as one primary instructor for seed germination and seedling growth. Together, our study will significantly enrich the genomic resources of Camellia and help us understand the molecular mechanisms of the development in the seed germination and seedling growth of C.oleifera. It is helpful to culture standard and superior quality rootstock for C.oleifera breeding.

Abstract Background As a perennial crop, oil-Camellia possesses a long domestication history and produces high-quality seed oil that is beneficial to human health. Camellia oleifera Abel. is a sister species to the tea plant, which is extensively cultivated for edible oil production. However, the molecular mechanism of the domestication of oil-Camellia is still limited due to the lack of sufficient genomic information. Results To elucidate the genetic and genomic basis of evolution and domestication, here we report a chromosome-scale reference genome of wild oil-Camellia (2.95 Gb), together with transcriptome sequencing data of 221 cultivars. The oil-Camellia genome, assembled by an integrative approach of multiple sequencing technologies, consists of a large proportion of repetitive elements (76.1%) and high heterozygosity (2.52%). We construct a genetic map of high-density corrected markers by sequencing the controlled-pollination hybrids. Genome-wide association studies reveal a subset of artificially selected genes that are involved in the oil biosynthesis and phytohormone pathways. Particularly, we identify the elite alleles of genes encoding sugar-dependent triacylglycerol lipase 1, β-ketoacyl-acyl carrier protein synthase III, and stearoyl-acyl carrier protein desaturases; these alleles play important roles in enhancing the yield and quality of seed oil during oil-Camellia domestication. Conclusions We generate a chromosome-scale reference genome for oil-Camellia plants and demonstrate that the artificial selection of elite alleles of genes involved in oil biosynthesis contributes to oil-Camellia domestication.

Seminal roots play an important role in acquisition of water and nutrients by maize seedlings. Compared with its teosinte ancestor, maize underwent a change in seminal root number (SRN). Although several key genes controlling SRN have been cloned, identification and utilization of new genes from teosinte would be useful for improving maize root architecture. In this study, a maize-teosinte BC2F6 population containing 206 individuals genotyped by resequencing was used to conduct high-resolution quantitative trait locus (QTL) mapping of SRN. A new major QTL on chromosome 7 (qSRN7) was identified. Differentially expressed genes (DEGs) based on RNA-Seq were identified between two inbred lines with no SRN and multiple SRN at two periods of seminal roots primordia formation. A total of 116 DEGs detected in at least one period were identified within the qSRN7 interval. Three DEGs (Zm00001d021572, Zm00001d021579 and Zm00001d021861) associated with SRN were identified through regional association mapping. When compared with reported domestication-related selective sweeps, Zm00001d021572 was selected during maize domestication. Our findings provide important insights into the genetic basis of SRN and identify a promising candidate gene for further studies on SRN.

Camellia oleifera is one of the essential wood oil trees in the world. C.oleifera was propagated by nurse seedling grafting. Since the scion of C.oleifera had a significant regulated effect on the properties of rootstock after grafting and impacted on the growth of the grafted seedlings, it was necessary to understand the characteristics of buds among varieties to cultivate high-quality grafted seedlings. The metabolome was thought to be a powerful tool for understanding connecting phenotype-genotype interactions, which has an important impact on plant growth and development. In this study, UPLC-MS was used to determine the metabolites of the apical buds of CL3, CL4, CL40, and CL53 spring shoots after 30 days of sprout and to measure the growth characteristics of roots and stems after grafting. Metabolomics analysis revealed 554 kinds of metabolites were significant differences among four varieties, and 29 metabolic pathways were identified to have significant changes (p< 0.05), including carboxylic acids and derivatives, fatty Acyls, organooxygen compounds, and prenol lipids metabolites. The metabolites appeared in all varieties, including phenethyl rutinoside in glycosyl compounds and hovenidulcioside A1 in terpene glycosides. Metabolite–metabolite correlations in varieties revealed more complex patterns in relation to bud and enabled the recognition of key metabolites (e.g., Glutamate, (±)Catechin, GA52, ABA, and cs-Zeatin) affecting grafting and growth ability. Each variety has a unique metabolite type and correlation network relationship. Differentiated metabolites showed different growth trends for development after grafting. Many metabolites regulate the growth of scions in buds before grafting, which plays a crucial role in the growth of seedlings after grafting. It not only regulates the growth of roots but also affects the development of this stem. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites could be potentially used as indicators for the genetic background, indicating that metabolites could potentially be used as indicators for seedling growth characteristics. Together, this study will enrich the theoretical basis of seedling growth and lay a foundation for further research on the molecular regulation mechanism interaction between rootstock and scion, rootstock growth, and the development of grafted seedlings after grafting.

