Challenges in Reducing Bias Using Post-Processing Fairness for Breast Cancer Stage Classification with Deep Learning.

Breast cancer is the most common cancer affecting women globally. Despite the significant impact of deep learning models on breast cancer diagnosis and treatment, achieving fairness or equitable outcomes across diverse populations remains a challenge when some demographic groups are underrepresented in the training data. We quantified the bias of models trained to predict breast cancer stage from a dataset consisting of 1000 biopsies from 842 patients provided by AIM-Ahead (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity). Notably, the majority of data (over 70%) were from White patients. We found that prior to post-processing adjustments, all deep learning models we trained consistently performed better for White patients than for non-White patients. After model calibration, we observed mixed results, with only some models demonstrating improved performance. This work provides a case study of bias in breast cancer medical imaging models and highlights the challenges in using post-processing to attempt to achieve fairness.

Effects of different post-harvest processing methods on changes in the active ingredients of licorice based on LC-MS and plant metabolomics.

INTRODUCTION: Licorice, the dried roots and rhizomes of the Glycyrrhiza uralensis Fisch., holds a prominent status in various formulations within the realm of Chinese medicinal practices. The traditional processing methods of licorice hinder quality assurance, thus prompting Chinese medicine researchers to focus on the fresh processing methods to enhancing processing efficiency and quality. OBJECTIVE: This study aimed to identify the differential compounds of licorice between traditional and fresh processing methods and provide a scientific basis for the fresh processing of licorice and for further research on the processing mechanism. METHODOLOGY: A methodology integrating ultra-performance liquid chromatography with quadrupole-time-of-flight tandem mass spectrometry combined with multivariate statistical analysis was employed to characterize the differential compounds present in licorice between traditional processing and fresh processing. RESULTS: The results derived from principal component analysis and heat map analyses underscored significant differences in the content of bioactive compounds between the two processing methods. By applying conditions of VIP > 1.5 and p < 0.05, a total of 38 differential compounds were identified through t tests, and the transformation mechanisms of select compounds were illustrated. CONCLUSION: The adoption of fresh processing techniques not only improved processing efficiency but also significantly enhanced the preservation of bioactive compounds within licorice. This research has established a rapid and efficient analytical method for the identification of differential compounds present in differently processed licorice products.

Improving physicochemical and nutritional attributes of rice starch through green modification techniques.

Rice, has long been an inseparable part of the human diet all over the world. As one of the most rapidly growing crops, rice has played a key role in securing the food chain of low-income food-deficit countries. Starch is the main component in rice granules which other than its nutritional essence, plays a key role in defining the physicochemical attributes of rice-based products. However, rice starch suffers from weak techno-functional characteristics (e.g., retrogradability of pastes, opacity of gels, and low shear/temperature resistibility. Green modification techniques (i.e. Non-thermal methods, Novel thermal (e.g., microwave, and ohmic heating) and enzymatic approaches) were shown to be potent tools in modifying rice starch characteristics without the exertion of unfavorable chemical reagents. This study corroborated the potential of green techniques for rice starch modification and provided deep insight for their further application instead of unsafe chemical methods.

Changes in chemical components and hepatoprotective effect of red Panax notoginseng processed by aspartic acid impregnation treatment.

