Approaching a Minimal Topological Electronic Structure in Antiferromagnetic Topological Insulator MnBi2Te4 via Surface Modification.

The topological electronic structure plays a central role in the nontrivial physical properties in topological quantum materials. A minimal, "hydrogen-atom-like" topological electronic structure is desired for research. In this work, we demonstrate an effort toward the realization of such a system in the intrinsic magnetic topological insulator MnBi2Te4, by manipulating the topological surface state (TSS) via surface modification. Using high resolution laser- and synchrotron-based angle-resolved photoemission spectroscopy (ARPES), we found the TSS in MnBi2Te4 is heavily hybridized with a trivial Rashba-type surface state (RSS), which could be efficiently removed by the in situ surface potassium (K) dosing. By employing multiple experimental methods to characterize K dosed surface, we attribute such a modification to the electrochemical reactions of K clusters on the surface. Our work not only gives a clear band assignment in MnBi2Te4 but also provides possible new routes in accentuating the topological behavior in the magnetic topological quantum materials.

Taurine Treatment Alleviates Intestinal Mucositis Induced by 5-Fluorouracil in Mice.

Taurine (Tau), a ß-amino acid, exists in red goji fruit (Lycium barbarum L.). It exerts many cellular physiological functions such as anti-inflammation and oxidation resistance. The chemotherapy drug 5-fluorouracil (5FU) can cause intestinal mucositis. However, current therapeutic approaches for mucositis have limited efficacy and are associated with various side effects. It is still unknown whether Tau can alleviate intestinal mucositis. This study aimed to investigate the protective effect of the Tau in a mucositis mouse model and elucidate the underlying molecular mechanisms. The intestinal mucositis symptoms were alleviated by the Tau administration as evidenced by decreased body weight loss, histopathological score, oxidative stress, and improved glutathione (GSH). The Tau supplementation strengthened intestinal epithelial tight junction and reduced serum lipopolysaccharide (LPS) levels in intestinal mucositis mice. Moreover, the 5FU-induced inflammatory responses were alleviated by Tau treatment via the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) and nuclear factor kappa-B/inducible nitric oxide synthase (NF-κB/iNOS) signaling pathway. Tau administration modulated short chain fatty acids (SCFAs) in the colon of mice. The results indicated that the Tau might be a new dietary strategy for intestinal mucositis caused by 5FU.

Diversity in storage age enables discrepancy in quality attributes and metabolic profile of Citrus grandis "Tomentosa" in China.

The folk proverb "the older, the better" is usually used to describe the quality of Citrus grandis "Tomentosa" (CGT) in China. In this study, CGT aged for 6-, 12-, 16-, and 19-years were collected for the investigation of infusion color, main bioactive components, antioxidant activity, metabolic composition, and pathway. The results found that infusion color, the total phenolic and flavonoid, and antioxidant activity of CGT were obviously changed by aging process. Through untargeted metabolomics, 55 critical metabolites were identified to in discrimination of CGT with different storage ages, mainly including phenylpropanoids, lipids, and organic oxygen compounds. Twenty compounds that showed good linear relationships with storage ages could be used for year prediction of CGT. Kyoto encyclopedia of genes and genomes enrichment pathway analysis uncovered important metabolic pathways related to the accumulation of naringin, kaempferol, and choline as well as the degradation of benzenoids, thus supporting that aged CGT might be more beneficial to health. Correlation analysis provided that some key metabolites with bitter taste and biological activity were involved in the darkening and reddening of CGT infusion during aging, and total phenolic and flavonoid were more strongly associated with the antioxidant activity of CGT. This study systematically revealed the quality changes and key metabolic pathways during CGT aging at first time. PRACTICAL APPLICATION: This study reveals the differences in quality attributes and metabolic profile between CGT with different storage ages, providing guidance for consumers' consumption, and also providing more scientific basis for the quality evaluation and improvement of CGT.

Revealing oxidative degradation of lipids and screening potential markers of four vegetable oils during thermal processing by pseudotargeted oxidative lipidomics.