It is of great significance to study the nutritional characteristics of plants. Further understanding of plant mineral nutrient dynamics can provide theoretical basis for scientific fertilization to improve fruit quality and yield. In this study, eight mineral elements (N, P, K, Ca, Mg, Mn, Zn, B) were measured at regular intervals in leaves and kernels of the pecan “Mahan” planted in southern China. The study discussed the characteristics of mineral nutrient dynamics of pecan through the indicators of concentration, accumulation and cumulative relative rate, a new first proposed indicator, and focused on critical time, intensity, amount of mineral nutrients required in pecan during the fruit developing period, as well as the transfer information of the elements in leaves and kernels. The results show that the mineral nutrient requirements of the leaves and kernels are not identical, with an upward trend in nutrient accumulation within the kernel. The most abundant mineral nutrients in the leaves and kernels were N, K and Ca with Ca being greater than N in leaves. In particular, the concentration of Mn in pecan ‘Mahan’ is higher than that of other plants, and its Mg content is also higher than that of P in kernels. The dynamic changes of mineral nutrients in walnut showed obvious stages, with a trend of “slow (before mid-July) - fast (mid-July to late August) - slow (late August to late September) - fast (late September to harvest)”. The “critical period” of kernels was before mid-July, during which the cumulative relative rates increased rapidly, indicating that the kernels had a great potential to absorb mineral nutrients. Significant accumulation of mineral nutrients occurred from mid-July to late August and late September to the end.

Camellia oleifera (C. oleifera), one of the world’s four major edible woody oil crops, has been widely planted in southern China’s subtropical region for the extremely high nutritional and health benefits of its seed oil. Timing and synchronization of fruit dehiscence are critical factors influencing the oil output and quality, as well as the efficiency and cost of harvesting C. oleifera, yet they extremely lack attention. To gain an understanding of the molecular basis underlying the dehiscence of C. oleifera fruit, we sampled pericarp–replum tissues containing dehiscence zones from fruits at different developmental stages and performed time-series transcriptomic sequencing and analysis for the first time. Statistical and GO enrichment analysis of differentially expressed genes revealed that drastic transcriptional changes occurred over the last short sampling interval (4 days, 18th–22nd October), which directed functional classifications link to cell wall and cell wall macromolecule activity. WGCNA further showed that factors controlling cell wall modification, including endo-1,3;1,4-beta-D-glucanase, WAT1-like protein 37, LRR receptor-like serine/threonine-protein kinase, and cellulose synthase A catalytic subunit, were identified as core members of the co-expression network of the last stage highly related modules. Furthermore, in these modules, we also noted genes that were annotated as coding for polygalacturonase and pectinesterase, two pectinases that were expected to be major players in cell separation during dehiscence. qRT-PCR further confirmed the expression profiles of these cell wall modification relating factors, which possessed a special high transcriptional abundance at the final stage. These results suggested the cell wall associated cell separation, one of the essential processes downstream of fruit dehiscence, happened in dehiscing fruit of C. oleifera during ripening. Hydrolases acting on cell wall components are good candidates for signal mediating dehiscence of C. oleifera fruit. In conclusion, our analysis provided insights into the cell wall macromolecule-mediated fruit dehiscence during ripening in C. oleifera.

