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Abstract Aquilaria sinensis is a significant resin-producing plant worldwide that is crucial for agarwood production. Agarwood has different qualities depending on the method with which it is formed, and the microbial community structures that are present during these methods are also diverse. Furthermore, the microbial communities of plants play crucial roles in determining their health and productivity. While previous studies have investigated the impact of microorganisms on agarwood formation, they lack comprehensiveness, particularly regarding the properties of the microbial community throughout the entire process from seedling to adult to incense formation. We collected roots, stems, leaves, flowers, fruits and other tissues from seedlings, healthy plants and agarwood-producing plants to address this gap and assess the dominant bacterial species in the microbial community structures of A. sinensis at different growth stages and their impacts on growth and agarwood formation. The bacteria and fungi in these tissues were classified and counted from different perspectives. The samples were sequenced using the Illumina sequencing platform, and sequence analyses and species annotations were performed using a range of bioinformatics tools to assess the plant community compositions. An additional comparison of the samples was conducted using diversity analyses to assess their differences. This research revealed that Listeria, Kurtzmanomyces, Ascotaiwania, Acinetobacter, Sphingobium, Fonsecaea, Acrocalymma, Allorhizobium, Bacillus, Pseudomonas, Peethambara, and Debaryomyces are potentially associated with the formation of agarwood. Overall, the data provided in this article help us understand the important roles played by bacteria and fungi in the growth and agarwood formation process of A. sinensis, will support the theoretical basis for the large-scale cultivation of A. sinensis, and provide a basis for further research on microbial community applications in agarwood production and beyond.

Abstract A wide variety of metabolic gene clusters exist in eukaryotic genomes, but fatty acid metabolic gene clusters have not been discovered. Here, combining with metabolic and phenotypic genome-wide association studies, we identify a major locus containing a six-gene fatty acid metabolic gene cluster on chromosome 3 (FGC3) that controls the cutin monomer hydroxymonoacylglycerols (HMGs) contents and rice yield, possibly through variation in the transcription of FGC3 members. We show that HMGs are sequentially synthesized in the endoplasmic reticulum by OsFAR2, OsKCS11, OsGPAT6, OsCYP704B2 and subsequently transported to the apoplast by OsABCG22 and OsLTPL82. Mutation of FGC3 members reduces HMGs, leading to defective male reproductive development and a significant decrease in yield. OsMADS6 and OsMADS17 directly regulate FGC3 and thus influence male reproduction and yield. FGC3 is conserved in Poaceae and likely formed prior to the divergence of Pharus latifolius. The eukaryotic fatty acid and plant primary metabolic gene cluster we identified show a significant impact on the origin and evolution of Poaceae and has potential for application in hybrid crop breeding.

Abstract In plants due to their sessile nature, secondary metabolites are important components against different abiotic and biotic stress, such as extended darkness. For this reason, the variation of secondary metabolite content of the Arabidopsis thaliana HapMap natural population following 0-and 6-d darkness treatment were detected and the raw data of different accessions at two timepoints were deposited in the Zenodo database. Moreover, the annotated secondary metabolites of these samples are presented in this data descriptor, which we believe will be a usefully re-usable resource for future integrative analysis with dark-treated transcripts, proteins or other phenotypic data in order to comprehensively illustrate the multiomic landscape of Arabidopsis in response to the stresses exerted by extended darkness.

Jasmonic acid is a crucial phytohormone that plays a pivotal role, serving as a regulator to balancing plant development and resistance. However, there are analogous and distinctive characteristics exhibited in JA biosynthesis, perception, and signal transduction pathways in both herbaceous and woody plants. Moreover, the majority of research subjects have predominantly focused on the function of JA in model or herbaceous plants. Consequently, there is a significant paucity of studies investigating JA regulation networks in woody plants, particularly concerning post-transcriptional regulatory events such as alternative splicing (AS). This review article aims to conduct a comprehensive summary of advancements that JA signals regulate plant development across various woody species, comparing the analogous features and regulatory differences to herbaceous counterparts. In addition, we summarized the involvement of AS events including splicing factor (SF) and transcripts in the JA regulatory network, highlighting the effectiveness of high-throughput proteogenomic methods. A better understanding of the JA signaling pathway in woody plants has pivotal implications for forestry production, including optimizing plant management and enhancing secondary metabolite production.

