Enhancing Eritadenine Production in Submerged Cultures of Shiitake (Lentinula edodes Berk. Pegler) Using Blue LED Light and Activated Charcoal. Revealing Eritadenine's Novel In Vitro Bioherbicidal Activity Against Chrysanthemum morifolium.

Eritadenine from shiitake mushroom is a secondary metabolite with hypocholesterolemic, hypotensive and antiparasitic properties, thus promising for pharmaceutical and agricultural applications. Eritadenine is obtained from submerged mycelial cultures of shiitake, but the actual yields remain unsatisfactory to explore potential applications or industrial-scale production. In this study, green and blue LED lights were tested to increase yields of eritadenine in submerged cultures of shiitake. Notably, blue LEDs increased yields by 13-14 times, reaching 165.7 mg/L, compared to darkness (11.2 mg/L) and green light (12.1 mg/L) (p < 0.05, Tukey test). Nitrogen sources yeast extract (YE) and peptone (at 2 g/L) increased eritadenine production. YE promoted 22.6 mg/L, while peptone 18.3 mg/L. The recovery of eritadenine was evaluated using amberlite and activated charcoal (AC) adsorption isotherms. AC demonstrated the highest adsorption rate, with 75 mg of eritadenine per gram of AC, according to the Freundlich isotherm. The desorption rate reached 93.95% at pH 10. The extract obtained from submerged cultures had eritadenine content of 63.31%, corresponding to 87.86% of recovery, according to HPLC analysis. Furthermore, the novel bioherbicidal potential of eritadenine was tested on in vitro Chrysanthemum morifolium plants. The cultures extract containing eritadenine had a detrimental impact on plant development, generating mortality of 100% at 3%, 0.5%, and 0.25%. Moreover, pure eritadenine exhibited a phytotoxic effect similar than glyphosate on leaves, stems and roots. These findings highlight the significant bioherbicidal properties of eritadenine. Further studies are needed to understand the biosynthetic pathway of eritadenine and its bioherbicidal properties on weeds and illicit crops.

Comparing Methods for Identifying Post-Market Patient Preferences at the Point of Decision-Making: Insights from Patients with Chronic Pain Considering a Spinal Cord Stimulator Device.

Purpose: To compare three methods for identifying patient preferences (MIPPs) at the point of decision-making: analysis of video-recorded patient-clinician encounters, post-encounter interviews, and post-encounter surveys. Patients and Methods: For the decision of whether to use a spinal cord stimulator device (SCS), a video coding scheme, interview guide, and patient survey were iteratively developed with 30 SCS decision-making encounters in a tertiary academic medical center pain clinic. Burke's grammar of motives was used to classify the attributed source or justification for a potential preference for each preference block. To compare the MIPPs, 13 patients' encounters with their clinician were video recorded and subsequently analyzed by 4 coders using the final video coding scheme. Six of these patients were interviewed, and 7 surveyed, immediately following their encounters. Results: For videos, an average of 66 (range 33-106) sets of utterances potentially indicating a patient preference (a preference block), surveys 33 (range 32-34), and interviews 25 (range 18-30) were identified. Thirty-eight unique themes (75 subthemes), each a preference topic, were identified from videos, surveys 19 themes (12 subthemes), and interviews 39 themes (54 subthemes). The proportion of preference blocks that were judged as expressing a preference that was clearly important to the patient or affected their decision was highest for interviews (72.8%), surveys (68.0%), and videos (27.0%). Videos mostly attributed preferences to the patient's situation (scene) (65%); interviews, the act of receiving or living with SCS (43%); surveys, the purpose of SCS (40%). Conclusion: MIPPs vary in the type of preferences identified and the clarity of expressed preferences in their data sets. The choice of which MIPP to use depends on projects' goals and resources, recognizing that the choice of MIPP may affect which preferences are found.

IAVRS-International Affective Virtual Reality System: Psychometric Assessment of 360° Images by Using Psychophysiological Data.