BACKGROUND: Red Panax notoginseng (RPN) is one of the major processed products of P. notoginseng (PN), with more effective biological activities. However, the traditional processing method of RPN has some disadvantages, such as low conversion rate of ginsenosides and long processing time. RESULTS: In this work, we developed a green, safe, and efficient approach for RPN processing by aspartic acid impregnation pretreatment. Our results showed that the optimized temperature, steaming time, and concentration of aspartic acid were 120 °C, 1 h, and 3% respectively. The original ginsenosides in PN treated by aspartic acid (Asp-PN) were completely converted to rare saponins at 120 °C within just 1 h. The concentration of the rare ginsenosides in Asp-PN was two times higher than that in untreated RPN. In addition, we examined the protective effect of RPN and Asp-PN on acetaminophen-induced liver injury in a mouse model. The results showed that Asp-PN has significantly more potent hepatoprotective action than the RPN. The hepatoprotection of Asp-PN in acetaminophen-induced hepatotoxicity may be due to its anti-oxidative stress, anti-apoptotic, and anti-inflammatory activities. CONCLUSION: These results indicated that aspartic acid impregnation pretreatment may provide an effective method to shorten the steaming time, improve the conversion rate of ginsenosides, and enhance hepatoprotective activity of RPN. © 2024 Society of Chemical Industry.

Self-attention-based generative adversarial network optimized with color harmony algorithm for brain tumor classification.

This paper proposes a novel approach, BTC-SAGAN-CHA-MRI, for the classification of brain tumors using a SAGAN optimized with a Color Harmony Algorithm. Brain cancer, with its high fatality rate worldwide, especially in the case of brain tumors, necessitates more accurate and efficient classification methods. While existing deep learning approaches for brain tumor classification have been suggested, they often lack precision and require substantial computational time.The proposed method begins by gathering input brain MR images from the BRATS dataset, followed by a pre-processing step using a Mean Curvature Flow-based approach to eliminate noise. The pre-processed images then undergo the Improved Non-Sub sampled Shearlet Transform (INSST) for extracting radiomic features. These features are fed into the SAGAN, which is optimized with a Color Harmony Algorithm to categorize the brain images into different tumor types, including Gliomas, Meningioma, and Pituitary tumors. This innovative approach shows promise in enhancing the precision and efficiency of brain tumor classification, holding potential for improved diagnostic outcomes in the field of medical imaging. The accuracy acquired for the brain tumor identification from the proposed method is 99.29%. The proposed BTC-SAGAN-CHA-MRI technique achieves 18.29%, 14.09% and 7.34% higher accuracy and 67.92%,54.04%, and 59.08% less Computation Time when analyzed to the existing models, like Brain tumor diagnosis utilizing deep learning convolutional neural network with transfer learning approach (BTC-KNN-SVM-MRI); M3BTCNet: multi model brain tumor categorization under metaheuristic deep neural network features optimization (BTC-CNN-DEMFOA-MRI), and efficient method depending upon hierarchical deep learning neural network classifier for brain tumour categorization (BTC-Hie DNN-MRI) respectively.

This paper proposes a novel approach, BTC-SAGAN-CHA-MRI, for the classification of brain tumors using a Self-Attention based Generative Adversarial Network (SAGAN) optimized with a Color Harmony Algorithm. Brain cancer, with its high fatality rate worldwide, especially in the case of brain tumors, necessitates more accurate and efficient classification methods. While existing deep learning approaches for brain tumor classification have been suggested, they often lack precision and require substantial computational time. The proposed method begins by gathering input brain MR images from the BRATS dataset, followed by a pre-processing step using a Mean Curvature Flow-based approach to eliminate noise. The pre-processed images then undergo the Improved Non-Sub sampled Shearlet Transform (INSST) for extracting radiomic features. These features are fed into the SAGAN, which is optimized with a Color Harmony Algorithm to categorize the brain images into different tumor types, including Gliomas, Meningioma, and Pituitary tumors. This innovative approach shows promise in enhancing the precision and efficiency of brain tumor classification, holding potential for improved diagnostic outcomes in the field of medical imaging.

Comparative Metabolomics Study of Four Kinds of Xihu Longjing Tea Based on Machine Fixing and Manual Fixing Methods.

