SAFE-GC-O-MS and descriptive sensory analysis were used to reveal the chemical sensory characteristics of sesame paste (tahini) at different storage stages.

Understanding the evolution of aroma profiles in stored sesame paste (SP) is essential for maintaining its quality. This study investigated the storage quality of SP and potential aroma markers indicative of sensory degradation. The descriptive sensory analysis demonstrated changes in aroma attributes during storage, transitioning from roasted sesame and nutty aromas to fermented and green aromas. Physicochemical analysis showed deepening color, intensified lipid oxidation, decreased levels of bioactive components, increased particle aggregation, and deteriorated flowability over 63 days at 40 °C. Gas chromatography-olfactometry-mass spectrometry identified 37 aroma-active compounds, with pyrazines, aldehydes, and phenols identified as the major constituents. Partial least squares regression analysis revealed 2-ethyl-3-methyl-pyrazine, 2-methoxy-4-vinylphenol, and benzaldehyde as key aroma-active compounds contributing significantly to the distinctive aromas "roasted nut and roasted sesame" found in SP. Conversely, hexanal and dimethyl disulfide emerged as potential markers of undesirable aromas in SP, including "rancid, green, and fermented". These findings provide insights into SP changes during storage, which is vital for preservation and quality enhancement strategies.

An Evaluation of the Physicochemical Properties of Sesame Paste Produced by Ball Milling Compared against Conventional Colloid Milling.

The physicochemical characteristics and general food quality were greatly impacted by milling. In order to investigate the effect of milling technique for physicochemical properties of sesame paste of sesame paste, samples were prepared using ball mill and colloid mill by varying grinding times. The samples prepared by ball milling had the higher moisture contents (0.07% - 0.14%) than colloid milling (p < 0.05), except for colloid milling for one cycle (0.11%). The particle size curves showed the multimodal distributions. Compared to colloid milled samples, ball milled samples have smaller particle sizes and more uniform particle distribution. The L* values of samples prepared by ball milling were higher than colloid milling. The ball mill produced sesame paste with a wider range of hardness and silkier texture, and the samples made by ball milling for 30 min had the highest hardness. And the hardness of both CMS and BMS showed a decreasing trend with increasing grinding time. During ball milling, high-speed cutting and collision caused breakage of disulfide bonds, and the sesame proteins were decomposed to their subunits. In conclusions, ball milling may be an alternative and promising process for the preparation of sesame paste.

Effect of Dehulling Pretreatment on the Flavor of Sesame Paste.

Gas chromatography-olfactory-mass spectrometry (GC-O-MS) combined with Aroma Extract Dilution Analysis (AEDA) were employed to characterize the key odor-active compounds in sesame paste (SP) and dehulled sesame paste (DSP). The AEDA results revealed the presence of 32 and 22 odor-active compounds in SP and DSP, respectively. Furthermore, 13 aroma compounds with FD ≥ 2, OAV ≥ 1, and VIP ≥ 1 were identified as key differential aroma compounds between SP and DSP. Specifically, compounds such as 3-methylbutyraldehyde (OAV = 100.70-442.57; fruity), 2-methylbutyraldehyde (OAV = 106.89-170.31; almond), m-xylene (FD = 16; salty pastry), and 2,5-dimethylpyrazine (FD = 8-16; roasted, salty pastry) played an important role in this differentiation. Additionally, the dehulling process led to increased fermented, sweet, green, and nutty aroma notes in DSP compared to the more pronounced burnt and roasted sesame aroma notes in SP. Our findings offer a theoretical foundation for the regulation of sesame paste aroma profiles.

Moisture content in dehulled sesame seeds: A key factor affecting the aroma and safety quality of sesame paste (tahini).