The oxidative degradation of lipids in vegetable oils during thermal processing may present a risk to human health. However, not much is known about the evolution of lipids and their non-volatile derivatives in vegetable oils under different thermal processing conditions. In the present study, a pseudotargeted oxidative lipidomics approach was developed and the evolution of lipids and their non-volatile derivatives in palm oil, rapeseed oil, soybean oil, and flaxseed oil under different thermal processing conditions was investigated. The results showed that thermal processing resulted in the oxidative degradation of TGs in vegetable oils, which generated oxTGs, DGs, and FFAs, as well as TGs with smaller molecular weights. The lower the fatty acid saturation, the more severe the oxidative degradation of vegetable oils and thermal processing at high temperatures should be avoided if possible. From the accumulation of oxTGs concentrations, the hazards during thermal processing at high temperatures were, in descending order, soybean oil, rapeseed oil, flaxseed oil, and palm oil. The non-volatile potential markers were screened in palm oil, rapeseed oil, soybean oil, and flaxseed oil for 1, 7, 5, and 2 markers related to thermal processing time, respectively. The study provided suggestions for the consumption of vegetable oils from multiple perspectives and identified markers for monitored oxidative degradation of vegetable oils.

Oxidative lipidomics to elucidate the non-volatile derivatives of four typical triglycerides in vegetable oils under simulated frying conditions.

Vegetable oils with different saturations have varied composition of triglycerides (TGs) and produce different non-volatile derivatives during oxidation. Precise characterization of the non-volatile derivatives of TGs is essential for understanding the degradation of TGs and the production pattern of non-volatile derivatives. Oxidative lipidomics was combined with collision-induced dissociation and electron-activated dissociation to elucidate the precise structures of non-volatile derivatives produced under simulated frying conditions by 1,3-dipalmitoyl-2-oleoylglycerol (POP), triolein (OOO), trilinolein (LLL), and trilinolenin (LnLnLn). The results indicate that the unsaturated fatty acyl chains at the sn-2 position were more susceptible to oxidation compared with those at the sn-1/3 position. Species of non-volatile derivatives included epoxy-, hydroperoxy-, hydroxy-, and oxo-TGs, as well as degradation products. The potential reaction pathways of TGs and their non-volatile derivatives were also proposed. This study elucidated oxidative degradation mechanisms of the four typical TGs and provided a theoretical basis for changes of vegetable oils during frying.

Unravelling dynamic changes in non-volatile and volatile metabolites of pulses during soaking: An integrated metabolomics approach.

An integrated metabolomics approach based on UPLC-QTOF-MS and HS-SPME-GC-orbitrap-MS was performed to investigate the dynamic changes of metabolite profiling in chickpeas, red speckled kidney beans, and mung beans during soaking. There were 23, 23, 16 non-volatile metabolites, and 18, 21, 22 volatile metabolites were identified as differential metabolites in chickpeas, red speckled kidney beans, and mung beans during soaking, respectively. These metabolites mainly included flavonoids, lysophosphatidylcholines (LPCs), lysophosphatidylethanolamines (LPEs), fatty acids, alcohols, aldehydes, and esters. The key time points responsible for the significant changes in metabolites and quality of the three pulses were 4, 8, and 24 h of soaking. Results revealed that the variations of some metabolites could attribute to oxidation and hydrolysis reactions. These results contribute to a better understanding of how soaking affects pulses quality, and provide useful information for determining soaking time according to nutritional and sensory requirements of their final products or dishes.

The functional role of sulforaphane in intestinal inflammation: a review.