Abstract Acinetobacter baumannii is without a doubt one of the most problematic bacteria causing hospital-acquired nosocomial infections in today's healthcare system. To solve the high prevalence of multi-drug resistant (MDR) in A. baumannii, we investigated one of the medicinal plants traditionally used as antibacterial agent; namely Murraya koenigii (L.) Sprengel. The total methanolic extracts of seeds and pericarps were prepared and their anti-bacterial activity was assessed using the agar diffusion method and minimum inhibitory concentration (MIC) was then calculated as compared to tigecycline. Then, an in-vivo murine model was established which confirmed the promising activity of M. koenigii seeds in demonstrating anti-bacterial and anti-inflammatory actions. The histopathological study of lungs, scoring of pulmonary lesions, counting of bacterial loads after infection by multi-drug resistant A. baumannii all provided evidence to support these findings. LC–MS/MS profiling coupled to molecular networking and chemometrics detected the presence of carbazole alkaloids, and coumarins as dominate metabolites of the active seed extracts. Positively correlated metabolites to antibacterial potential were 6-(2ʹ,3ʹ-dihydroxy-3-methylbutyl)-8-prenylumbelliferone, scopoline, and 5-methoxymurrayatin. An in-silico study was also performed on the crystal structure of MurF from A. baumannii (PDB ID: 4QF5), the studied structures of the mentioned extracts revealed good docking interaction at the active site suggestive of competition with the ATP ligand. These collective findings suggest that extracts of Murraya koenigii (L.) Sprengel seed is a novel prospective for the discovery of drug candidates against infections caused by MDR A. baumannii.

Abstract Background Decubitus ulcers are prevalent among the aging population due to a gradual decline in their overall health, such as nutrition, mental health, and mobility, resulting in injury to the skin and tissue. The most common technique to prevent these ulcers is through frequent repositioning to redistribute body pressures. Therefore, the main goal of this study is to facilitate the timely repositioning of patients through the use of a pressure mat to identify in-bed postures in various sleep environments. Pressure data were collected from 10 healthy participants lying down on a pressure mat in 19 various in-bed postures, correlating to the supine, prone, right-side, and left-side classes. In addition, pressure data were collected from participants sitting at the edge of the bed as well as an empty bed. Each participant was asked to lie in these 19 postures in three distinct testing environments: a hospital bed, a home bed, and a home bed with a foam mattress topper. To categorize each posture into its respective class, the pre-trained 2D ResNet-18 CNN and the pre-trained Inflated 3D CNN algorithms were trained and validated using image and video pressure mapped data, respectively. Results The ResNet-18 and Inflated 3D CNN algorithms were validated using leave-one-subject-out (LOSO) and leave-one-environment-out (LOEO) cross-validation techniques. LOSO provided an average accuracy of 92.07% ± 5.72% and 82.22% ± 8.50%, for the ResNet-18 and Inflated 3D CNN algorithms, respectively. Contrastingly, LOEO provided a reduced average accuracy of 85.37% ± 14.38% and 77.79% ± 9.76%, for the ResNet-18 and Inflated 3D CNN algorithms, respectively. Conclusion These pilot results indicate that the proposed algorithms can accurately distinguish between in-bed postures, on unseen participant data as well as unseen mattress environment data. The proposed algorithms can establish the basis of a decubitus ulcer prevention platform that can be applied to various sleeping environments. To the best of our knowledge, the impact of mattress stiffness has not been considered in previous studies regarding in-bed posture monitoring.

Autophagy is a process of cellular self-eating, which allows organisms to eliminate and recycle unwanted components and damaged organelles to maintain cellular homeostasis. It is an important process in the development of eukaryotic organisms. Autophagy plays a critical role in many physiological processes in plants such as nutrient remobilization, cell death, immunity, and abiotic stress responses. Autophagy thus represents an obvious target for generating resilient crops. During plant development, autophagy is also implicated in the differentiation and maturation of various cell types and plant organs, including root cap cells, tracheary elements, gametes, fruits and seeds. Here, we review our current understanding and recent advances of plant autophagy including insight into autophagy regulation and signaling as well as autophagosome membrane biogenesis. In addition, we describe how autophagy contributes to development, metabolism, biotic and abiotic stress tolerance and where the autophagic field is heading in terms of applied research for crop improvement.