China Xihu Longjing tea is famous for its good flavor and quality. However, information on its related metabolites, except for flavonoids, is largely deficient. Different processing methods for China Xihu Longjing tea fixing-by machines at both the first and second step (A1), first step by machine and second step by hand (A2), first step by hand and second step by machine (A3), and by hand at both the first and second step (A4)-were compared using a UHPLC-QE-MS-based metabolomics approach. Liquid chromatography-mass spectrometry was used to analyze the metabolic profiles of the processed samples. A total of 490 metabolites (3 alkaloids, 3 anthracenes, 15 benzene and substituted derivatives, 2 benzopyrans, 13 coumarins and derivatives, 128 flavonoids, 4 furanoid lignans, 16 glycosides and derivatives, 5 indoles and derivatives, 18 isocoumarins and derivatives, 4 chalcones and dihydrochalcones, 4 naphthopyrans, 3 nucleosides, 78 organic acids and derivatives, 55 organooxygen compounds, 5 phenols, 109 prenol lipids, 3 saccharolipids, 3 steroids and steroid derivatives, and 17 tannins) were identified. The different metabolic profiles were distinguished using PCA and OPLS-DA. There were differences in the types and contents of the metabolites, especially flavonoids, furanoid lignans, glycosides and derivatives, organic acids and derivatives, and organooxygen compounds. There was a positive correlation between flavonoid metabolism and amino acid metabolism. However, there was a negative correlation between flavonoid metabolism and amino acid metabolism, which had the same trend as prenol lipid metabolism and tannins. This study provides new valuable information regarding differences in the metabolite profile of China Xihu Longjing tea processed based on machine fixing and on manual fixing methods.

[Comparison on anti-inflammatory activity of Gynostemma pentaphyllum processed with different methods].

The aim of this study is to investigate the effects of Gynostemma pentaphyllum dried with two different methods(air drying and heating) on inflammation in acute lung injury(ALI) mice in vivo and in vitro. Lipopolysaccharide(LPS) was sprayed into the airway of wild type C57BL/6J male mice to establish the model, and the drug was injected into the tail vein 24 h after modeling. Lung function, lung tissue wet/dry weight(W/D) ratio, the total protein concentration, interleukin 6(IL-6), IL-1ß, and tumor necrosis factor-α(TNF-α) in the bronchoalveolar lavage fluid(BALF), and pathological changes of the lung tissue were used to evaluate the effects of different gypenosides on ALI mice. The results showed that total gypenosides(YGGPs) and the gypenosides substituted with one or two glycosyl(GPs_(1-2)) in the air-dried sample improved the lung function, significantly lowered the levels of IL-1ß and TNF-α in BALF, and alleviated the lung inflammation of ALI mice. Moreover, GPs_(1-2) had a more significant effect on inhibiting NO release in RAW264.7 cells. This study showed that different drying methods affected the anti-inflammatory activity of G. pentaphyllum, and the rare saponins in the air-dried sample without heating had better anti-inflammatory activity.

[Research progress in pharmacological effects and chemical components of processed Angelicae Sinensis Radix products].

Angelicae Sinensis Radix is one of the main Chinese medicinal materials with both medicinal and edible values. It has the functions of tonifying and activating blood, regulating menstruation and relieving pain, and moistening intestines to relieve constipation. It is mainly produced in the southeastern Gansu province, and that produced in Minxian, Gansu is praised for the best quality. The chemical components of Angelicae Sinensis Radix mainly include volatile oils, organic acids, and polysaccharides, which have anti-inflammatory, pain-relieving, anti-tumor, anti-oxidation, immunomodulatory and other pharmacological effects. Therefore, this medicinal material is widely used in clinical practice. By reviewing the relevant literature, this study systematically introduced the research status about the chemical constituents and pharmacological effects of processed Angelicae Sinensis Radix products, aiming to provide a theoretical reference and support for the future research, development, and clinical application of related drugs.

High-oleic rapeseed oil quality indicators and endogenous antioxidant substances under different processing methods.

