Air and argon cold plasma effects on lipolytic enzymes inactivation, physicochemical properties and volatile profiles of lightly-milled rice.

This study investigated the effectiveness of cold-plasma treatment using air and argon as input gas on deactivation of lipolytic enzymes in lightly-milled-rice (LMR). The results showed no significant inactivation in lipase and lipoxygenase using air-plasma. However, using argon as input gas, the residual activities of lipase and lipoxygenase were reduced to 64.51 % and 29.15 % of initial levels, respectively. Argon plasma treatment resulted in more substantial augmentation in peak and breakdown viscosities of LMR starch, suggesting an enhancement in palatability of cooked LMR with increased stickiness and decreased hardness. In contrast to the decrease in volatile compounds in LMR following argon plasma treatment, the concentrations of several prevalent aroma compounds, including 1-hexanol, 1-hexanal, and 2-pentylfuran, exhibited significant increments, reaching 1489.70 ng/g, 3312.10 ng/g, and 58.80 ng/g, respectively. These findings suggest the potential for enhancing various facets of the commercial qualities of LMR by utilizing different input gases during plasma treatment.

Multi-Wavelength Selective and Broadband Near-Infrared Plasmonic Switches in Anisotropic Plasmonic Metasurfaces.

Anisotropic plasmonic metasurfaces have attracted broad research interest since they possess novel optical properties superior to natural materials and their tremendous design flexibility. However, the realization of multi-wavelength selective plasmonic metasurfaces that have emerged as promising candidates to uncover multichannel optical devices remains a challenge associated with weak modulation depths and narrow operation bandwidth. Herein, we propose and numerically demonstrate near-infrared multi-wavelength selective passive plasmonic switching (PPS) that encompasses high ON/OFF ratios and strong modulation depths via multiple Fano resonances (FRs) in anisotropic plasmonic metasurfaces. Specifically, the double FRs can be fulfilled and dedicated to establishing tailorable near-infrared dual-wavelength PPS. The multiple FRs mediated by in-plane mirror asymmetries cause the emergence of triple-wavelength PPS, whereas the multiple FRs governed by in-plane rotational asymmetries avail the implementation of the quasi-bound states in the continuum-endowed multi-wavelength PPS with the ability to unfold a tunable broad bandwidth. In addition, the strong polarization effects with in-plane anisotropic properties further validate the existence of the polarization-resolved multi-wavelength PPS. Our results provide an alternative approach to foster the achievement of multifunctional meta-devices in optical communication and information processing.

Effects of Protein Components on the Chemical Composition and Sensory Properties of Millet Huangjiu (Chinese Millet Wine).

Millet Huangjiu is a national alcoholic beverage in China. The quality of Chinese millet Huangjiu is significantly influenced by the protein components in the raw materials of millet. Therefore, in this study, the impact of different protein components on the quality of millet Huangjiu was investigated by adding exogenous proteins glutelin and albumin either individually or in combination. The study commenced with the determination of the oenological parameters of different millet Huangjiu samples, followed by the assessment of free amino acids and organic acids. In addition, the volatile profiles of millet Huangjiu were characterized by employing HS-SPME-GC/MS. Finally, a sensory evaluation was conducted to evaluate the overall aroma profiles of millet Huangjiu. The results showed that adding glutelin significantly increased the contents of total soluble solids, amino acid nitrogen, and ethanol in millet Huangjiu by 32.2%, 41.5%, and 17.7%, respectively. Furthermore, the fortification of the fermentation substrate with glutelin protein was found to significantly enhance the umami (aspartic and glutamic acids) and sweet-tasting (alanine and proline) amino acids in the final product. Gas chromatography-quadrupole mass spectrometry coupled with multivariate statistical analysis revealed distinct impacts of protein composition on the volatile organic compound (VOC) profiles of millet Huangjiu. Excessive glutelin led to an over-accumulation of alcohol aroma, while the addition of albumin protein proved to be a viable approach for enhancing the ester and fruity fragrances. Sensory analysis suggested that the proper amount of protein fortification using a Glu + Alb combination could enhance the sensory attributes of millet Huangjiu while maintaining its unique flavor characteristics. These findings suggest that reasonable adjustment of the glutelin and albumin contents in millet could effectively regulate the chemical composition and improve the sensory quality of millet Huangjiu.

Semi-Supervised Deep Transfer Learning for Benign-Malignant Diagnosis of Pulmonary Nodules in Chest CT Images.