This study aimed to investigate the influence of the moisture content of dehulled sesame seeds on the aroma formation and harmful substances in sesame paste (SP). The SP samples were made of dehulled sesame seeds with moisture contents of 5%, 10%, 15%, 20%, and 25% and denoted as T5, T10, T15, T20, and T25, respectively. The results revealed that adjusting the moisture content had a significant impact on aroma compounds, color intensity, and sensory properties. SP pre-adjusted to a moisture content of 10% exhibited the smallest L* value and the highest browning strength. Using gas chromatography-olfactometry-mass spectrometry analysis, the researchers identified 38 aroma-active compounds in the SP, with pyrazines being the most abundant, contributing to roasted sesame and nutty aromas. Additionally, the presence of pyrrole and furan derivatives led to enhanced caramel and almond aromas, positively influencing the overall sensory properties. T10 demonstrated the highest levels of roasted sesame and nutty odors. Furthermore, the regulation of moisture content also affected the formation of harmful compounds, such as heterocyclic amines and polycyclic aromatic hydrocarbons (PAHs). Notably, the sample made of the sesame seeds with 10% and 15% moisture content exhibited the lowest total PAHs content (18.21-28.91 ng/g) and PAH4 content (non-detectable-0.15 ng/g). The carcinogen benzo[a]pyrene was not detected in any of the samples, ensuring a safer product. The pre-adjustment of moisture content in SP appears to be a promising approach to improve both its flavor and safety qualities.

Pre-regulation of the water content impacts on the flavor and harmful substances of sesame paste.

In this study, the influence of pre-regulation of the water content (5-25 %) on the harmful substances and aroma compounds of sesame paste (SP) was investigated. The results indicated that pre-regulation of the water content reduced the generation of harmful substances in SP. Notably, the total heterocyclic amine content in SP-15 was significantly lower than in other samples. SP-10 had the lowest total polycyclic aromatic hydrocarbon content, while SP-5 exhibited the lowest PAH4 content. Using solvent-assisted aroma evaporation and GC-O-MS, 50 aroma compounds were identified in SP. Pre-regulation of water content in SP led to an elevated concentration of heterocyclic compounds thereby imparting a diverse aromatic profile. It enhanced the perceived intensity of roasted sesame and salty pastry aromas while reducing the perceived intensity of fermentation and burnt aromas. The findings suggested the pre-regulation of the water content played a crucial role in aroma modulation and harmful substances control in SP.

Intervention of Tanshinone IIA on the PGK1-PDHK1 Pathway to Reprogram Macrophage Phenotype After Myocardial Infarction.

BACKGROUND: Myocardial infarction remains a disease with high morbidity and death rate among cardiovascular diseases. Macrophages are abundant immune cells in the heart. Under different stimulatory factors, macrophages can differentiate into different phenotypes and play a dual pro-inflammatory and anti-inflammatory role. Therefore, a potential strategy for the treatment of myocardial infarction is to regulate the energy metabolism of macrophages and thereby regulate the polarization of macrophages. Tan IIA is an effective liposolubility component extracted from the root of Salvia miltiorrhiza and plays an important role in the treatment of cardiovascular diseases. On this basis, this study proposed whether Tan IIA could affect phenotype changes by regulating energy metabolism of macrophages, and thus exert its potential in the treatment of MI. METHODS: Establishing a myocardial infarction model, Tan IIA was given for 3 days and 7 days for intervention. Cardiac function was detected by echocardiography, and cardiac pathological sections of each group were stained with HE and Masson to observe the inflammatory cell infiltration and fibrosis area after administration. The expression and secretion of inflammatory factors in heart tissue and serum of each group, as well as the proportion of macrophages at the myocardial infarction site, were detected using RT-PCR, ELISA, and immunofluorescence. The mitochondrial function of macrophages was evaluated using JC-1, calcium ion concentration detection, reactive oxygen species detection, and mitochondrial electron microscopic analysis. Mechanically, single-cell transcriptome data mining, cell transcriptome sequencing, and molecular docking technology were used to anchor the target of Tan IIA and enrich the pathways to explore the mechanism of Tan IIA regulating macrophage energy metabolism and phenotype. The target of Tan IIA was further determined by gene knockdown and overexpression assay. RESULTS: The intervention of Tan IIA can improve the cardiac function, inflammatory cell infiltration and fibrosis after MI, reduce the expression of inflammatory factors in the heart, enhance the secretion of anti-inflammatory factors, increase the proportion of M2-type macrophages, reduce the proportion of M1-type macrophages, and promote tissue repair, suggesting that Tan IIA has pharmacological effects in the treatment of MI. In terms of mechanism, RNA-seq results suggest that the phenotype of macrophages is strongly correlated with energy metabolism, and Tan IIA can regulate the PGK1-PDHK1 signaling pathway, change the energy metabolism mode of macrophages, and then affect its phenotype. CONCLUSION: Tan IIA regulates the energy metabolism of macrophages and changes its phenotype through the PGK1-PDHK1 signaling pathway, thus playing a role in improving MI.