This study exposed high-oleic rapeseed oil (HORO) to different pretreatment (microwave or roasting) and processing methods to investigate (cold pressing, hexane extraction, subcritical butane extraction, and aqueous enzymatic extraction) the effects of processing technologies on HORO parameters associated with its physicochemical properties, endogenous antioxidant substances, and antioxidant capacity. The oil yield of various processing technologies was between 35.4% and 59.7%, and the fatty acid composition did not significantly differ. Hierarchical clustering and principal component analyses were used for evaluation. The results revealed that the microwave pretreatment-hexane extraction (M-HE) method resulted in significantly higher levels of tocopherols (688.4 mg/kg), polyphenols (1007.76 mg/kg), and phytosterols (1810.6 mg/kg) in HORO, implying strong free radical scavenging capacity (DPPH-oil: 79.63, DPPH-nonpolar: 71.42, DPPH-polar: 6.65, FRAP: 55.4, ABTS: 3043.7 µmol TE/kg). Hence, M-HE is a promising method for producing HORO with a higher stability and nutritional value.

DNA Metabarcoding Reveals the Fungal Community on the Surface of Lonicerae Japonicae Flos, an Edible and Medicinal Herb.

Lonicerae Japonicae Flos (LJF) has been globally applied as an herbal medicine and tea. A number of reports recently revealed fungal and mycotoxin contamination in medicinal herbs. It is essential to analyze the fungal community in LJF to provide an early warning for supervision. In this study, the fungal community in LJF samples was identified through DNA metabarcoding. A total of 18 LJF samples were collected and divided based on the collection areas and processing methods. The results indicated that Ascomycota was the dominant phylum. At the genus level, Rhizopus was the most abundant, followed by Erysiphe and Fusarium. Ten pathogenic fungi were detected among the 41 identified species. Moreover, Rhizopus, Fusarium, and Aspergillus had lower relative abundances in LJF samples under oven drying than under other processing methods. This work is expected to provide comprehensive knowledge of the fungal community in LJF and a theoretical reference for enhanced processing methods in practical manufacturing.

Interaction and Metabolic Function of Microbiota during the Washed Processing of Coffea arabica.

Coffee fermentation is crucial for flavor and aroma, as microorganisms degrade mucilage and produce metabolites. This study aimed to provide a basis for understanding the impact of microorganisms on Coffea arabica from Yunnan, China, during washed processing. The microbial community structure and differentially changed metabolites (DCMs) of C. arabica beans during washed processing were analyzed. The results indicated that the top five predominant microorganisms at the genera level were Achromobacter, Tatumella, Weissella, Streptococcus, and Trichocoleus for bacteria and Cystofilobasidium, Hanseniaspora, Lachancea, Wickerhamomyces, and Aspergillus for fungi. Meanwhile, the relative content of 115 DCMs in 36 h samples decreased significantly, compared to non-fermentation coffee samples (VIP > 1, p < 0.05, FC < 0.65), and the relative content of 28 DCMs increased significantly (VIP > 1, p < 0.05, FC > 1.5). Furthermore, 17 DCMs showed a strong positive correlation with microorganisms, and 5 DCMs had a strong negative correlation (p < 0.05, |r| > 0.6). Therefore, the interaction and metabolic function of microbiota play a key role in the formation of coffee flavor, and these results help in clarifying the fermentation mechanisms of C. arabica and in controlling and improving the quality of coffee flavor.

Rhizoma Atractylodis Macrocephalae-Assessing the influence of herbal processing methods and improved effects on functional dyspepsia.