Domesticated crops have been disseminated by humans over vast geographic areas. Common bean (Phaseolus vulgaris L.) was introduced in Europe after 1492. Here, by combining whole-genome profiling, metabolic fingerprinting and phenotypic characterisation, we show that the first common bean cultigens successfully introduced into Europe were of Andean origin, after Francisco Pizarro's expedition to northern Peru in 1529. We reveal that hybridisation, selection and recombination have shaped the genomic diversity of the European common bean in parallel with political constraints. There is clear evidence of adaptive introgression into the Mesoamerican-derived European genotypes, with 44 Andean introgressed genomic segments shared by more than 90% of European accessions and distributed across all chromosomes except PvChr11. Genomic scans for signatures of selection highlight the role of genes relevant to flowering and environmental adaptation, suggesting that introgression has been crucial for the dissemination of this tropical crop to the temperate regions of Europe.

Abstract Background Tartary buckwheat, Fagopyrum tataricum, is a pseudocereal crop with worldwide distribution and high nutritional value. However, the origin and domestication history of this crop remain to be elucidated. Results Here, by analyzing the population genomics of 567 accessions collected worldwide and reviewing historical documents, we find that Tartary buckwheat originated in the Himalayan region and then spread southwest possibly along with the migration of the Yi people, a minority in Southwestern China that has a long history of planting Tartary buckwheat. Along with the expansion of the Mongol Empire, Tartary buckwheat dispersed to Europe and ultimately to the rest of the world. The different natural growth environments resulted in adaptation, especially significant differences in salt tolerance between northern and southern Chinese Tartary buckwheat populations. By scanning for selective sweeps and using a genome-wide association study, we identify genes responsible for Tartary buckwheat domestication and differentiation, which we then experimentally validate. Comparative genomics and QTL analysis further shed light on the genetic foundation of the easily dehulled trait in a particular variety that was artificially selected by the Wa people, a minority group in Southwestern China known for cultivating Tartary buckwheat specifically for steaming as a staple food to prevent lysine deficiency. Conclusions This study provides both comprehensive insights into the origin and domestication of, and a foundation for molecular breeding for, Tartary buckwheat.

Abstract Background Tele-rehabilitation, also known as tele-rehab, uses communication technologies to provide rehabilitation services from a distance. The COVID-19 pandemic has highlighted the importance of tele-rehab, where the in-person visits declined and the demand for remote healthcare rises. Tele-rehab offers enhanced accessibility, convenience, cost-effectiveness, flexibility, care quality, continuity, and communication. However, the current systems are often not able to perform a comprehensive movement analysis. To address this, we propose and validate a novel approach using depth technology and skeleton tracking algorithms. Methods Our data involved 14 participants (8 females, 6 males) performing shoulder abduction exercises. We collected depth videos from an LiDAR camera and motion data from a Motion Capture (Mocap) system as our ground truth. The data were collected at distances of 2 m, 2.5 m, and 3.5 m from the LiDAR sensor for both arms. Our innovative approach integrates LiDAR with the Cubemos and Mediapipe skeleton tracking frameworks, enabling the assessment of 3D joint angles. We validated the system by comparing the estimated joint angles versus Mocap outputs. Personalized calibration was applied using various regression models to enhance the accuracy of the joint angle calculations. Results The Cubemos skeleton tracking system outperformed Mediapipe in joint angle estimation with higher accuracy and fewer errors. The proposed system showed a strong correlation with Mocap results, although some deviations were present due to noise. Precision decreased as the distance from the camera increased. Calibration significantly improved performance. Linear regression models consistently outperformed nonlinear models, especially at shorter distances. Conclusion This study showcases the potential of a marker-less system, to proficiently track body joints and upper-limb angles. Signals from the proposed system and the Mocap system exhibited robust correlation, with Mean Absolute Errors (MAEs) consistently below $$10^\circ$$ 10 ∘ . LiDAR’s depth feature enabled accurate computation of in-depth angles beyond the reach of traditional RGB cameras. Altogether, this emphasizes the depth-based system’s potential for precise joint tracking and angle calculation in tele-rehab applications.