Virtual Reality is an effective technique for eliciting emotions. It provides immersive and ecologically valid emotional experiences while maintaining experimental control. Recently, novel VR forms like 360° videos have been used successfully for emotion elicitation. Some preliminary databases of 360° videos for emotion elicitation have been proposed, but they tapped mainly into an emotional dimensional approach and did not include a concurrent physiological assessment of an emotional profile. This study expands on these databases by combining dimensional and discrete approaches to validate a new set of 360° emotion-inducing images. Twenty-six participants viewed 46 immersive images, and their emotional reactions were measured using self-reporting, psychophysiological signals, and eye tracking. The IAVRS database can successfully elicit a wide range of emotional responses, including both positive and negative valence, as well as different levels of arousal. Results reveal an important correspondence between the discrete and dimensional models of emotions. Furthermore, the images that exhibit convergence between the dimensional and discrete emotional models are particularly impactful regarding arousal and valence values. The IAVRS database provides insights into potential relationships between physiological parameters and emotional responses. This preliminary investigation highlights the complexity of emotional elicitation processes and their physiological correlates, suggesting the need for further research to deepen our understanding.

Enhancing growth and bioactive metabolites characteristics in Mentha pulegium L. via silicon nanoparticles during in vitro drought stress.

The development and production of secondary metabolites from priceless medicinal plants are restricted by drought stress. Mentha pulegium L. belongs to the Lamiaceae family and is a significant plant grown in the Mediterranean region for its medicinal and aesthetic properties. This study investigated the effects of three polyethylene glycol (PEG) (0, 5, and 10%) as a drought stress inducer and four silicon nanoparticle (SiNP) (0, 25, 50, and 100 ppm) concentrations as an elicitor to overcome the adverse effect of drought stress, on the growth parameters and bioactive chemical composition of M. pulegium L. plants grown in vitro. The experiment was performed as a factorial experiment using a completely randomized design (CRD) consisting of 12 treatments with two factors (3 PEG × 4 SiNPs concentrations), 6 replicates were used for each treatment for a total of 72 experimental units.The percentage of shoot formation was inversely proportional to the PEG concentration; for the highest PEG concentration, the lowest percentage of shoot formation (70.26%) was achieved at 10% PEG. SiNPs at 50 ppm enhanced shoot formation, the number of shoots, shoot height, fresh and dry weight, rosmarinic acid, total phenols, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity. The methanol extract from M. pulegium revealed the presence of significant secondary metabolites using gas chromatography‒mass spectrometry (GC-MS). The principal constituents of the extract were limonene (2.51, 2.99%), linalool (3.84, 4.64%), geraniol (6.49, 8.77%), menthol (59.73, 65.43%), pulegone (3.76, 2.76%) and hexadecanoic acid methyl ester or methyl palmitate (3.2, 4.71%) for the 0 ppm SiNPs, PEG 0% and 50 ppm SiNPs, and PEG 10%, respectively. Most of the chemical components identified by GC‒MS in the methanol extract were greater in the 50 ppm SiNP and 10% PEG treatment groups than in the control group. SiNP improves drought tolerance by regulating biosynthesis and accumulating some osmolytes and lessens the negative effects of polyethylene glycol-induced drought stress.Based on the results, the best treatment for most of the parameters was 50 ppm SiNPs combined with 10% PEG, the morphological and chemical characteristics were inversely proportional to the PEG concentration, as the highest PEG concentration (10%) had the lowest results. Most parameters decreased at the highest SiNP concentration (100 ppm), except for the DPPH scavenging percentage, as there was no significant difference between the 50 and 100 ppm SiNPs.

Content validation of the National Comprehensive Cancer Network/Functional Assessment of Cancer Therapy Lymphoma Symptom Index-18 (NFLymSI-18) in indolent B-cell non-Hodgkin's lymphoma.

BACKGROUND: The NFLymSI-18 is a patient-reported outcome measure comprised of the highest priority symptoms, emotional concerns, treatment side effects, and other concerns identified by lymphoma patients and oncologists. This study assessed the content validity of the NFLymSI-18 for patients with indolent B-cell non-Hodgkin's lymphoma (iNHL), with a focus on the Disease-Related Symptoms Physical (DRS-P) subscale. METHODS: Patients with a confirmed iNHL diagnosis who had received one or more lines of treatment were recruited during clinic visits. Patients described their symptoms, treatment side effects, and emotional concerns related to iNHL in a semi-structured interview. Qualitative data were analyzed using NVivo10. RESULTS: Data saturation was obtained by the 18th interview. Most participants (67%) had follicular lymphoma. 28% of participants had marginal zone lymphoma, and one participant had lymphoplasmacytoid lymphoma/Waldenström macroglobulinemia. Mean age of the 18 participants was 67 years. 56% of the sample was male. Most participants (67%) had a college or advanced degree. When asked to describe their iNHL symptoms, patients most often discussed swelling (n = 14), fatigue (n = 11), and pain (n = 8). The following symptoms were mentioned by three patients each: anxiety, appetite loss, rash, sleep disruption, trouble breathing, and malaise. Mapping of NFLymSI-18 content to these concerns showed the instrument includes all those most frequently mentioned symptoms. CONCLUSIONS: This study supports the content validity of the NFLymSI-18, including its DRS-P Subscale, for patients with iNHL. The instrument shows strong validity for the most referenced symptoms of swelling, fatigue, and pain. The diversity of additional symptoms reported by patients is consistent with the heterogeneous symptomology of iNHL.

