Enhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study.

Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.

Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults.

As an increasing number of states adopt more permissive cannabis regulations, the necessity of gaining a comprehensive understanding of cannabis's effects on young adults has grown exponentially, driven by its escalating prevalence of use. By leveraging popular eXplainable Artificial Intelligence (XAI) techniques such as SHAP (SHapley Additive exPlanations), rule-based explanations, intrinsically interpretable models, and counterfactual explanations, we undertake an exploratory but in-depth examination of the impact of cannabis use on individual behavioral patterns and physiological states. This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior.

Characterization and structure-functionality analysis of starch in different layers of Lycoris chinensis bulb scales.

According to literature, the size distribution of starch granules varies significantly in different layers of Lycoris chinensis bulb scales, however its effect on structural and physicochemical properties of starch still remains unclear. In this study, outer, middle and inner layers of bulb scales of L. chinensis were compared for starch characteristics.

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 (R = 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.

"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.

The effect of lactic acid bacteria fermentation on physicochemical properties of starch from fermented proso millet flour.

A waxy and a non-waxy proso millet flour were each fermented by Lactobacillus amylovorus, Lactobacillus fermentum, and Lactobacillus plantarum. The samples were fermented for one to five days, and starch was isolated from the fermented flours. The pH of fermented proso millet flour ranged from 3.

Structural and physicochemical properties of bracken fern () 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.

Characterization of starch extracted from seeds of .

Introduction: Starch is major component in the big seeds of , however the characteristics of remain unknown.

Methods: In this study, the physicochemical and structural properties of two starch samples extracted from seeds were systematically investigated, using various techniques.

Results: The amylose contents of the two samples were 34.

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.

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.

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.

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.

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.

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 C-type crystallinity.

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.

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.

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

(black truffle) has been considered as a medicinal mushroom for a long time. 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.

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.