Flavonoids influence the flavor and nutritional value of pecan nuts. However, limited information is available regarding the molecular mechanisms underlying pecan flavonoid biosynthesis. Here, we used a high (“YLC28”) and a low (“Oconee”) flavonoid content cultivar as the research objects. The changes in flavonoid content and the gene transcription patterns during kernel development were identified. Different accumulation patterns of total flavonoids (TF) and condensed tannins (CT) were observed between the two cultivars. The contents of TF and CT in “YLC28” were 1.76- and 2.67-fold higher levels than that of “Oconee” on 150 days after full bloom of female flowers, respectively. In total, 30 RNA-Seq libraries were constructed and sequenced. The upregulated genes in “YLC28” were highly enriched in flavonoid-related pathways. Thirty-three structural genes were identified, and the expression of two phenylalanine ammonia lyases, one chalcone synthase, one flavonoid 3’,5’-hydroxylase, and one flavonol synthase exhibited high correlation (r ≥ 0.7, p < 0.01) with the condensed tannin content in “YLC28.” A putative MYB transcription factor, CIL1093S0100, might act as a flavonoid biosynthesis repressor during kernel development. Altogether, these results will be useful for uncovering the molecular mechanisms of flavonoid biosynthesis and subsequently accelerating quality pecan breeding.

Camellia is the largest genus in the family Theaceae. Due to phenotypic diversity, frequent hybridization, and polyploidization, an understanding of the phylogenetic relationships between Camellia species remains challenging. Comparative chloroplast (cp) genomics provides an informative resource for phylogenetic analyses of Camellia. In this study, 12 chloroplast genome sequences from nine Camellia species were determined using Illumina sequencing technology via de novo assembly. The cp genome sizes ranged from 156,545 to 157,021 bp and were organized into quadripartite regions with the typical angiosperm cp genomes. Each genome harbored 87 protein-coding, 37 transfer RNA, and 8 ribosomal RNA genes in the same order and orientation. Differences in long and short sequence repeats, SNPs, and InDels were detected across the 12 cp genomes. Combining with the complete cp sequences of seven other species in the genus Camellia, a total of nine intergenic sequence divergent hotspots and 14 protein-coding genes with high sequence polymorphism were identified. These hotspots, especially the InDel (~400 bp) located in atpH-atpI region, had sufficient potential to be used as barcode markers for further phylogenetic analysis and species identification. Principal component and phylogenetic analysis suggested that regional constraints, rather than functional constraints, strongly affected the sequence evolution of the cp genomes in this study. These cp genomes could facilitate the development of new molecular markers, accurate species identification, and investigations of the phylogenomic relationships of the genus Camellia.

Deep brain stimulation (DBS) is an effective treatment for dyskinesia in patients with Parkinson’s disease (PD), among which the therapeutic targets commonly used include the subthalamic nucleus (STN) and the globus pallidus internus (GPi). Levodopa-induced dyskinesia (LID) is one of the common motor complications arising in PD patients on chronic treatment with levodopa. In this article, we retrospectively evaluated the outcomes of LID with the Unified Dyskinesia Rating Scale (UDysRS) in patients who underwent DBS in multiple centers with a GPi or an STN target. Meanwhile, the Med off MDS-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-Ⅲ) and the levodopa equivalent daily dose (LEDD) were also observed as secondary indicators. PD patients with a GPi target showed a more significant improvement in the UDysRS compared with an STN target (92.9 ± 16.7% vs. 66.0 ± 33.6%, p < 0.0001). Both the GPi and the STN showed similar improvement in Med off UPDRS-III scores (49.8 ± 22.6% vs. 52.3 ± 29.5%, p = 0.5458). However, the LEDD was obviously reduced with the STN target compared with the GPi target (44.6 ± 28.1% vs. 12.2 ± 45.8%, p = 0.006).