Background: The unique pharmaceutical methods for the processing of botanical drugs according to the theory of traditional Chinese medicine (TCM) affect clinical syndrome differentiation and treatment. The objective of this study was to comprehensively elucidate the principles and mechanisms of an herbal processing method by investigating the alterations in the metabolites of Rhizoma Atractylodis Macrocephalae (AMR) processed by Aurantii Fructus Immaturus (AFI) decoction and to determine how these changes enhance the efficacy of aqueous extracts in treating functional dyspepsia (FD). Methods: A qualitative analysis of AMR before and after processing was conducted using UPLC-Q-TOF-MS/MS, and HPLC was employed for quantitative analysis. A predictive analysis was then conducted using a network analysis strategy to establish a botanical drug-metabolite-target-disease (BMTD) network and a protein-protein interaction (PPI) network, and the predictions were validated using an FD rat model. Results: A total of 127 metabolites were identified in the processed AMR (PAMR), and substantial changes were observed in 8 metabolites of PAMR after processing, as revealed by the quantitative analysis. The enhanced aqueous extracts of processed AMR (PAMR) demonstrate improved efficacy in treating FD, which indicates that this processing method enhances the anti-inflammatory properties and promotes gastric motility by modulating DRD2, SCF, and c-kit. However, this enhancement comes at the cost of attenuating the regulation of motilin (MTL), gastrin (GAS), acetylcholine (Ach), and acetylcholinesterase (AchE). Conclusion: Through this series of investigations, we aimed to unravel the factors influencing the efficacy of this herbal formulation in improving FD in clinical settings.

Dual-Color Lasers in Interlayer-Free Solution Processed Polymeric Bilayer Devices.

Multiwavelength organic lasers have attracted considerable interest in recent years due to the cost efficiency, wide luminescence coverage, and simple processability of organics. In this work, by simply spin coating immiscible polymeric gain media in sequence, dual-wavelength (blue-green or blue-red) amplified spontaneous emission (ASE) was achieved in bilayer devices. The blue emission, water/alcohol-soluble conjugated polyelectrolyte, poly[(9,9-bis(3'-((N,N-dimethyl)-N-ethylammonium)-propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene)]dibromide (PFN-Br), was used as the bottom layer. The commercially available nonpolar solvent soluble polymer poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) and its blend with poly(3-hexylthiophene) (P3HT) were used as the top active layers offering green and red emission, respectively. This novel compact configuration, without interlayers between the two active layers, offers potential for developing various applications. The carefully selected top and bottom layer polymers not only meet the conditions of immiscibility and different emission wavelength range but also have a common absorption band in UV, which allows simultaneous blue-green or blue-red dual-color ASE behaviors observed in the bilayer devices under the same 390 nm laser excitation. By introducing two-dimension (2D) square distributed feedback (DFB) gratings with different periods (300 nm for blue, 330 nm for green, and 390 nm for red) as cavities, single mode blue-green (Eth = 245 µJ cm-2) and blue-red (Eth = 189 µJ cm-2) lasers were achieved by focusing the excitation laser spot on different 2D DFB gratings area. Furthermore, we found it possible to gain sufficient light confinement for red emission along its diagonal direction (Λ âˆ¼424 nm), whereas the 2D DFB gratings offer feedback for blue emission from the 300 nm period along the rectangle direction. Therefore, both blue and red lasers were eventually achieved in the same PFN-Br/F8BT:P3HT bilayer device on the single 2D DFB gratings with a period of 300 nm in this work.

A New Inner Fabrication Method of Internal Cavity in Metal under Compound Acoustic Fields.

In order to realize direct manufacturing of cavity inside metal without assembly, this paper investigates the mechanism of cavity manufacturing inside metals under compound acoustic fields. First, a local acoustic cavitations model is established to study the single bubble generation at fixed point in Ga-In metal droplets, which has a low melting point. Second, cavitation-levitation acoustic composite fields are integrated with the experimental system for simulation and experimentation. Through COMSOL simulation and experimentation, this paper expounds the manufacturing mechanism of metal internal cavity under acoustic composite fields. The key problem is to control the duration of the cavitation bubble by controlling the driving acoustic pressure's frequency and the magnitude of ambient acoustic pressure. Under the condition of composite acoustic fields, this method realizes the direct fabrication of cavity inside Ga-In alloy for the first time.