A visual approach to facilitating conversations about supportive care options in the context of cognitive impairment.

BACKGROUND: Persons with cognitive impairment may experience difficulties with language and cognition that interfere with their ability to communicate about health-related decision making. OBJECTIVE: We developed a visual elicitation technique to facilitate conversations about preferences concerning potential future supportive care needs and explored the utility of this technique in a qualitative interview study. METHODS: We conducted 15 online interviews with persons with mild cognitive impairment and mild to moderate dementia, using storytelling and a virtual tool designed to facilitate discussion about preferences for supportive care. Interviews were transcribed verbatim and analyzed using an inductive qualitative data analysis method. We report our findings with respect to several main themes. First, we considered participants' perspectives on supportive care. Next, we examined the utility of the tool for engaging participants in conversation through two themes: cognitive and communicative processes exhibited by participants; and dialogic interactions between the interviewer and the participant. RESULTS: With respect to participants' perspectives on supportive care, common themes included considerations relating to informal caregivers such as availability and burden, and the quality of care options such as paid caregivers. Other themes, such as the importance of making decisions as a family, considerations related to facing these challenges on one's own, and the fluid nature of decision making, also emerged. Common communicative processes included not being responsive to the question and unclear responses. Common cognitive processes included uncertainty and introspection, or self-awareness, of their cognitive abilities. Last, we examined dialogic interactions between the participant and the interviewer to better understand engagement with the tool. The interviewer was active in using the visualization tool to facilitate the conversation, and participants engaged with the interface to varying degrees. Some participants expressed greater agency and involvement through suggesting images, elaborating on their or the interviewer's comments, and suggesting icon labels. CONCLUSION: This article presents a visual method to engage older adults with cognitive impairment in active dialogue about complex decisions. Though designed for a research setting, the diverse communication and participant-interviewer interaction patterns observed in this study suggest that the tool might be adapted for use in clinical or community settings.

Multimodal Sensing for Depression Risk Detection: Integrating Audio, Video, and Text Data.

Depression is a major psychological disorder with a growing impact worldwide. Traditional methods for detecting the risk of depression, predominantly reliant on psychiatric evaluations and self-assessment questionnaires, are often criticized for their inefficiency and lack of objectivity. Advancements in deep learning have paved the way for innovations in depression risk detection methods that fuse multimodal data. This paper introduces a novel framework, the Audio, Video, and Text Fusion-Three Branch Network (AVTF-TBN), designed to amalgamate auditory, visual, and textual cues for a comprehensive analysis of depression risk. Our approach encompasses three dedicated branches-Audio Branch, Video Branch, and Text Branch-each responsible for extracting salient features from the corresponding modality. These features are subsequently fused through a multimodal fusion (MMF) module, yielding a robust feature vector that feeds into a predictive modeling layer. To further our research, we devised an emotion elicitation paradigm based on two distinct tasks-reading and interviewing-implemented to gather a rich, sensor-based depression risk detection dataset. The sensory equipment, such as cameras, captures subtle facial expressions and vocal characteristics essential for our analysis. The research thoroughly investigates the data generated by varying emotional stimuli and evaluates the contribution of different tasks to emotion evocation. During the experiment, the AVTF-TBN model has the best performance when the data from the two tasks are simultaneously used for detection, where the F1 Score is 0.78, Precision is 0.76, and Recall is 0.81. Our experimental results confirm the validity of the paradigm and demonstrate the efficacy of the AVTF-TBN model in detecting depression risk, showcasing the crucial role of sensor-based data in mental health detection.

