The suspension stability of nanoplastics in aquatic environments revealed using meta-analysis and machine learning.

Nanoplastics (NPs) aggregation determines their bioavailability and risks in natural aquatic environments, which is driven by multiple environmental and polymer factors. The back propagation artificial neural network (BP-ANN) model in machine learning (R2 = 0.814) can fit the complex NPs aggregation, and the feature importance was in the order of surface charge of NPs > dissolved organic matter (DOM) > functional group of NPs > ionic strength and pH > concentration of NPs. Meta-analysis results specified low surface charge (0 ≤ |ζ| < 10 mV) of NPs, low concentration (< 1 mg/L) and low molecular weight (< 10 kg/mol) of DOM, NPs with amino groups, high ionic strength (IS > 700 mM) and acidic solution, and high concentration (≥ 20 mg/L) of NPs with smaller size (< 100 nm) contribute to NPs aggregation, which is consistent with the prediction in machine learning. Feature interaction synergistically (e.g., DOM and pH) or antagonistically (e.g., DOM and cation potential) changed NPs aggregation. Therefore, NPs were predicted to aggregate in the dry period and estuary of Poyang Lake. Research on aggregation of NPs with different particle size,shapes, and functional groups, heteroaggregation of NPs with coexisting particles and aging effects should be strengthened in the future. This study supports better assessments of the NPs fate and risks in environments.

"Structure-function" analysis using starches isolated from Lycoris chinensis bulbs of different developmental stages.

In this study, Lycoris chinensis bulbs of four developmental stages were compared for starch characteristics. Based on correlation analysis and hierarchical cluster analysis, the relationships among 36 traits were discussed. Compared to commonly consumed starches, L. chinensis starch had higher amylose content (33.4-43.2 %) and weight-average molar mass (36410-82,781 kDa), lower gelatinization temperature (61.8-68.1 °C), gel hardness (19.0-39.5 g) and viscosities. Among developmental stages, starches varied significantly in characteristics. As compared to juvenile stage (S1), mature bulbs (S4) had higher amylose content, lower gelatinization temperature, weight-average molar mass and degree of polymorphism. Correlation analysis revealed that the molecular weight-related traits had significantly positive correlations to gelatinization temperature (Tp, p < 0.05), positive but weak correlations to traits of particle size distribution, significantly negative correlations to AAC and many parameters of viscosity properties (p < 0.05). Based on the results of correlation analysis and hierarchical cluster analysis, the 36 traits of starch characteristics were proposed to be divided into three groups: particle size-related traits, molecular weight-related traits and AAC-related traits. The information presented in the current study are useful for future studies on starches of Lycoris and other bulb species, and instructive for future studies in investigating the "Structure-Function" relationship in starch.

Structural and physicochemical properties of bracken fern (Pteridium aquilinum) starch.

Introduction: Bracken fern (Pteridium aquilinum) starch is a non-mainstream, litter-researched starch, thus the starch characteristics remain largely unknown. Methods: The structural and physicochemical properties of two bracken starches were systematically investigated, by use of various techniques that routinely applied in starch analysis. Results and Discussion: The starches had amylose contents of 22.6 and 24.7%, respectively. The starch granules possessed C-type polymorph with D (4,3) ranging from 18.6 to 24.5 µm. During gelatinization event, the bracken starches showed lower viscosity than typical for rice starch, and lower gelatinization temperature than typical for cereal starches. After gelatinization event, bracken starches formed much softer and sticky gel than rice and potato starch. The molecular weight and branching degree (indexed by Mw, Mn and Rz values) of bracken starches were much higher than starches of many other sources. The branch chain length distributions showed that the bracken starches were structurally similar to some rice varieties (e. g. BP033, Beihan 1#), as reflected by proportions of A, B1, B2, and B3 chains. Notable differences in some starch traits between the two bracken starches were recorded, e. g. amylose content, gel hardness, gelatinization temperature and traits of structural properties. This study provides useful information on the utilization of bracken starch in both food and non-food industries.

Characterization of starch extracted from seeds of Cycas revoluta.

Introduction: Starch is major component in the big seeds of Cycas revoluta, however the characteristics of Cycas revoluta remain unknown. Methods: In this study, the physicochemical and structural properties of two starch samples extracted from Cycad revoluta seeds were systematically investigated, using various techniques. Results: The amylose contents of the two samples were 34.3 % and 35.5%, respectively. The spherical-truncated shaped starch granules possessed A-type crystallinity, and had an average diameter less than 15 µm. Compared to most commonly consumed cereal and potato starch, Cycad revoluta starch showed distinctive characteristics. For physicochemical properties, in the process of gelatinization, the Cycad revoluta starch showed similar viscosity profile to starches of some potato varieties, but Cycad revoluta starch had higher gelatinization temperature. Upon cooling, Cycad revoluta starch formed harder gels than rice starch. For structure, the molecular weight (indexed by Mw, Mn and Rz values), branching degree and the branch chain length distribution were determined. Discussion: The results suggested that Cycad revoluta starch were different in structure from the main-stream starches. Notable differences in some starch traits between the two samples were recorded, which could be attributed to environmental factors. In general, this study provides useful information on the utilization of Cycad revoluta starch in both food and non-food industries.

Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study.

BACKGROUND: Digital just-in-time adaptive interventions can reduce binge-drinking events (BDEs; consuming ≥4 drinks for women and ≥5 drinks for men per occasion) in young adults but need to be optimized for timing and content. Delivering just-in-time support messages in the hours prior to BDEs could improve intervention impact. OBJECTIVE: We aimed to determine the feasibility of developing a machine learning (ML) model to accurately predict future, that is, same-day BDEs 1 to 6 hours prior BDEs, using smartphone sensor data and to identify the most informative phone sensor features associated with BDEs on weekends and weekdays to determine the key features that explain prediction model performance. METHODS: We collected phone sensor data from 75 young adults (aged 21 to 25 years; mean 22.4, SD 1.9 years) with risky drinking behavior who reported their drinking behavior over 14 weeks. The participants in this secondary analysis were enrolled in a clinical trial. We developed ML models testing different algorithms (eg, extreme gradient boosting [XGBoost] and decision tree) to predict same-day BDEs (vs low-risk drinking events and non-drinking periods) using smartphone sensor data (eg, accelerometer and GPS). We tested various "prediction distance" time windows (more proximal: 1 hour; distant: 6 hours) from drinking onset. We also tested various analysis time windows (ie, the amount of data to be analyzed), ranging from 1 to 12 hours prior to drinking onset, because this determines the amount of data that needs to be stored on the phone to compute the model. Explainable artificial intelligence was used to explore interactions among the most informative phone sensor features contributing to the prediction of BDEs. RESULTS: The XGBoost model performed the best in predicting imminent same-day BDEs, with 95% accuracy on weekends and 94.3% accuracy on weekdays (F1-score=0.95 and 0.94, respectively). This XGBoost model needed 12 and 9 hours of phone sensor data at 3- and 6-hour prediction distance from the onset of drinking on weekends and weekdays, respectively, prior to predicting same-day BDEs. The most informative phone sensor features for BDE prediction were time (eg, time of day) and GPS-derived features, such as the radius of gyration (an indicator of travel). Interactions among key features (eg, time of day and GPS-derived features) contributed to the prediction of same-day BDEs. CONCLUSIONS: We demonstrated the feasibility and potential use of smartphone sensor data and ML for accurately predicting imminent (same-day) BDEs in young adults. The prediction model provides "windows of opportunity," and with the adoption of explainable artificial intelligence, we identified "key contributing features" to trigger just-in-time adaptive intervention prior to the onset of BDEs, which has the potential to reduce the likelihood of BDEs in young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT02918565; https://clinicaltrials.gov/ct2/show/NCT02918565.

Preliminary Characterization of Phytochemicals and Polysaccharides in Diverse Coffee Cascara Samples: Identification, Quantification and Discovery of Novel Compounds.

Coffee cascara is the first and most significant by-product of the coffee processing industry, whose valorization has become an urgent priority to reduce harmful environmental impacts. This work aimed to provide an improved understanding of phytochemicals and polysaccharides in coffee cascara in order to offer information for the better evaluation of potential applications. Phytochemicals in 20 different coffee cascara samples were ultrasonically extracted and analyzed by HPLC-UV and HPLC-MS/MS. Four novel compounds were isolated for the first time from coffee cascara, including two still unknown tautomers (337 Da), and two dihydroflavonol glycosides (dihydromyricetin glycoside and dihydromyricetin rhamnosylglycoside). Their presence can contribute to the design of new value-added applications of coffee cascara. Chemical characterization of two polysaccharides from two of the coffee cascara pulp samples showed that they were mainly composed of homogalacturonan, with rhamnose and arabinose as minor neutral sugars. In addition, principal component analysis results indicated that coffee cultivar and/or country significantly impacted the phytochemical composition of coffee cascara, although differences may be reduced by the external environment and processing method. It is suggested that processing method should be carefully designed when generating coffee cascara from the same cultivar and country/farm.

Starch properties of high and low amylose proso millet (Panicum miliaceum L.) genotypes are differentially affected by varying salt and pH.