Improving the mixed model for repeated measures to robustly increase precision in randomized trials.

In randomized trials, repeated measures of the outcome are routinely collected. The mixed model for repeated measures (MMRM) leverages the information from these repeated outcome measures, and is often used for the primary analysis to estimate the average treatment effect at the primary endpoint. MMRM, however, can suffer from bias and precision loss when it models intermediate outcomes incorrectly, and hence fails to use the post-randomization information harmlessly. This paper proposes an extension of the commonly used MMRM, called IMMRM, that improves the robustness and optimizes the precision gain from covariate adjustment, stratified randomization, and adjustment for intermediate outcome measures. Under regularity conditions and missing completely at random, we prove that the IMMRM estimator for the average treatment effect is robust to arbitrary model misspecification and is asymptotically equal or more precise than the analysis of covariance (ANCOVA) estimator and the MMRM estimator. Under missing at random, IMMRM is less likely to be misspecified than MMRM, and we demonstrate via simulation studies that IMMRM continues to have less bias and smaller variance. Our results are further supported by a re-analysis of a randomized trial for the treatment of diabetes.

Multi-omics approach for identification of molecular alterations of QiShenYiQi dripping pills in heart failure with preserved ejection fraction.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine theory believes that qi deficiency and blood stasis are the key pathogenesis of heart failure with preserved ejection fraction (HFpEF). As a representative prescription for replenishing qi and activating blood, QiShenYiQi dripping pills (QSYQ) has been used for treating heart diseases. However, the pharmacological mechanism of QSYQ in improving HFpEF is not well understood. AIM OF THE STUDY: The objective of the study is to investigate the cardioprotective effect and mechanism of QSYQ in HFpEF using the phenotypic dataset of HFpEF. MATERIALS AND METHODS: HFpEF mouse models established by feeding mice combined high-fat diet and Nω-nitro-L-arginine methyl ester drinking water were treated with QSYQ. To reveal causal genes, we performed a multi-omics study, including integrative analysis of transcriptomics, proteomics, and metabolomics data. Moreover, adeno-associated virus (AAV)-based PKG inhibition confirmed that QSYQ mediated myocardial remodeling through PKG. RESULTS: Computational systems pharmacological analysis based on human transcriptome data for HFpEF showed that QSYQ could potentially treat HFpEF through multiple signaling pathways. Subsequently, integrative analysis of transcriptome and proteome showed alterations in gene expression in HFpEF. QSYQ regulated genes involved in inflammation, energy metabolism, myocardial hypertrophy, myocardial fibrosis, and cGMP-PKG signaling pathway, confirming its function in the pathogenesis of HFpEF. Metabolomics analysis revealed fatty acid metabolism as the main mechanism by which QSYQ regulates HFpEF myocardial energy metabolism. Importantly, we found that the myocardial protective effect of QSYQ on HFpEF mice was attenuated after RNA interference-mediated knock-down of myocardial PKG. CONCLUSION: This study provides mechanistic insights into the pathogenesis of HFpEF and molecular mechanisms of QSYQ in HFpEF. We also identified the regulatory role of PKG in myocardial stiffness, making it an ideal therapeutic target for myocardial remodeling.

Effect of Flaxseed Addition on the Quality and Storage Stability of Sesame Paste.