Patients with advanced Alzheimer's disease (AD) experience cognitive impairment and physical disabilities in daily life. Currently, there are no treatments available to slow down the course of the disease, and limited treatments exist only to treat symptoms. However, deep brain stimulation of the nucleus basalis of Meynert (NBM-DBS) has been reported to improve cognitive function in individuals with AD. Here, we report the effects of NBM-DBS on cognitive function in a subject with severe AD. An 80-year-old male with severe AD (Clinical Dementia Rating scale: 3.0 points) underwent surgery for bilateral NBM-DBS electrode placement. After 10 weeks of stimulation, Mini-Mental State Examination (MMSE) assessment improved from a score of 5 to 9 points, and assessment using the Alzheimer's Disease Assessment Scale–Cognitive Subscale (ADAS-cog) showed a marked reduction in total score from 43 to 33 points, suggesting cognitive benefits from NBM-DBS. The patient's postoperative course was complicated by a subdural effusion that occurred several days after surgery, with complete recovery. Interestingly, the subject also displayed abnormal thermoregulation with stimulation initiation and stimulation parameter modifications. NBM-DBS may serve as a potential therapy for severe AD patients.Clinical Trial Registration: ChiCTR1900022324.

AbstractPecan is rich in bioactive components such as fatty acids (FAs) and flavonoids and is an important nut type worldwide. Therefore, the molecular mechanisms of phytochemical biosynthesis in pecan are a focus of research. Recently, a draft genome and several transcriptomes have been published. However, the full-length mRNA transcripts remain unclear, and the regulatory mechanisms behind the quality components biosynthesis and accumulation have not been fully investigated. In this study, single-molecule long-read sequencing technology was used to obtain full-length transcripts of pecan kernels. In total, 37,504 isoforms of 16,702 genes were mapped to the reference genome. The numbers of known isoforms, new isoforms, and novel isoforms were 9013 (24.03%), 26,080 (69.54%), and 2411 (6.51%), respectively. Over 80% of the transcripts (30,751, 81.99%) had functional annotations. A total of 15,465 alternative splicing (AS) events and 65,761 alternative polyadenylation events were detected; wherein, the retained intron was the predominant type (5652, 36.55%) of AS. Furthermore, 1894 long noncoding RNAs and 1643 transcription factors were predicted using bioinformatics methods. Finally, the structural genes associated with FA and flavonoid biosynthesis were characterized. A high frequency of AS accuracy (70.31%) was observed in FA synthesis-associated genes. This study provides a full-length transcriptome data set of pecan kernels, which will significantly enhance the understanding of the regulatory basis of phytochemical biosynthesis during pecan kernel maturation.

As woody oil crop, pecan [Carya illinoinensis (Wangenh.) K. Koch] may be a solution to the shortage of edible oil in the future. In this study, fruit traits, kernel nutrition and fatty acid composition of 10 pecan varieties were determined to assess the potential of pecans for exploitation as edible oil, as well as to further screen varieties that could be used as edible oil resources and to understand their development prospects for cultivation in mountainous hills. The study showed that all the fruit trait indicators measured, including green-fruit weight (mean 28.47 g), nut weight (10.33 g), kernel weight (5.25 g), nut percentage (36.83%) and kernel percentage (50.50%), showed highly significant differences among the 10 varieties. Among the main nutritional indicators of the kernels, the crude fat content was stable (mean 70.01%) with non-significant differences, while protein (67.50 mg·g−1), soluble sugar (10.7 mg·g−1) and tannin (6.07 mg·g−1) showed highly significant differences between varieties. The oil percentage of nuts (kernel percentage * crude fat) averaged 35.36%, with highly significant differences between varieties. The fatty acid composition was dominated by unsaturated fatty acids (mean 91.82%), with unsaturated fatty acids being 11.24 times more abundant than saturated fatty acids. Among the monounsaturated fatty acids, oleic acid was the highest (mean 70.02%), with highly significant differences between varieties, followed by cis-11-eicosanoic acid (0.25%), with non-significant differences between varieties; among the polyunsaturated fatty acids, linoleic acid was the highest (19.58%), followed by linolenic acid (0.97%), both of which showed highly significant differences between varieties; monounsaturated fatty acids were 2.42 times more abundant than polyunsaturated fatty acids. Compared to other oilseed crops, pecan has the potential to produce “nutritious, healthy and stable” edible oil, while its wide habitat and good productivity benefits offer broad prospects for development in the hills and mountains of subtropical China.