Variation in salt content and in pH are common in starch-based foods and can affect starch properties and final product texture. Fifteen accessions of proso millet starch with diverse amylose content were selected to investigate single factor and interaction effects of pH and NaCl on thermal, pasting, and textural properties. Pasting properties and gelatinization temperatures were markedly altered by salt addition. Changes in pH only had substantial effects on ΔH, but other properties were generally stable under different pH conditions. From two-way ANOVA, interactive effects of salt and pH were found to affect ΔH. The response of starch of different genotypes in terms of thermal and pasting properties differed under the same pH and salinity conditions. The reason is likely that ions in the starch-water system performed the roles of both reducing water activity and building of hydrogen bonds, which will have opposite effects on starch gelatinization.

Diversity analysis of starch physicochemical properties in 95 proso millet (Panicum miliaceum L.) accessions.

In this study, 95 accessions of proso millet (Panicum miliaceum L.) were characterized for starch physicochemical properties, including apparent amylose content (AAC), gel textural properties, Rapid Visco Analyzer (RVA) pasting viscosity properties, thermal and retrogradation properties. Based on genotypic data, the genetic diversity and inter-relationship of these starch traits were analyzed. Diverse starch quality was found, for example, AAC ranged from 0 to 32.3%, gelatinization temperature (GT) varied from 71.5 to 79.0 ℃, and RVA profile showed distinct patterns among proso millet of different AAC types. Interestingly, high AAC proso millet usually had GT lower than that of low AAC proso millet, which is different from the findings in rice starch. Many starch traits were significantly correlated and most of the 18 tested traits could be classified as either AAC-related traits or GT-related traits. In summary, the information presented here will be useful for further development of proso millet products.

Characterization of morphology and physicochemical properties of native starches isolated from 12 Lycoris species.

In this study, starch was isolated from 13 genotypes of 12 Lycoris species, and the morphology, granule size distribution and physicochemical properties, including apparent amylose content (AAC), Rapid Visco Analyzer (RVA) pasting properties, textural properties, thermal and retrogradation properties were characterized. The majority of starch granules of the 13 Lycoris genotypes were oval in shape, and granule size followed a normal distribution with a mean diameter of 20-30 µm. Contrary to previously published findings, the XRD results revealed that lycoris starches had either C-type or CA-type crystallinity. All lycoris starches showed high AAC varying from 25.6% to 32.7%, and low gelatinization temperature (GT) ranging from 58.8 to 69.7℃. Inter-relationships among 18 starch quality traits were analyzed based on correlation analysis. The present study provides information on lycoris starch characteristics which should serve as a useful guide for later studies on lycoris starch utilization in food and non-food industries.

The Black Truffle, Tuber melanosporum (Ascomycetes), Ameliorates Hyperglycemia and Regulates Insulin Signaling Pathway in STZ-Induced Diabetic Rats.

Black truffle mushroom, Tuber melanosporum, is effective in treating various symptoms associated with diabetes mellitus such as hyperglycemia, oxidative stress, and hyperlipidemia and is used as traditional medicine. The aim of our study is to elucidate the antidiabetic potential of T. melanosporum. Male albino Wistar rats were administered a single dose of STZ (40 mg/kg b.w.) to induce mild diabetes mellitus (DM). After the confirmation of hyperglycemia, rats were treated with three different doses of truffle extract (TE) (200, 400, and 600 mg/kg b.w.) for the duration of 45 days. The various tissues were collected at the end of the study. The levels of glucose, oral glucose tolerance test, insulin, hexokinase, glucose 6 phosphatase, and fructose-1,6-bisphosphatase, and regulation of insulin signaling genes were quantified. The results showed that STZ- induced rats have a higher blood glucose level and a lower insulin level compared with the control groups and TE treated groups. Results also reveal that STZ suppressed the expressions of insulin signaling genes in diabetic rats and TE treatment resulted in a positive regulation of the insulin signaling pathway. The results of TE are similar to the results attained in glibenclamide (GB) group rats. Overall, the study provides scientific evidence for the medicinal properties of black truffle; future clinical studies can warrant a potential antidiabetic drug in the form of diet.

Isoquercetin regulates SREBP-1C via AMPK pathway in skeletal muscle to exert antihyperlipidemic and anti-inflammatory effects in STZ induced diabetic rats.

Diabetes mellitus (DM) is a cluster of metabolic diseases that exhibits high blood glucose levels accompanied by hyperlipidemia and inflammation. DM is the primary risk factor contributes majorly to cardiovascular disease (CVD) mediated morbidity and mortality. The incidence of dyslipidemia seems to attribute considerably to the initiation of CVDs. The beneficial action of isoquercetin on hyperlipidemia and related signaling pathways are not documented yet, hence we decide to carry out this study. The experimental rats were divided into five groups: Group 1, control rats; group 2, isoquercetin control (40 mg/kg b.w); group 3, diabetic rats (STZ-40 mg/kg b.w); group 4, diabetic + isoquercetin (40 mg/kg b.w); and group 5, diabetic + glibenclamide (600 µg/kg b.w). The animals were sacrificed at the end of the experimental duration of 45 days. Results of our analysis reveal that isoquercetin have a major impact on the tissue lipid profile, isoquercetin strongly regulates the expression of various lipid-metabolizing enzymes, C-reactive protein, expression of various inflammatory genes, SREBP-1C genes and proteins and AMP-activated protein kinase-α (AMPK) signaling pathway genes and proteins. Results recommend that isoquercetin can be effective in mitigating the consequences of hyperlipidemia and DM.