The flaxseed-sesame paste (FSP) was prepared by mixing the heat-treated flaxseed and sesame seeds in different proportions and grinding them in a colloid mill to obtain a FSP. In this study, flaxseed was added to sesame paste (SP) at different addition to assess its effect on the rheological properties, textural properties, and particle size. The effect of flaxseed addition on lipid oxidation and volatile aldehydes and ketones during storage of SP was investigated by accelerated oxidation experiments (63°C, 60 days). Notably, the addition of all different additions of flaxseed increased the linolenic acid content, and also enhanced the hardness, cohesiveness, and viscosity of SP. However, it increased the rate of lipid oxidation in SP during storage, mainly in the form of higher acid value (AV) and malondialdehyde (MDA) content. The content of volatile aldehydes and ketones from lipid oxidation increased significantly with storage time. It was found by using cluster analysis that mixing flaxseed with SP at a ratio of 20 g/100 g had little effect on its storage stability, the sample had a higher overall quality than the addition of 40 g/100 g flaxseed, and its linolenic acid content was 18.7 times higher than that of the SP. Collectively, the results indicated that the addition of flaxseed at an appropriate proportion might be a feasible way to prepare the functional formulated SP.

Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors.

Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheimer's disease outcomes. In this study, we propose an ℓ1 -type regularization for predictors that follow a hierarchical tree structure. Considering a tree as a directed acyclic graph, we interpret the model parameters from a path analysis perspective. Under this concept, the proposed penalty regulates the total effect of each predictor on the outcome. With regularity conditions, it is shown that under the proposed regularization, the estimator of the model coefficient is consistent in ℓ2 -norm and the model selection is also consistent. When applied to a brain sMRI dataset acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the proposed approach identifies brain regions where atrophy in these regions demonstrates the declination in memory. With regularization on the total effects, the findings suggest that the impact of atrophy on memory deficits is localized from small brain regions, but at various levels of brain segmentation. Data used in preparation of this paper were obtained from the ADNI database.

Regularized regression on compositional trees with application to MRI analysis.

A compositional tree refers to a tree structure on a set of random variables where each random variable is a node and composition occurs at each non-leaf node of the tree. As a generalization of compositional data, compositional trees handle more complex relationships among random variables and appear in many disciplines, such as brain imaging, genomics and finance. We consider the problem of sparse regression on data that are associated with a compositional tree and propose a transformation-free tree-based regularized regression method for component selection. The regularization penalty is designed based on the tree structure and encourages a sparse tree representation. We prove that our proposed estimator for regression coefficients is both consistent and model selection consistent. In the simulation study, our method shows higher accuracy than competing methods under different scenarios. By analyzing a brain imaging data set from studies of Alzheimer's disease, our method identifies meaningful associations between memory decline and volume of brain regions that are consistent with current understanding.

Microneedle-based two-step transdermal delivery of Langerhans cell-targeting immunoliposomes induces a Th1-biased immune response.

Novel Coronavirus is affecting human's life globally and vaccines are one of the most effective ways to combat the epidemic. Transcutaneous immunization based on microneedle (MN) has attracted much attention because of its painlessness, rapidity, high efficiency and good compliance. In this study, CD11c monoclonal antibody-immunoliposomes (OVA@CD11c-ILP) actively targeting to Langerhans cells (LCs) were successfully prepared and were delivered by the microchannels of skin produced by MN to induce an immune response in vivo. OVA@CD11c-ILP could be targeted to LCs by conjugating CD11c monoclonal antibody to the surface of the ILP. OVA@CD11c-ILP promoted the maturation of dendritic cells (DCs) and the uptake and endocytosis of antigen by LCs. Moreover, OVA@CD11c-ILP immunization can significantly inhibit tumor growth and prolong overall survival. Furthermore, a higher antibody's titer ratio of IgG1/IgG2a indicated that the immune response stimulated by this immunization method was Th1-biased and the liposomes showed Th1-type adjuvant effect. In conclusion, the combination delivery system of immunoliposomes and microneedle can significantly improve the efficiency of antigen presentation and effectively activate cellular immune responses in the body, which is expected to be a promising transdermal immune strategy.

Lysosomal activable Vorinostat carrier-prodrug self-assembling with BPQDs enables photothermal oncotherapy to reverse tumor thermotolerance and metastasis.