Intestinal inflammation represented by inflammatory bowel disease (IBD) has become a global epidemic disease and the number of patients with IBD continues to increase. This digestive tract disease not only affects the absorption of food components by destroying the intestinal epithelial structure, but also can induce diseases in remote organs via the gut-organ axis, seriously harming human health. Nowadays, increasing attention is being paid to the nutritional and medicinal value of food components with increasing awareness among the general public regarding health. As an important member of the isothiocyanates, sulforaphane (SFN) is abundant in cruciferous plants and is famous for its excellent anti-cancer effects. With the development of clinical research, more physiological activities of SFN, such as antidepressant, hypoglycemic and anti-inflammatory activities, have been discovered, supporting the fact that SFN and SFN-rich sources have great potential to be dietary supplements that are beneficial to health. This review summarizes the characteristics of intestinal inflammation, the anti-inflammatory mechanism of SFN and its various protective effects on intestinal inflammation, and the possible future applications of SFN for promoting intestinal health have also been discussed.

Effects of postharvest cysteine treatment on sensory quality and contents of bioactive compounds in goji fruit.

Effects of cysteine (Cys) treatments (0, 0.01%, 0.05% and 0.10%) on sensory quality and bioactive compounds in goji fruit stored at 4 °C and 90% RH for 10 d were investigated. Results indicated that 0.05% Cys treatment significantly reduced decay ratio and weight loss, and maintained total soluble solid content in goji fruit. Furthermore, 0.05% Cys treatment increased the contents of total phenolic, ascorbic acid and total glutathione, and the ratio of glutathione/oxidized glutathione, resulting in the higher antioxidant capacity. Determination of five free amino acids showed that 0.05% Cys treatment increased the Pro and Tau contents, while had no significant effect on the Cys, Glu and GABA contents. The increase in Tau content might be due to the up-regulation of two key genes involved in the Tau synthesis including CDO and CSAD. These findings suggested that Cys treatment could improve the storage quality in goji fruit.

Observation of Coexisting Dirac Bands and Moiré Flat Bands in Magic-Angle Twisted Trilayer Graphene.

Moiré superlattices that consist of two or more layers of 2D materials stacked together with a small twist angle have emerged as a tunable platform to realize various correlated and topological phases, such as Mott insulators, unconventional superconductivity, and quantum anomalous Hall effect. Recently, magic-angle twisted trilayer graphene (MATTG) has shown both robust superconductivity similar to magic-angle twisted bilayer graphene and other unique properties, including the Pauli-limit violating and re-entrant superconductivity. These rich properties are deeply rooted in its electronic structure under the influence of distinct moiré potential and mirror symmetry. Here, combining nanometer-scale spatially resolved angle-resolved photoemission spectroscopy and scanning tunneling microscopy/spectroscopy, the as-yet unexplored band structure of MATTG near charge neutrality is systematically measured. These measurements reveal the coexistence of the distinct dispersive Dirac band with the emergent moiré flat band, showing nice agreement with the theoretical calculations. These results serve as a stepstone for further understanding of the unconventional superconductivity in MATTG.

Melatonin treatment affects the glucoraphanin-sulforaphane system in postharvest fresh-cut broccoli (Brassica oleracea L.).

The effect of postharvest melatonin treatment on sulforaphane production of fresh-cut broccoli at 4℃ during storage was investigated in this study. Florets treated with 100 µM melatonin exhibited higher contents of total glucosinolates and sulforaphane. Glucoraphanin content was significantly increased after melatonin treatment, and which was explained by gene analysis. Expressions of glucoraphanin biosynthesis genes including Elong, CYP83A1, MYB28, UGT74B1 and FMOGS-OX1 were up-regulated while AOP2 was obviously decreased by melatonin treatment, leading to a higher glucoraphanin accumulation. In addition, application of melatonin enhanced the myrosinase activity and the expression level of MYO, benefiting the formation of sulforaphane. This study demonstrates that melatonin treatment positively affected the glucoraphanin-sulforaphane system in postharvest fresh-cut broccoli.

Two new species of a new genus, Pseudorogneda, of Polycystididae discovered in Southern China.