Assurance methods for designing a clinical trial with a delayed treatment effect.

An assurance calculation is a Bayesian alternative to a power calculation. One may be performed to aid the planning of a clinical trial, specifically setting the sample size or to support decisions about whether or not to perform a study. Immuno-oncology is a rapidly evolving area in the development of anticancer drugs. A common phenomenon that arises in trials of such drugs is one of delayed treatment effects, that is, there is a delay in the separation of the survival curves. To calculate assurance for a trial in which a delayed treatment effect is likely to be present, uncertainty about key parameters needs to be considered. If uncertainty is not considered, the number of patients recruited may not be enough to ensure we have adequate statistical power to detect a clinically relevant treatment effect and the risk of an unsuccessful trial is increased. We present a new elicitation technique for when a delayed treatment effect is likely and show how to compute assurance using these elicited prior distributions. We provide an example to illustrate how this can be used in practice and develop open-source software to implement our methods. Our methodology has the potential to improve the success rate and efficiency of Phase III trials in immuno-oncology and for other treatments where a delayed treatment effect is expected to occur.

Cefiderocol for treating severe aerobic Gram-negative bacterial infections: technology evaluation to inform a novel subscription-style payment model.

Background: To limit the use of antimicrobials without disincentivising the development of novel antimicrobials, there is interest in establishing innovative models that fund antimicrobials based on an evaluation of their value as opposed to the volumes used. The aim of this project was to evaluate the population-level health benefit of cefiderocol in the NHS in England, for the treatment of severe aerobic Gram-negative bacterial infections when used within its licensed indications. The results were used to inform the National Institute for Health and Care Excellence guidance in support of commercial discussions regarding contract value between the manufacturer and NHS England. Methods: The health benefit of cefiderocol was first derived for a series of high-value clinical scenarios. These represented uses that were expected to have a significant impact on patients' mortality risks and health-related quality of life. The clinical effectiveness of cefiderocol relative to its comparators was estimated by synthesising evidence on susceptibility of the pathogens of interest to the antimicrobials in a network meta-analysis. Patient-level costs and health outcomes of cefiderocol under various usage scenarios compared with alternative management strategies were quantified using decision modelling. Results were reported as incremental net health effects expressed in quality-adjusted life-years, which were scaled to 20-year population values using infection number forecasts based on data from Public Health England. The outcomes estimated for the high-value clinical scenarios were extrapolated to other expected uses for cefiderocol. Results: Among Enterobacterales isolates with the metallo-beta-lactamase resistance mechanism, the base-case network meta-analysis found that cefiderocol was associated with a lower susceptibility relative to colistin (odds ratio 0.32, 95% credible intervals 0.04 to 2.47), but the result was not statistically significant. The other treatments were also associated with lower susceptibility than colistin, but the results were not statistically significant. In the metallo-beta-lactamase Pseudomonas aeruginosa base-case network meta-analysis, cefiderocol was associated with a lower susceptibility relative to colistin (odds ratio 0.44, 95% credible intervals 0.03 to 3.94), but the result was not statistically significant. The other treatments were associated with no susceptibility. In the base case, patient-level benefit of cefiderocol was between 0.02 and 0.15 quality-adjusted life-years, depending on the site of infection, the pathogen and the usage scenario. There was a high degree of uncertainty surrounding the benefits of cefiderocol across all subgroups. There was substantial uncertainty in the number of infections that are suitable for treatment with cefiderocol, so population-level results are presented for a range of scenarios for the current infection numbers, the expected increases in infections over time and rates of emergence of resistance. The population-level benefits varied substantially across the base-case scenarios, from 896 to 3559 quality-adjusted life-years over 20 years. Conclusion: This work has provided quantitative estimates of the value of cefiderocol within its areas of expected usage within the NHS. Limitations: Given existing evidence, the estimates of the value of cefiderocol are highly uncertain. Future work: Future evaluations of antimicrobials would benefit from improvements to NHS data linkages; research to support appropriate synthesis of susceptibility studies; and application of routine data and decision modelling to assess enablement value. Study registration: No registration of this study was undertaken. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment Policy Research Programme (NIHR award ref: NIHR135591), conducted through the Policy Research Unit in Economic Methods of Evaluation in Health and Social Care Interventions, PR-PRU-1217-20401, and is published in full in Health Technology Assessment; Vol. 28, No. 28. See the NIHR Funding and Awards website for further award information.