Photothermal therapy (PTT) is becoming increasing prevalent in clinic for eradicating the primary tumor and improving cancer patients' compliance. However, photothermal resistance and distal metastasis still haunt the tumor treatment with PTT. Herein, on the basis that histone deacetylase acetylase inhibitor (HDACis) could activate the expression of anti-tumor gene and accelerate the differentiation and apoptosis of tumor cells, we propose that HDACis supplementing PTT could overcome those obstacles with appropriate drug-controlled release strategy. Thus, we fabricated a nano-complex of lysosomal activable vorinostat (SAHA) carrier-prodrug encapsulating black phosphorus quantum dots (BPQDs@PPS) to counter those challenges in PTT. With spherical morphology and favorable bio-safety, BPQDs@PPS could release BPQDs and Vorinostat spontaneously in lysosome, not only effectively inhibiting tumor growth, but also reversing tumor thermotolerance and metastasis within a PTT procedure. Especially, both western blot and immunofluorescence analysis validate that Vorinostat enables PTT to reverse tumor thermotolerance and distal metastasis by down-regulation of HSP70 and up-regulation of H3. Therefore, this research not only reveals the mechanism how HDACis supplement PTT in reversing tumor thermotolerance and metastasis, but also provides a promising prospect to upgrade clinical photothermal therapy.

Location Determination of Impact on the Wind Turbine Blade Surface Based on the FBG and the Time Difference.

This paper proposes an approach to the determination of the precise location of an impact on the surface of a wind turbine blade (WTB) based on a fiber Bragg grating (FBG) and the time difference, and its effectiveness is verified by experiments. First, the strain on the WTB surface is detected with an FBG. Then, the signal is decomposed into a series of components via variational mode decomposition (VMD), and some signals with impact characteristics are chosen for reconstruction. The instant energy of the reconstructed signal is then amplified through the Teager energy operator (TEO) to identify the time difference between FBGs. Finally, the coordinate of the impact point is obtained by solving the hyperbolic mode with the time difference. The results of experiments demonstrate that the proposed approach exhibits good performance with high accuracy (97%) and low error (12.3 mm).

Covariate Assisted Principal regression for covariance matrix outcomes.

In this study, we consider the problem of regressing covariance matrices on associated covariates. Our goal is to use covariates to explain variation in covariance matrices across units. As such, we introduce Covariate Assisted Principal (CAP) regression, an optimization-based method for identifying components associated with the covariates using a generalized linear model approach. We develop computationally efficient algorithms to jointly search for common linear projections of the covariance matrices, as well as the regression coefficients. Under the assumption that all the covariance matrices share identical eigencomponents, we establish the asymptotic properties. In simulation studies, our CAP method shows higher accuracy and robustness in coefficient estimation over competing methods. In an example resting-state functional magnetic resonance imaging study of healthy adults, CAP identifies human brain network changes associated with subject demographics.

Semiparametric partial common principal component analysis for covariance matrices.

We consider the problem of jointly modeling multiple covariance matrices by partial common principal component analysis (PCPCA), which assumes a proportion of eigenvectors to be shared across covariance matrices and the rest to be individual-specific. This paper proposes consistent estimators of the shared eigenvectors in the PCPCA as the number of matrices or the number of samples to estimate each matrix goes to infinity. We prove such asymptotic results without making any assumptions on the ranks of eigenvalues that are associated with the shared eigenvectors. When the number of samples goes to infinity, our results do not require the data to be Gaussian distributed. Furthermore, this paper introduces a sequential testing procedure to identify the number of shared eigenvectors in the PCPCA. In simulation studies, our method shows higher accuracy in estimating the shared eigenvectors than competing methods. Applied to a motor-task functional magnetic resonance imaging data set, our estimator identifies meaningful brain networks that are consistent with current scientific understandings of motor networks during a motor paradigm.

A whole-brain modeling approach to identify individual and group variations in functional connectivity.