Two new species of the new genus Pseudorogneda of Polycystididae were discovered in a brackish environment from Southern China. Pseudorogneda sinensis n. gen. n. sp., is distinguished by a semicircular double-walled prostate stylet type II that tapers in diameter from proximal to distal with a proximal-to-distal fold, and an inner wall with a funnel-shaped base originating at the midpoint of the outer wall; its flattened tubular prostate stylet type IV exhibits a horn-like base and a proximal-to-distal folded structure on its wall. For Pseudorogneda shenda n. gen. n. sp., its crescent-shaped prostate stylet type II is double-walled and the inner wall has a funnel-shaped base that starts at the proximal 2/3 position of the outer stylet and is fused with the outer stylet to form a sharp distal end; its tubular and slightly-curved prostate stylet type IV exhibits a slit and a distal fold. Phylogenetic analysis of 18S rDNA and 28S rDNA sequences shows that the two novel species are clustered to form an independent clade from other genera, which is consistent with morphological comparison in the establishment of two new species in a new genus.

Multispectral imaging for predicting the water status in mushroom during hot-air dehydration.

In-depth understanding of the shifting of water status during dehydration is crucial for obtaining better quality of dried food. In this work, we report a nondestructive method to measure the water status in hot-air dried mushroom via multispectral imaging (MSI) technology combined with chemometric methods. The low-field nuclear magnetic resonance (LF-NMR) measurements were performed as reference. During drying process, the moisture content changed dramatically with notable migration and conversion of different water phases. Partial least squares (PLS), back propagation neural network (BPNN), and least squares-support vector machine (LS-SVM) models were applied to develop quantitative models. Among all, BPNN model showed considerably better performance of prediction with coefficient of determination R2 c = 0.9829, R2 p = 0.9639. The results demonstrated that MSI technology combined with chemometric methods is an impressive approach for determination of the water status in hot-air dried mushrooms, which would facilitate infield of food processing by providing applicable and appropriate platform. PRACTICAL APPLICATION: Experimental investigation of different water status during food processing. Assessment of the potential of multispectral imaging to predict water status. Usage of novel measurement method for food processors.

Microcalcification classification assisted by content-based image retrieval for breast cancer diagnosis.

In this paper we propose a microcalcification classification scheme, assisted by content-based mammogram retrieval, for breast cancer diagnosis. We recently developed a machine learning approach for mammogram retrieval where the similarity measure between two lesion mammograms was modeled after expert observers. In this work we investigate how to use retrieved similar cases as references to improve the performance of a numerical classifier. Our rationale is that by adaptively incorporating local proximity information into a classifier, it can help to improve its classification accuracy, thereby leading to an improved "second opinion" to radiologists. Our experimental results on a mammogram database demonstrate that the proposed retrieval-driven approach with an adaptive support vector machine (SVM) could improve the classification performance from 0.78 to 0.82 in terms of the area under the ROC curve.

A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications.

In this paper, we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs). The classifier is part of a computer-aided diagnosis (CADx) scheme that is aimed to assisting radiologists in making more accurate diagnoses of breast cancer on mammograms. The methods we considered were: support vector machine (SVM), kernel Fisher discriminant (KFD), relevance vector machine (RVM), and committee machines (ensemble averaging and AdaBoost), of which most have been developed recently in statistical learning theory. We formulated differentiation of malignant from benign MCs as a supervised learning problem, and applied these learning methods to develop the classification algorithm. As input, these methods used image features automatically extracted from clustered MCs. We tested these methods using a database of 697 clinical mammograms from 386 cases, which included a wide spectrum of difficult-to-classify cases. We analyzed the distribution of the cases in this database using the multidimensional scaling technique, which reveals that in the feature space the malignant cases are not trivially separable from the benign ones. We used receiver operating characteristic (ROC) analysis to evaluate and to compare classification performance by the different methods. In addition, we also investigated how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD, and RVM) yielded the best performance (Az = 0.85, SVM), significantly outperforming a well-established, clinically-proven CADx approach that is based on neural network (Az = 0.80).

Relevance vector machine for automatic detection of clustered microcalcifications.