Effects of processing methods on the aroma constituents of hihatsumodoki (Piper retrofractum Vahl).

Hihatsumodoki (Piper retrofractum Vahl) is a traditional spice from Okinawa (Japan) that can be processed in different ways to create the desired flavor. Herein, we examined the effects of processing (sun-drying, oven-drying, roasting, and steaming) on the volatile aroma constituents of hihatsumodoki fruits. Among the 106 chromatographic peaks observed in total, 58 were assigned to known aroma compounds. The relative contents of terpenes, for example, linalool, ß-caryophyllene, α-caryophyllene, and germacrene D, ranged from 57.6% to 88.1%. Sun-drying decreased the content of aldehydes such as hexanal and trans-2-hexenal but did not significantly affect the total content of aroma compounds. The amount of aroma compounds released during oven-drying and roasting increased with temperature up to a certain point (90°C) and decreased at an excessively high temperature of 180°C. High-temperature roasting generated Maillard reaction products such as furans and furanones, which could impart sweet caramel odors. Steamed fruits had the lowest content of aroma compounds, which was ascribed to the loss of these compounds to vapor. Meanwhile, drying steamed fruits resulted in an approximately 3.6-fold increase in their aroma compound content, and the content of sesquiterpenes in the steamed-dried fruits was similar to that in fruits exposed to high temperatures. The effects of processing on aroma quality were visualized using multivariate statistical analysis. The aroma characteristics of roasted (180°C), steamed, and steamed-dried fruits were different from those of the control. The combined findings provide useful information for the selection of processing methods to achieve the desired flavor of hihatsumodoki. Practical Application: This study reveals the effects of different processing methods on the aroma profile of hihatsumodoki (Piper retrofractum Vahl), a subtropical spice from Okinawa (Japan). The results facilitate the selection of preferred hihatsumodoki flavors for household and industrial applications in foods and beverages. In addition, they inspire research on the processing-induced flavor changes of other tropical or subtropical spices.

Polishing the bonding surface, before or after crystallization, does not alter the fatigue behavior of bonded CAD-CAM lithium disilicate.

The aim of this study was to assess if the finishing/polishing of the bonding surface of lithium disilicate ceramic, prior to or after crystallization, would affect the fatigue behavior of a bonded restorations. For this, lithium disilicate ceramic (IPS e.max CAD) discs (n = 15) were milled and randomly divided into 3 groups: CAD-CAM group which remained untouched; PRE group which received a finishing/polishing protocol (OptraFine system) prior to its crystallization; and POST group, which received the treatment after its crystallization. After surface treatments, ceramic and glass-fiber reinforced epoxy resin discs were paired and bonded using a resin cement (Multilink N). A cyclical fatigue test was conducted (frequency 20 Hz, initial load 200 N for 5000 cycles, step-size of 100 N for 10,000 cycles/step) until failure occurrence. Surface roughness and topography were analyzed. An initial descriptive analysis of surface roughness, FFL and CFF was performed to obtain the mean, standard deviation and confidence interval values (SPSS v. 21, SPSS Inc.) for statistical analysis. Roughness data was using one-way ANOVA with Tukey's post hoc test (α = 0.05), while the fatigue data was submitted to survival analysis with Kaplan-Meier test (α = 0.05) and Weibull modulus (Weibull++, Reliasoft). Neither the finishing/polishing procedure of the bonding surface, nor the moment (prior to or after crystallization), affected the fatigue behavior of bonded milled lithium disilicate. There were also no differences for mechanical reliability among conditions. Despite this, finishing/polishing reduced surface roughness and led to smoother topography. Finishing/polishing the bonding surface of milled lithium disilicate, before or after crystallization, does not alter the fatigue behavior of the bonded restorative set, although there is some influence on roughness and topography.

Recent Advances in Wayside Railway Wheel Flat Detection Techniques: A Review.