Lung cancer is the leading cause of cancer deaths worldwide. Accurately diagnosing the malignancy of suspected lung nodules is of paramount clinical importance. However, to date, the pathologically-proven lung nodule dataset is largely limited and is highly imbalanced in benign and malignant distributions. In this study, we proposed a Semi-supervised Deep Transfer Learning (SDTL) framework for benign-malignant pulmonary nodule diagnosis. First, we utilize a transfer learning strategy by adopting a pre-trained classification network that is used to differentiate pulmonary nodules from nodule-like tissues. Second, since the size of samples with pathological-proven is small, an iterated feature-matching-based semi-supervised method is proposed to take advantage of a large available dataset with no pathological results. Specifically, a similarity metric function is adopted in the network semantic representation space for gradually including a small subset of samples with no pathological results to iteratively optimize the classification network. In this study, a total of 3,038 pulmonary nodules (from 2,853 subjects) with pathologically-proven benign or malignant labels and 14,735 unlabeled nodules (from 4,391 subjects) were retrospectively collected. Experimental results demonstrate that our proposed SDTL framework achieves superior diagnosis performance, with accuracy = 88.3%, AUC = 91.0% in the main dataset, and accuracy = 74.5%, AUC = 79.5% in the independent testing dataset. Furthermore, ablation study shows that the use of transfer learning provides 2% accuracy improvement, and the use of semi-supervised learning further contributes 2.9% accuracy improvement. Results implicate that our proposed classification network could provide an effective diagnostic tool for suspected lung nodules, and might have a promising application in clinical practice.

Integrated Analysis of Metabolome and Volatile Profiles of Germinated Brown Rice from the Japonica and Indica Subspecies.

In the present study, germinated brown rice (GBR) from three Japonica and three Indica rice cultivars were subjected to metabolomics analysis and volatile profiling. The statistical assessment and pathway analysis of the metabolomics data demonstrated that in spite of significant metabolic changes in response to the germination treatment, the Japonica rice cultivars consistently expressed higher levels of several health-promoting compounds, such as essential amino acids and γ-aminobutyric acid (GABA), than the Indica cultivars. No clear discriminations of the volatile profiles were observed in light of the subspecies, and the concentrations of the volatile organic compounds (VOCs), including alkenes, aldehydes, furans, ketones, and alcohols, all exhibited significant reductions ranging from 26.8% to 64.1% after the germination. The results suggest that the Japonica cultivars might be desirable as the raw materials for generating and selecting GBR food products for health-conscious consumers.

Distinct clinicopathologic factors and prognosis based on the presence of ground-glass opacity components in patients with resected stage I non-small cell lung cancer.

BACKGROUND: This study was to investigate the prognostic value of ground-glass opacity(GGO) components and to evaluate distinct the clinicopathological variables of survival outcomes for the pure-GGO, part-solid and solid groups of patients with resected stage I non-small cell lung cancer (NSCLC). METHODS: We retrospectively reviewed the structured data for stage I NSCLC patients who had undergone the curative-intent surgical resection in the Lung Cancer Database of West China Hospital from 2009 to 2016. The eligible patients were divided into the pure-GGO, part-solid and solid groups according to the radiological manifestation. Univariate and multivariate Cox regression analyses were performed between the 3 groups. And we further evaluated the clinicopathological variables in each group separately. RESULTS: Among a total of 2,775 eligible patients enrolled into the cohort were 1,587 (57.19%) in the solid group, 508 (18.31%) in the part-solid group, and 680 (24.50%) in the pure-GGO group. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates were 98.8% and 98.0% in the pure-GGO group, 96.0% and 86.5% in the part-solid group, and 88.0% and 75.5% in the solid group, respectively (P<0.001). Presence of GGO components was a significantly favorable prognosticator (HR =0.415, 95% CI: 0.286-0.601). Different groups had distinct prognostic factors. LVI was the shared risk factor for groups with presence of GGO components in both part-solid and pure-GGO groups. Pathological stage (IA or IB) was influential exclusively for the pure-GGO group. In the solid group, females, younger patients, and patients without VPI had better survival. But such independent significance did not exist in the other two groups. CONCLUSIONS: GGO component was a strong prognosticator of better prognosis in resected patients with stage I NSCLC. Prognostic factors and survival outcomes were disparate among the pure-GGO, part-solid, and solid group. Our results support the proposal that the next edition tumor-node-metastasis (TNM) classification should consider the importance of GGO components as a new T descriptor.

Clinical and molecular characteristics associated with survival among cancer patients receiving first-line anti-PD-1/PD-L1-based therapies.

BACKGROUND: Anti-PD-1/PD-L1-based therapy has emerged recently, and we aimed to figure out the latent value of different clinical and molecular factors to predict the efficacy of immune checkpoint inhibitors (ICIs) therapy compared with non-immunotherapy in the first-line setting. METHODS: We assessed the clinical outcomes of 8711 patients in 13 trials receiving anti-PD-1/PD-L1-based therapy or non-immunotherapy as first-line treatment, and different predictors were investigated. RESULTS: Overall, compared with non-immunotherapy, anti-PD-1/PD-L1-based therapy reduced the risk of death by 31% (HR 0.69, 95%CI: 0.60-0.79) for all cancers. Stratified analysis showed that the progression-free survival (PFS) benefit from anti-PD-1/PD-L1-based therapy existed in all three PD-L1 status subgroups (tumour proportion score, TPS ≥50%: HR 0.54, 95%CI: 0.38-0.78; TPS 1-49%: HR 0.56, 95%CI: 0.46-0.68; TPS <1%: HR 0.82, 95%CI: 0.73-0.91; interaction, p < 0.01). ICI therapy also prolonged PFS in males (HR 0.64, 95%CI: 0.50-0.83) and younger patients (HR 0.70, 95%CI: 0.52-0.93), and they might prolong overall survival (OS) in patients without brain metastasis (HR 0.54, 95%CI: 0.41-0.71). CONCLUSION: PD-L1 expression level alone is imperfect to predict the efficacy of anti-PD-1/PD-L1-based therapies as first-line cancer treatment. Meanwhile, sex, age, and status of brain metastases might also be predictive parameters for the selection of cancer patients.