Clustered microcalcifications (MC) in mammograms can be an important early sign of breast cancer in women. Their accurate detection is important in computer-aided detection (CADe). In this paper, we propose the use of a recently developed machine-learning technique--relevance vector machine (RVM)--for detection of MCs in digital mammograms. RVM is based on Bayesian estimation theory, of which a distinctive feature is that it can yield a sparse decision function that is defined by only a very small number of so-called relevance vectors. By exploiting this sparse property of the RVM, we develop computerized detection algorithms that are not only accurate but also computationally efficient for MC detection in mammograms. We formulate MC detection as a supervised-learning problem, and apply RVM as a classifier to determine at each location in the mammogram if an MC object is present or not. To increase the computation speed further, we develop a two-stage classification network, in which a computationally much simpler linear RVM classifier is applied first to quickly eliminate the overwhelming majority, non-MC pixels in a mammogram from any further consideration. The proposed method is evaluated using a database of 141 clinical mammograms (all containing MCs), and compared with a well-tested support vector machine (SVM) classifier. The detection performance is evaluated using free-response receiver operating characteristic (FROC) curves. It is demonstrated in our experiments that the RVM classifier could greatly reduce the computational complexity of the SVM while maintaining its best detection accuracy. In particular, the two-stage RVM approach could reduce the detection time from 250 s for SVM to 7.26 s for a mammogram (nearly 35-fold reduction). Thus, the proposed RVM classifier is more advantageous for real-time processing of MC clusters in mammograms.

Learning a channelized observer for image quality assessment.

It is now widely accepted that image quality should be evaluated using task-based criteria, such as human-observer performance in a lesion-detection task. The channelized Hotelling observer (CHO) has been widely used as a surrogate for human observers in evaluating lesion detectability. In this paper, we propose that the problem of developing a numerical observer can be viewed as a system-identification or supervised-learning problem, in which the goal is to identify the unknown system of the human observer. Following this approach, we explore the possibility of replacing the Hotelling detector within the CHO with an algorithm that learns the relationship between measured channel features and human observer scores. Specifically, we develop a channelized support vector machine (CSVM) which we compare to the CHO in terms of its ability to predict human-observer performance. In the examples studied, we find that the CSVM is better able to generalize to unseen images than the CHO, and therefore may represent a useful improvement on the CHO methodology, while retaining its essential features.

Three-dimensional sonography with needle tracking: role in diagnosis and treatment of prostate cancer.

OBJECTIVE: Image-guided prostate biopsy has become routine in medical diagnosis. Although it improves biopsy outcome, it mostly operates in 2 dimensions, therefore lacking presentation of information in the complete 3-dimensional (3D) space. Because prostatic carcinomas are nonuniformly distributed within the prostate gland, it is crucial to accurately guide the needles toward clinically important locations within the 3D volume for both diagnosis and treatment. METHODS: We reviewed the uses of 3D image-guided needle procedures in prostate cancer diagnosis and cancer therapy as well as their advantages, work flow, and future directions. RESULTS: Guided procedures for the prostate rely on accurate 3D target identification and needle navigation. This 3D approach has potential for better disease diagnosis and therapy. Additionally, when fusing together different imaging modalities and cancer probability maps obtained from a population of interest, physicians can potentially place biopsy needles and other interventional devices more accurately and efficiently by better targeting regions that are likely to host cancerous tissue. CONCLUSIONS: With the information from anatomic, metabolic, functional, biochemical, and biomechanical statuses of different regions of the entire gland, prostate cancers will be better diagnosed and treated with improved work flow.

Improvement in C-arm acquired DSA image quality via combined effect of inverse consistent motion correction and nonlinear normalization.

In this paper, we present a new two-step strategy to improve DSA image quality. First, an inverse consistent image registration algorithm is used to register the mask frame and the bolus frame before subtraction. This can effectively reduce the motion artifacts in DSA. Second, the resulted DSA image is further enhanced by background diffusion and nonlinear normalization for better visualization. The proposed method has been evaluated on a database of 73 subjects by quantitatively measuring signal-to-noise (SNR) ratio and Tenengrad measure. DSA embedded with proposed strategies demonstrates an improvement of 136.56% over conventional DSA in terms of SNR. Our system runs on Eigen's DSA workstation using C++ in Windows environment.