Genetic variation in starch physicochemical properties of Chinese foxtail millet (Setaria italica Beauv.).

In this study, 34 Chinese foxtail millet germplasm accessions (cultivars and breeding lines) were characterized for starch physicochemical properties including apparent amylose content, and gel textural, RVA pasting, thermal and retrogradation properties. The relationships among 21 starch parameters were discussed based on correlation analysis and hierarchical cluster analysis. Generally, this set of germplasm presented a surprisingly low genetic diversity in starch properties. The apparent amylose content ranged from 18.3% to 25.3% with a CV value of 5.0%, and gelatinization temperature ranged from 72.1 to 73.8 °C with a CV value of 0.5%. AAC was negatively correlated only with ΔHg (p < 0.01) while GT only had a strong relationship with To and Tc of thermal properties (p < 0.001). The 21 measured starch parameters could be separated into three groups based on cluster analysis. This work should provide useful information for breeding improved quality foxtail millet.

Black Truffle Aqueous Extract Attenuates Oxidative Stress and Inflammation in STZ-Induced Hyperglycemic Rats via Nrf2 and NF-κB Pathways.

Background and Purpose: Tuber melanosporum (black truffle) has been considered as a medicinal mushroom for a long time. T. melanosporum has the ability to attenuate oxidative stress and in turn diabetes mellitus (DM). DM has become an awfully common chronic unwellness, threatening people's well-being. There are nearly 1 in 10 people in the world affected by diabetes. Oxidative stress plays a crucial role in vascular complications related to DM. Our study aimed to attain an effective treatment method to alleviate oxidative stress by scavenging free radicals and reducing inflammation, to display how truffle aqueous extract (TE) attenuates hyperglycemia. Methods: Streptozotocin (STZ)-induced hyperglycemic rat model was accustomed to check the hypoglycemic effect of black truffle by relating it with Nrf2 and NF-κB pathways. Varied biomarkers and inflammatory markers were analyzed. Results: Rats treated with TE showed reduced glucose levels, attenuated oxidative stress through regulation of SOD, CAT, VIT-E, and VIT-C. The gene expression of Nrf2 and NF-κB in rats treated with TE was increased to normal group level. The mRNA expression of inflammatory pathway genes and oxidative stress pathway genes in rats treated with TE was brought back normal. Similar results were achieved in the rats treated with standard drug, glibenclamide (GB). TE conjointly inhibits the state of inflammation within the tissues generally littered with the symptoms of hyperglycemia. Conclusion: The results of our study show the hypoglycemic impact of black truffle on STZ-induced hyperglycemia in rats via Nrf2 and NF-κB pathways, and both pathways have significant improvement that may support the hypoglycemic impact of truffle.

Isoquercetin ameliorates hyperglycemia and regulates key enzymes of glucose metabolism via insulin signaling pathway in streptozotocin-induced diabetic rats.

Among the foremost common flavonoids within the human diet, quercetin glycosides possess neuroprotective, cardioprotective, anti-oxidative, chemopreventive, and anti-allergic properties. Isoquercetin is one such promising candidate with anti-diabetic potential. However, complete studies of its molecular action on insulin signaling pathway and carbohydrate metabolizing enzymes remain unclear. Hence, we have designed this study to accumulate the experimental evidence in support of anti-diabetic effects of isoquercetin. Male albino Wistar rats were divided into seven groups. Rats (Groups 3-7) were administered a single intraperitoneal injection of streptozotocin (STZ; 40 mg/kg b.w) to induce diabetes mellitus. As an extension, STZ rats received isoquercetin at three different doses (20, 40 and 80 mg/kg b.w), and Group 7 rats received glibenclamide (standard drug) (600 µg/kg b.w). The results showed that STZ exaggerated blood sugar, decreased insulin, altered metabolizing enzymes, and impaired the mRNA expression of insulin signaling genes and carbohydrate metabolizing enzyme genes. Supplementation with isoquercetin significantly normalized blood sugar levels, insulin and regulated the mRNA expression of insulin signaling genes and carbohydrate metabolizing enzyme genes. The results achieved with isoquercetin are similar to that of standard drug glibenclamide. The findings suggest isoquercetin could be a possible therapeutic agent for treating diabetes mellitus in the near future.