This project tested new methods for estimating the value to the NHS of an antimicrobial, cefiderocol, so its manufacturer could be paid fairly even if very little drug is used in order to reduce the risk of bacteria becoming resistant to the product. Clinicians said that the greatest benefit of cefiderocol is when used for complicated urinary tract infections and pneumonia acquired within hospitals caused by two types of bacteria (called Enterobacterales and Pseudomonas aeruginosa), with a resistance mechanism called metallo-beta-lactamase. Because there were no relevant clinical trial data, we estimated how effective cefiderocol and alternative treatments were by doing a systematic literature review of studies that grew bacteria from infections in the laboratory and tested the drugs on them. We linked this to data estimating the long-term health and survival of patients. Some evidence was obtained by asking clinicians detailed questions about what they thought the effects would be based on their experience and the available evidence. We included the side effects of the alternative treatments, some of which can cause kidney damage. We estimated how many infections there would be in the UK, whether they would increase over time and how resistance to treatments may change over time. Clinicians told us that they would also use cefiderocol to treat intra-abdominal and bloodstream infections, and some infections caused by another bacteria called Stenotrophomonas. We estimated how many of these infections there would be, and assumed the same health benefits as for other types of infections. The total value to the NHS was calculated using these estimates. We also considered whether we had missed any additional elements of value. We estimated that the value to the NHS was £18­71 million over 20 years. This reflects the maximum the NHS could pay for use of cefiderocol if the health lost as a result of making these payments rather than funding other NHS services is not to exceed the health benefits of using this antimicrobial. However, these estimates are uncertain due to limitations with the evidence used to produce them and assumptions that had to be made.

Weight of evidence evaluation of the metabolism disrupting effects of triphenyl phosphate using an expert knowledge elicitation approach.

Identification of Endocrine-Disrupting Chemicals (EDCs) in a regulatory context requires a high level of evidence. However, lines of evidence (e.g. human, in vivo, in vitro or in silico) are heterogeneous and incomplete for quantifying evidence of the adverse effects and mechanisms involved. To date, for the regulatory appraisal of metabolism-disrupting chemicals (MDCs), no harmonised guidance to assess the weight of evidence has been developed at the EU or international level. To explore how to develop this, we applied a formal Expert Knowledge Elicitation (EKE) approach within the European GOLIATH project. EKE captures expert judgment in a quantitative manner and provides an estimate of uncertainty of the final opinion. As a proof of principle, we selected one suspected MDC -triphenyl phosphate (TPP) - based on its related adverse endpoints (obesity/adipogenicity) relevant to metabolic disruption and a putative Molecular Initiating Event (MIE): activation of peroxisome proliferator activated receptor gamma (PPARγ). We conducted a systematic literature review and assessed the quality of the lines of evidence with two independent groups of experts within GOLIATH, with the objective of categorising the metabolic disruption properties of TPP, by applying an EKE approach. Having followed the entire process separately, both groups arrived at the same conclusion, designating TPP as a "suspected MDC" with an overall quantitative agreement exceeding 85%, indicating robust reproducibility. The EKE method provides to be an important way to bring together scientists with diverse expertise and is recommended for future work in this area.

Preferences of people with diabetes for diabetes care in Germany: a discrete choice experiment.

OBJECTIVES: The objective of this study is to elicit health care preferences of people with diabetes and identify classes of people with different preferences. METHODS: A discrete choice experiment was conducted among people with diabetes in Germany comprising attributes of role division in daily diabetes care planning, type of lifestyle education, support for correct medication intake, consultation frequency, emotional support, and time spent on self-management. A conditional logit model and a latent class model were used to elicit preferences toward diabetes care and analyze preference heterogeneity. RESULTS: A total of 76 people with diabetes, recruited in two specialized diabetes care centers in Germany (mean age 51.9 years, 37.3% women, 49.1% type 2 diabetes mellitus, 50.9% type 1 diabetes mellitus), completed the discrete choice experiment. The most important attributes were consultation frequency, division in daily diabetes care planning, and correct medication intake. The latent class model detected preference heterogeneity by identifying two latent classes which differ mainly with respect to lifestyle education and medication intake. CONCLUSION: While the majority of people with diabetes showed preferences in line with current health care provision in Germany, a relevant subgroup wished to strengthen lifestyle education and medication intake support with an aid or website.