A practical method for the determination of cyanide in bamboo shoots has been developed using microdiffusion preparation integrated with ion chromatography–pulsed amperometric detection (IC-PAD). Cyanide was released from bamboo shoots after Conway cell microdiffusion, and then analysed by IC-PAD. In comparison with the previously reported methods, derivatization and ion-pairing agent addition were not required in this proposed microdiffusion combined with IC-PAD method. The microdiffusion parameters were optimized including hydrolysis systems, temperature, time, and so on. Under the optimum conditions, the linear range of the calibration curve for cyanide was 0.2–200.0 µg kg−1 with satisfactory correlation coefficients of 0.9996 and the limit of detection was 0.2 µg kg−1 (S/N = 3). The spiked recovery range was from 92.8 to 98.6%. The intra-day and inter-day relative standard deviations of cyanide were 2.7–14.9% and 3.0–18.3%, respectively. This method was proved to be convenient in operation with high sensitivity, precision and accuracy, and was successfully applied in the determination of cyanide in bamboo shoot samples.

Phenolics are a group of important plant secondary metabolites that have been proven to possess remarkable antioxidant activity and to be beneficial for human health. Pecan nuts are an excellent source of dietary phenolics. In recent years, many studies have focused on the separation and biochemical analysis of pecan phenolics, but the molecular mechanisms of phenolic metabolism in pecans have not been fully elucidated, which significantly hinders quality breeding research for this plant. Chalcone synthase (CHS) plays crucial roles in phenolic biosynthesis. In this study, three Carya illinoinensis CHSs (CiCHS1, CiCHS2, and CiCHS3), were isolated and analyzed. CiCHS2 and CiCHS3 present high expression levels in different tissues, and they are also highly expressed at the initial developmental stages of kernels in three pecan genotypes. A correlation analysis was performed between the phenolic content and CHSs expression values during kernel development. The results indicated that the expression variations of CiCHS2 and CiCHS3 are significantly related to changes in total phenolic content. Therefore, CiCHSs play crucial roles in phenolic components synthesis in pecan. We believe that the isolation of CiCHSs is helpful for understanding phenolic metabolism in C. illinoinensis, which will improve quality breeding and resistance breeding studies in this plant.

Introduction: 18F-FDG-PET is widely used to help localize the hypometabolic epileptogenic focus for presurgical evaluation of drug-refractory epilepsy patients. Two voxel-based brain mapping methods to interpret 18F-FDG-PET, statistical parametric mapping (SPM), and three-dimensional stereotactic surface projection (3D-SSP), improve the detection rate of seizure foci. This study aimed to compare the consistency of epileptic focus detection between SPM and 3D-SSP for 18F-FDG-PET brain mapping analysis. Methods: We retrospectively reviewed the clinical, electroecephalographic, and brain imaging results of 35 patients with refractory epilepsy. 18F-FDG-PET studies were revaluated by SPM, 3D-SSP, and visual assessment, and the results were compared to the MRI lesion location and to the presumed epileptogenic zone (PEZ) defined by video-EEG and other clinical data. A second consistency study compared PET analyses to histopathology and surgical outcomes in the 19 patients who underwent lesion resection surgery. Results: Of the 35 patients, consistency with the PEZ was 29/35 for SPM, 25/35 for 3D-SSP, 14/35 for visual assessment, and 10/35 for MRI. Concordance rates with the PEZ were significantly higher for SPM and 3D-SSP than for MRI (P0.05). A favorable Engel outcome (class I/II) was found in 16 of 19 cases (84%), and failure of seizure control was found in 3 of 19 patients (class III/IV). Conclusion: Voxel-based 18F-FDG-PET brain mapping analysis using SPM or 3D-SSP can improve the detection rate of the epileptic focus compared to visual assessment and MRI. Consistency with PEZ was similar between SPM and 3D-SSP; According to their own characteristics, 3D-SSP is recommended for primary evaluation due to greater efficiency and operability of the software, while SPM is recommended for high-accuracy localization of complex lesions. Therefore, joint application of both software packages may be the best solution for FDG-PET analysis of epileptic focus localization. Keywords: Epilepsy; Statistical Parametric Mapping; 18F-FDG-PET; 3D-SSP; Epileptic focus