Prognostic value of pre-treatment red blood cell distribution width in lung cancer: a meta-analysis.

Objective: In recent years, increasing studies found that pre-treatment red blood cell distribution width (RDW) could predict clinical outcomes in various cancers. However, the prognostic value of pre-treatment RDW in lung cancer was inconsistent. Therefore, we performed a meta-analysis to determine prognostic value of pre-treatment RDW in lung cancer.Methods: We performed a search in PubMed, The Cochrane Library, EMBASE (via OVID), Web of Science, CNKI, Wanfang, VIP, SinoMed databases, then we identified all records up to February 15, 2019. Outcomes of interest were overall survival (OS) and disease-free survival (DFS). Hazard ratios (HRs) and corresponding 95% confidence intervals (95% CIs) were calculated to assess the relevance of pre-treatment RDW to OS in lung cancer.Results: We included ten articles in total. Pooled results revealed that elevated pre-treatment RDW was significantly associated with poor OS (HR = 1.55, 95% CI: 1.26-1.92, p < 0.001) and DFS (HR = 1.53, 95% Cl: 1.15-2.05; p = 0.004) in lung cancer. Further subgroup analysis manifested that lung cancer patients with elevated pre-treatment RDW had worse prognosis.Conclusions: A higher value of pre-treatment RDW indicated worse survival of patients with lung cancer. RDW may serve as a reliable and economical marker for prediction of lung cancer prognosis.

The application of artificial intelligence and radiomics in lung cancer.

Lung cancer is one of the most leading causes of death throughout the world, and there is an urgent requirement for the precision medical management of it. Artificial intelligence (AI) consisting of numerous advanced techniques has been widely applied in the field of medical care. Meanwhile, radiomics based on traditional machine learning also does a great job in mining information through medical images. With the integration of AI and radiomics, great progress has been made in the early diagnosis, specific characterization, and prognosis of lung cancer, which has aroused attention all over the world. In this study, we give a brief review of the current application of AI and radiomics for precision medical management in lung cancer.

Voltammetric, spectroscopic, and cellular characterization of redox functionality of eckol and phlorofucofuroeckol-A: A comparative study.

Interest in phlorotannins has increased in recent years largely due to antioxidant capacity, however, the redox mechanism of phlorotannins is still obscure. In the present study, the electrochemical oxidation mechanisms of eckol (EL) and phlorofucofuroeckol-A (PFF-A), two representative phlorotannin compounds, were comparatively analyzed in a wide pH range using cyclic and differential pulse voltammetry as well as spectroscopic assay. The voltammetric study revealed that EL and PFF-A were successively oxidized in three pH-dependent steps. Moreover, it was found that the PFF-A presented a stronger proton and electron transferring activity as compared to EL since PFF-A exhibited lower acid-base dissociation constant (pKa ) value and higher heterogeneous rate constant (kbh ) value in the first oxidation step. These property were further evidenced by comparison of direct antioxidant activity (i.e., superoxide anion and peroxide radicals) as well as indirect antioxidant activity (i.e., mRNA expression of two phase II enzymes) between EL and PFF-A. PRACTICAL APPLICATIONS: Phlorotannins from edible algae have been regarded as novel antioxidants those presented high application potential in food industry. Even though antioxidant activity of phlorotannin compounds have been widely investigated in both in vitro and in vivo studies, very few reports focused on electron transferring functionality which is chemical basis for antioxidant process. Herein, the oxidative mechanisms of two representative phlorotannins were comparatively analyzed using multiple electrochemical methods. This is hopefully to give information on the chemical meaning behind the antioxidant activity of dietary phlorotannins.

Gastrointestinal microbiome and breast cancer: correlations, mechanisms and potential clinical implications.

Gastrointestinal microbiome plays as a symbiont which provides protection effect against invading pathogens, aids in the immune system development, nutrient reclamation and absorption as well as molecule breakdown. And it may avert carcinogenesis through these biological activities. By now, studies have been carried out to elaborate the association between gastrointestinal microbiome and breast cancer. It has been implicated that breast cancer was substantially associated with estrogen-dependent and estrogen-independent functions of gastrointestinal microbiome. Evidence from animal experiments also confirmed mammary tumor-related changes in microbial community. The possible mechanisms involve estrogen metabolism, immune regulation, obese status and so forth. Based on the current evidence, cues on future management strategies of breast cancer such as antibiotics and dietary interventions are proposed. In conclusion, large-scale clinical studies and bench-based researches are needed to validate the associations and elaborate the mechanisms, so as to reduce the risk of breast cancer and improve the outcomes of those already diagnosed.