The Effect of Combined Elicitation with Light and Temperature on the Chlorogenic Acid Content, Total Phenolic Content and Antioxidant Activity of Berula erecta in Tissue Culture.

Chlorogenic acid is one of the most prominent bioactive phenolic acids with great pharmacological, cosmetic and nutritional value. The potential of Berula erecta in tissue culture was investigated for the production of chlorogenic acid and its elicitation combined with light of different wavelengths and low temperature. The content of chlorogenic acid in the samples was determined by HPLC-UV, while the content of total phenolic compounds and the antioxidant activity of their ethanol extracts were evaluated spectrophotometrically. The highest fresh and dry biomasses were obtained in plants grown at 23 °C. This is the first study in which chlorogenic acid has been identified and quantified in Berula erecta. The highest chlorogenic acid content was 4.049 mg/g DW. It was determined in a culture grown for 28 days after the beginning of the experiment at 12 °C and under blue light. The latter also contained the highest content of total phenolic compounds, and its extracts showed the highest antioxidant activity. Berula erecta could, potentially, be suitable for the in vitro production of chlorogenic acid, although many other studies should be conducted before implementation on an industrial scale.

Risk-Adapted Breast Screening for Women at Low Predicted Risk of Breast Cancer: An Online Discrete Choice Experiment.

BACKGROUND: A risk-stratified breast screening program could offer low-risk women less screening than is currently offered by the National Health Service. The acceptability of this approach may be enhanced if it corresponds to UK women's screening preferences and values. OBJECTIVES: To elicit and quantify preferences for low-risk screening options. METHODS: Women aged 40 to 70 y with no history of breast cancer took part in an online discrete choice experiment. We generated 32 hypothetical low-risk screening programs defined by 5 attributes (start age, end age, screening interval, risk of dying from breast cancer, and risk of overdiagnosis), the levels of which were systematically varied between the programs. Respondents were presented with 8 choice sets and asked to choose between 2 screening alternatives or no screening. Preference data were analyzed using conditional logit regression models. The relative importance of attributes and the mean predicted probability of choosing each program were estimated. RESULTS: Participants (N = 502) preferred all screening programs over no screening. An older starting age of screening, younger end age of screening, longer intervals between screening, and increased risk of dying had a negative impact on support for screening programs (P < 0.01). Although the risk of overdiagnosis was of low relative importance, a decreased risk of this harm had a small positive impact on screening choices. The mean predicted probabilities that risk-adapted screening programs would be supported relative to current guidelines were low (range, 0.18 to 0.52). CONCLUSIONS: A deintensified screening pathway for women at low risk of breast cancer, especially one that recommends a later screening start age, would run counter to women's breast screening preferences. Further research is needed to enhance the acceptability of offering less screening to those at low risk of breast cancer. HIGHLIGHTS: Risk-based breast screening may involve the deintensification of screening for women at low risk of breast cancer.Low-risk screening pathways run counter to women's screening preferences and values.Longer screening intervals may be preferable to a later start age.Work is needed to enhance the acceptability of a low-risk screening pathway.

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.

BACKGROUND: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

Natural biosynthesis, pharmacological applications, and sustainable biotechnological production of ornamental plant-derived anthocyanin: beyond colorants and aesthetics.

Flowers have long been admired for their aesthetic qualities and have even found their way to be included in the human diet. Among the many chemical compounds found in flowers, anthocyanins stand out for their versatile applications in the food, cosmetic, and nutraceutical industries. The biosynthetic pathway of anthocyanins has been thoroughly studied in certain flower species, leading to the detection of key regulatory genes that can be controlled to enhance the production of anthocyanins via biotechnological methods. Nevertheless, the quantity and form of anthocyanins found in natural sources differ, both qualitatively and quantitatively, depending on the ornamental plant species. For this reason, research on in vitro plant cultures has been conducted for years in an attempt to comprehend how these essential substances are produced. Different biotechnological systems, like in vitro plant cell, organ, and tissue cultures, and transgenic approaches, have been employed to produce anthocyanins under controlled conditions. However, multiple factors influence the production of anthocyanins and create challenges during large-scale production. Metabolic engineering techniques have also been utilized for anthocyanin production in microorganisms and recombinant plants. Although these techniques are primarily tested at lab- and pilot-scale, limited studies have focused on scaling up the production. This review analyses the chemistry and biosynthesis of anthocyanin along with the factors that influence the biosynthetic pathway. Further emphasis has been given on strategies for conventional and non-conventional anthocyanin production along with their quantification, addressing the prevailing challenges, and exploring ways to ameliorate the production using the in vitro plant cell and tissue culture systems and metabolic engineering to open up new possibilities for the cosmetic, pharmaceutical, and food industries.