Resting-state functional connectivity is an important and widely used measure of individual and group differences. Yet, extant statistical methods are limited to linking covariates with variations in functional connectivity across subjects, especially at the voxel-wise level of the whole brain. This paper introduces a modeling approach that regresses whole-brain functional connectivity on covariates. Our approach is a mesoscale approach that enables identification of brain subnetworks. These subnetworks are composite of spatially independent components discovered by a dimension reduction approach (such as whole-brain group ICA) and covariate-related projections determined by the covariate-assisted principal regression, a recently introduced covariance matrix regression method. We demonstrate the efficacy of this approach using a resting-state fMRI dataset of a medium-sized cohort of subjects obtained from the Human Connectome Project. The results suggest that the approach may improve statistical power in detecting interaction effects of gender and alcohol on whole-brain functional connectivity, and in identifying the brain areas contributing significantly to the covariate-related differences in functional connectivity.

Multifocal Cryoballoon Ablation for Eradication of Barrett's Esophagus-Related Neoplasia: A Prospective Multicenter Clinical Trial.

INTRODUCTION: Ablation of Barrett's esophagus (BE) is the preferred approach for the treatment of neoplasia without visible lesions. Limited data on cryoballoon ablation (CBA) suggest its potential clinical utility. We evaluated the safety and efficacy of CBA in a multicenter study of patients with neoplastic BE. METHODS: In a prospective clinical trial, 11 academic and community centers recruited consecutive patients with BE of 1-6 cm length and low-grade dysplasia, high-grade dysplasia (HGD), or intramucosal adenocarcinoma (ImCA) confirmed by central pathology. Patients with symptomatic pre-existing strictures or visible BE lesions had dilation or endoscopic mucosal resection (EMR), respectively, before enrollment. A nitrous oxide cryoballoon focal ablation system was used to treat all visible columnar mucosa in up to 5 sessions. Study end points included complete eradication of all dysplasia (CE-D) and intestinal metaplasia (CE-IM) at 1 year. RESULTS: One hundred twenty patients with BE with ImCA (20%), HGD (56%), or low-grade dysplasia (23%) were enrolled. In the intention-to-treat analysis, the CE-D and CE-IM rates were 76% and 72%, respectively. In the per-protocol analysis (94 patients), the CE-D and CE-IM rates were 97% and 91%, respectively. Postablation pain was mild and short lived. Fifteen subjects (12.5%) developed strictures requiring dilation. One patient (0.8%) with HGD progressed to ImCA, which was successfully treated with EMR. Another patient (0.8%) developed gastrointestinal bleeding associated with clopidogrel use. One patient (0.8%) had buried BE with HGD in 1 biopsy, not confirmed by subsequent EMR. DISCUSSION: In patients with neoplastic BE, CBA was safe and effective. Head-to-head comparisons between CBA and other ablation modalities are warranted (clinicaltrials.gov registration NCT02514525).

Gelated Vorinostat with inner-lysosome triggered release for tumor-targeting chemotherapy.

Histonedeacetylase inhibitor (HDACi) has great potential in targeted antitumor therapy by inhibiting tumor migration, invasion, and metastasis. As one of the typical HDACis, vorinostat (Suberoylanilide Hydroxamic Acid, SAHA) was approved as a therapeutic agent for cancer therapy, however, challenges remain due to their poor solubility, short half-life and low efficiency in cellular penetration. Considering the disadvantages of usual drug carriers, folate and vorinostat bound BSA nanogel (FVBN)was fabricated to implement higher solubility, stability, cellular uptake, and lipase-responsive release. With good dispersion and stability, FVBN significantly increased the cellular uptake of vorinostat through folate-mediated endocytosis. FVBN exhibited comparable cytotoxicity with free SAHA, and the growth of tumor cells was blocked in G1/G0 phase just like SAHA performed in cell cycle arrest tests. Moreover, FVBN not only effectively inhibited the growth of melanoma but also observably prevented pulmonary metastasis of melanoma. In the experiment against nude mice bearing solid ovarian cancer, FVBN showed excellent antitumor effect without liver damage, demonstrating the superiority of gelated and inner-lysosome triggered release strategies to the free SAHA, and it is promising to expand the scope of application of HDACi in clinical cancer therapy.