Wheel flats are amongst the most common local surface defect in railway wheels, which can result in repetitive high wheel-rail contact forces and thus lead to rapid deterioration and possible failure of wheels and rails if not detected at an early stage. The timely and accurate detection of wheel flats is of great significance to ensure the safety of train operation and reduce maintenance costs. In recent years, with the increase of train speed and load capacity, wheel flat detection is facing greater challenges. This paper focuses on the review of wheel flat detection techniques and flat signal processing methods based on wayside deployment in recent years. Commonly used wheel flat detection methods, including sound-based methods, image-based methods, and stress-based methods are introduced and summarized. The advantages and disadvantages of these methods are discussed and concluded. In addition, the flat signal processing methods corresponding to different wheel flat detection techniques are also summarized and discussed. According to the review, we believe that the development direction of the wheel flat detection system is gradually moving towards device simplification, multi-sensor fusion, high algorithm accuracy, and operational intelligence. With continuous development of machine learning algorithms and constant perfection of railway databases, wheel flat detection based on machine learning algorithms will be the development trend in the future.

Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms.

Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.

Ruminal responses, digestibility, and blood parameters of beef cattle fed diets without forage with different hybrids and processing of the corn.

The objective of this study was to evaluate the effects of corn hybrid and processing methods on intake and digestibility of nutrients, rumen fermentation and blood metabolites of steers fed no-forage finishing diets. Four ruminally fistulated Nellore castrated steers (502 ± 15 kg initial body weight) were distributed in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement consisting of two corn hybrids (semi-dent and flint) and two processing methods (dry milled and high moisture grain). Interactions of hybrid and processing methods were observed on intake of dry matter (DM), organic matter (OM) and crude protein (CP), as well as on digestibility of DM and CP, rumen pH and ammonia nitrogen (N-NH3 ). There was no interaction between hybrid and processing for the volatile fatty acids (VFA) total, acetate (C2), propionate (C3), isobutyric (iC4) and valeric (nC5) concentrations. VFA total concentration shown an average of 103.4 mmol/L. The C2 and C3 concentrations had no effect of the hybrid or processing with averages of 58.7 mmol/L for C2, and 31.3 mmol/l for C3. There was an effect of the processing method on starch consumption and fecal pH, the highest values were observed in grains with high moisture content. Starch digestibility was 0.89 g/g in dry milled and 0.96 g/g in high moisture corn. The greatest digestibility of starch in high moisture corn, irrespective of the corn hybrid, provided evidence of an increase in the energy supply, which may improve the feed efficiency and growth performance of cattle fed no-roughage finishing diets.

UPLC-Q-TOF-MS/MS analysis on the chemical composition of malts under different germination cycles and prepared with different processing methods.

OBJECTIVE: To investigate changes in the chemical composition of malts under different germination cycles and prepared with different processing methods, thus providing a reference for the clinical application of malt in disease treatment. METHODS: Nine malt samples were analyzed by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS), and the MS fragmentation pathway of 4 compounds (including hordenine, gramine, N-methyltyramine and catechin) were also analyzed. RESULTS: By database comparison and literature search, we detected 31 compounds in raw barley and 33 compounds in both raw malt and roasted malt. Nonetheless, the most of these 33 compounds were detected higher contents in raw malt than in roasted malt. Besides, we detected 15 compounds in brown malt. At Day1 of germination, 31 compounds were detected in malt, without two alkaloids (representative: hordenine). At Day2-5, 33 compounds were detected, with different contents as shown by the peak area comparison; hordenine had a gradually increasing abundance; and nearly one third of the chemical components in barley increased gradually, one third decreased gradually, and one third tended to be stable. CONCLUSION: Malts under different germination cycles and prepared with different processing methods have varying active ingredients, and especially brown malt exhibits a serious loss of compounds. The tight association between the chemical composition and clinical application of malt offers a basis to the clinically scientific and reasonable selection of Chinese medicinal materials for treatment purposes.