Carbon-based nanomaterials as inducers of biocompounds in plants: Potential risks and perspectives.

Biocompounds are metabolites synthesized by plants, with clinically proven capacity in preventing and treating degenerative diseases in humans. Carbon-based nanomaterials (CNMs) are atomic structures that assume different hybridization and shape. Due to the reactive property, CNMs can induce the synthesis of metabolites, such as biocompounds in cells and various plant species, by generating reactive oxygen species (ROS). In response, plants positively or negatively regulate the expression of various families of genes and enzymes involved in physiological and metabolomic pathways of plants, such as carbon and nitrogen metabolism, which are directly involved in plant development and growth. Likewise, ROS can modulate the expression of enzymes and genes related to the adaptation of plants to stress, such as the glutathione ascorbate cycle, the shikimic acid, and phenylpropanoid pathways, from which the largest amount of biocompounds in plants are derived. This document exposes the ability of three CNMs (fullerene, graphene, and carbon nanotubes) to positively or negatively regulate the activity of enzymes and genes involved in various plant species' primary and secondary metabolism. The mechanism of action of CNMs on the production of biocompounds and the effect of the translocation of CNMs on the growth and content of primary metabolites in plants are described. Adverse effects of CNMs on plants, prospects, and possible risks involved are also discussed. The use of CNMs as inducers of biocompounds in plants could have implications and relevance for human health, crop quality, and plant adaptation and resistance to biotic and abiotic stress.

Development of a Conceptual Model of Physical Functioning Limitations Experienced by Patients with Late-Stage Chronic Kidney Disease: A Qualitative Interview Study.

INTRODUCTION: Limitations in physical functioning are common in patients with late-stage chronic kidney disease (CKD) and can greatly affect their lives. Using patient interviews, this study reports experiences associated with physical functioning limitations for patients with late-stage CKD. METHODS: A preliminary conceptual model on concepts relevant to physical functioning limitations in patients with CKD was developed using data from a targeted literature review (patients with CKD stages IV-V) and previous interviews (patients with CKD stages IIIa-IIIb). The preliminary conceptual model informed a semi-structured interview guide designed to capture experiences of physical functioning limitations in patients with CKD. Patients with CKD stages IV-V who were not receiving dialysis were interviewed; their responses were used to develop a comprehensive conceptual model summarizing their experiences associated with physical functioning limitations. RESULTS: A total of 25 patients with CKD stage IV (n = 19) or V (n = 6) were interviewed. Based on patient responses, the reported concepts were grouped into one of six categories: physical functioning limitations/difficulties, behavioural impacts, activity participation restrictions, symptoms attributed to physical functioning limitations, impacts on sleep and emotional functioning impacts related to physical functioning limitations. Twenty-three patients reported concepts associated with physical functioning limitations, most frequently 'walking up and down stairs' (83%) and 'walking distances' (74%). All 23 patients also reported behavioural impacts, including 'need to rest/subsequent periods of rest' (100%) and 'participation in fewer activities' (91%). As well as summarizing the reported concepts, the comprehensive conceptual model shows how concepts may relate to one another; for example, challenging symptoms or difficulty completing tasks can lead to changes in patient behaviour such as purposely reducing or avoiding activities. CONCLUSIONS: This study found that patients with late-stage CKD not receiving dialysis who experience physical functioning limitations report a range of impacts on their daily lives. The comprehensive conceptual model summarizes the concepts reported and the relationships between them, providing a holistic understanding of how patients with late-stage CKD are affected by physical functioning limitations. Infographic available for this article. INFOGRAPHIC.

Content Validity of the Modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA) Instrument in Spinocerebellar Ataxia.