A series of trans-3-aryl acrylic acids 1-27 and their derivatives 28-34 were prepared and evaluated for their antiviral activity against tobacco mosaic virus (TMV) for the first time. The bioassay results showed that most of these compounds exhibited good antiviral activity against TMV, of which compounds 1, 5, 6, 20, 27 and 34 exhibited significantly higher activity against TMV than commercial Ribavirin both in vitro and in vivo. Furthermore, these compounds have more simple structure than commercial Ribavirin, and can be synthesized more efficiently. These new findings demonstrate that trans-3-aryl acrylic acids and their derivatives represent a new template for antiviral studies and could be considered for novel therapy against plant virus infection.

Drug-drug interaction (DDI) extraction in biomedical literature is a particular entity relation classification task, which is significant for biopharmaceutical research. Current researchers mainly concentrated on fine-tuning the Pre-trained Language Model (PLM) on medical datasets to forecast the interactions between target drugs. Despite the above approaches having shown positive results, it is still confronted with some serious limitations. First of all, ordinary fine-tuning makes it difficult to take the best advantage of prior knowledge embedded in the PLM, due to the wide gap between objective forms of pre-training and downstream tasks. Secondly, the issue of limited training data or category imbalance also poses a great challenge for real-world DDI extraction tasks. In this work, we propose a novel model using Prompt Tuning and Data Augmentation (PTDA) to extract the DDI. This method can augment training data and alleviate the adverse effects of category imbalance by properly utilizing contextual word embedding substitution to generate examples for specific relation types. Furthermore, we have tried to introduce prompt tuning into the DDI extraction process, aiming to narrow the gap between pre-training and downstream tasks to leverage the prior knowledge in the PLM fully. We conduct a series of experiments on diverse biomedical datasets to verify the performance of our model. The results show that PTDA hugely outperforms existing DDI extraction methods, achieving F1-micro of 84.9%, 79.8%, and 73.1% on benchmark datasets, DDI 2013, ChemProt, and DTIs, respectively. Therefore, we believe that the PTDA model holds considerable potential for future practical applications. [ABSTRACT FROM AUTHOR]

Relation classification is an important task in information extraction that involves identifying potential semantic connections between two entities in a sentence. Most relation extraction models either use semantic or structure information as the relation representation for classification. Although some researchers have tried to fuse both types of information, they simply combine different information as relation representation, which ignores semantic and structure information contribute unequally to the relation representation at the instance level, leading to degradation of performance and generalization capability. To address this issue, we propose a fusing multi-information model with a self-attentive strategy (Att-FMI) for relation classification. Our approach utilizes the pre-trained BERT model and dependency syntactic parser to obtain semantic and structure representations from the sequence, respectively and efficiently combines the two with support the selfattention mechanism. Experimental results on four commonly used datasets, including TACRED, TACREV, KBP-37 and SemEval-2010 Task8, demonstrate that our approach yields significant improvements over baseline methods. Additionally, we observe that the Att-FMI model exhibits greater robustness against information interference in the extraction of entity relations from longer sentences than previous methods. [ABSTRACT FROM AUTHOR]