The functional Scale for the Assessment and Rating of Ataxia (f-SARA) assesses Gait, Stance, Sitting, and Speech. It was developed as a potentially clinically meaningful measure of spinocerebellar ataxia (SCA) progression for clinical trial use. Here, we evaluated content validity of the f-SARA. Qualitative interviews were conducted among individuals with SCA1 (n = 1) and SCA3 (n = 6) and healthcare professionals (HCPs) with SCA expertise (USA, n = 5; Europe, n = 3). Interviews evaluated symptoms and signs of SCA and relevance of f-SARA concepts for SCA. HCP cognitive debriefing was conducted. Interviews were recorded, transcribed, coded, and analyzed by ATLAS.TI software. Individuals with SCA1 and 3 reported 85 symptoms, signs, and impacts of SCA. All indicated difficulties with walking, stance, balance, speech, fatigue, emotions, and work. All individuals with SCA1 and 3 considered Gait, Stance, and Speech relevant f-SARA concepts; 3 considered Sitting relevant (42.9%). All HCPs considered Gait and Speech relevant; 5 (62.5%) indicated Stance was relevant. Sitting was considered a late-stage disease indicator. Most HCPs suggested inclusion of appendicular items would enhance clinical relevance. Cognitive debriefing supported clarity and comprehension of f-SARA. Maintaining current abilities on f-SARA items for 1 year was considered meaningful for most individuals with SCA1 and 3. All HCPs considered meaningful changes as stability in f-SARA score over 1-2 years, 1-2-point change in total f-SARA score, and deviation from natural history. These results support content validity of f-SARA for assessing SCA disease progression in clinical trials.

The centrality of food in Norwegian adolescents' life; a photo elicitation study among Norwegian youth.

The purpose of the study was to explore how adolescents from a high school in Viken county define and interact with food systems in their immediate environments to understand if and how health and sustainability affect their food choices. A qualitative case study design and a participatory approach were employed. Data were collected through photo elicitation combined with group interviews. Pictures were analyzed in collaboration with participants, and the group interview through systematic text condensation. Results indicate that adolescents perceive food systems as being a substantial part of their everyday life, that they care about their health and that of the planet, and they wish to take sustainability and health into consideration when making food choices. Their food choices are affected by aspects such as family, friends, marketing, price, time, availability and accessibility. They perceive that their agency to influence their own diet and food systems is limited. Adolescents hold unique and important knowledge of their food-related behaviors and value their autonomy to make food choices. Future research and policies aiming to help adolescents make healthy and sustainable food choices should therefore actively include adolescents.

Influence of Abiotic and Biotic Elicitors on Organogenesis, Biomass Accumulation, and Production of Key Secondary Metabolites in Asteraceae Plants.

The medicinal plants of the Asteraceae family are a valuable source of bioactive secondary metabolites, including polyphenols, phenolic acids, flavonoids, acetylenes, sesquiterpene lactones, triterpenes, etc. Under stressful conditions, the plants develop these secondary substances to carry out physiological tasks in plant cells. Secondary Asteraceae metabolites that are of the greatest interest to consumers are artemisinin (an anti-malarial drug from Artemisia annua L.-sweet wormwood), steviol glycosides (an intense sweetener from Stevia rebaudiana Bert.-stevia), caffeic acid derivatives (with a broad spectrum of biological activities synthesized from Echinacea purpurea (L.) Moench-echinacea and Cichorium intybus L.-chicory), helenalin and dihydrohelenalin (anti-inflammatory drug from Arnica montana L.-mountain arnica), parthenolide ("medieval aspirin" from Tanacetum parthenium (L.) Sch.Bip.-feverfew), and silymarin (liver-protective medicine from Silybum marianum (L.) Gaertn.-milk thistle). The necessity to enhance secondary metabolite synthesis has arisen due to the widespread use of these metabolites in numerous industrial sectors. Elicitation is an effective strategy to enhance the production of secondary metabolites in in vitro cultures. Suitable technological platforms for the production of phytochemicals are cell suspension, shoots, and hairy root cultures. Numerous reports describe an enhanced accumulation of desired metabolites after the application of various abiotic and biotic elicitors. Elicitors induce transcriptional changes in biosynthetic genes, leading to the metabolic reprogramming of secondary metabolism and clarifying the mechanism of the synthesis of bioactive compounds. This review summarizes biotechnological investigations concerning the biosynthesis of medicinally essential metabolites in plants of the Asteraceae family after various elicitor treatments.