Abstract The evaluation of plant-based feedstocks is an important aspect of biorefining. Nicotiana glauca is a solanaceous, non-food crop that produces large amounts of biomass and is well adapted to grow in suboptimal conditions. In the present article, compatible sequential solvent extractions were applied to N. glauca leaves to enable the generation of enriched extracts containing higher metabolite content comparing to direct leaf extracts. Typically, between 60 to 100 metabolite components were identified within the fractions. The occurrence of plant fatty acids, fatty acid alcohols, alkanes, sterols and terpenoids was detected by gas liquid chromatography–mass spectrometry (GC–MS) and metabolite identification was confirmed by comparison of physico-chemical properties displayed by available authentic standards. Collectively, co-products such waxes, oils, fermentable sugars, and terpenoids were all identified and quantified. The enriched fractions of N. glauca revealed a high level of readily extractable hydrocarbons, oils and high value co-products. In addition, the saccharification yield and cell wall composition analyses in the stems revealed the potential of the residue material as a promising lignocellulosic substrate for the production of fermentable sugars. In conclusion a multifractional cascade for valuable compounds/commodities has been development, that uses N. glauca biomass. These data have enabled the evaluation of N. glauca material as a potential feedstock for biorefining. Graphical Abstract

Formic acid is reported to act as a food preservative and feed additive, but its effects on controlling postharvest physiological deterioration (PPD) development in cassava are unclear. In this study, we assessed the effectiveness of different concentrations of formic acid in attenuating PPD occurrence in fresh-cut cassava. The results showed that the concentration of 0.1% (v/v) formic acid could significantly delay the occurrence of PPD, and that the higher the concentration of formic acid supplied, the later the occurrence of PPD symptoms. The physiological and biochemical analysis of 0.5%-formic-acid-treated cassava slices revealed that formic acid decreased the degradation of starch, inhibited the accumulation of hydrogen peroxide (H2O2), malondialdehyde (MDA), and water-soluble pectin in cassava slices with PPD development, and increased the activities of the antioxidant enzymes ascorbate peroxidase (APX) and glutathione reductase (GR). A microscopic observation showed that the formic acid treatment inhibited the enlargement of the intercellular space during the cassava PPD process, which suggests that the formation of an intercellular layer of the cell wall was inhibited by formic acid. This study thus revealed the mechanism used by formic acid to extend the cassava shelf life; however, a detailed evaluation of the possible side effects on, for example, the cyanide content will be needed to categorically ensure the safety of this method.

A key best practice to prevent and treat pressure injuries (PIs) is to ensure at-risk individuals are repositioned regularly. Our team designed a non-contact position detection system that predicts an individual’s position in bed using data from load cells under the bed legs. The system was originally designed to predict the individual’s position as left-side lying, right-side lying, or supine. Our previous work suggested that a higher precision for detecting position (classifying more than three positions) may be needed to determine whether key bony prominences on the pelvis at high risk of PIs have been off-loaded. The objective of this study was to determine the impact of categorizing participant position with higher precision using the system prediction F1 score. Data from 18 participants was collected from four load cells placed under the bed legs and a pelvis-mounted inertial measurement unit while the participants assumed 21 positions. The data was used to train classifiers to predict the participants’ transverse pelvic angle using three different position bin sizes (45°, ~30°, and 15°). A leave-one-participant-out cross validation approach was used to evaluate classifier performance for each bin size. Results indicated that our prediction F1 score dropped as the position category precision was increased.

Despite recent advances in crop metabolomics, the genetic control and molecular basis of the wheat kernel metabolome at different developmental stages remain largely unknown. Here, we performed widely targeted metabolite profiling of kernels from three developmental stages (grain-filling kernels [FKs], mature kernels [MKs], and germinating kernels [GKs]) using a population of 159 recombinant inbred lines. We detected 625 annotated metabolites and mapped 3173, 3143, and 2644 metabolite quantitative trait loci (mQTLs) in FKs, MKs, and GKs, respectively. Only 52 mQTLs were mapped at all three stages, indicating the high stage specificity of the wheat kernel metabolome. Four candidate genes were functionally validated by in vitro enzymatic reactions and/or transgenic approaches in wheat, three of which mediated the tricin metabolic pathway. Metabolite flux efficiencies within the tricin pathway were evaluated, and superior candidate haplotypes were identified, comprehensively delineating the tricin metabolism pathway in wheat. Finally, additional wheat metabolic pathways were re-constructed by updating them to incorporate the 177 candidate genes identified in this study. Our work provides new information on variations in the wheat kernel metabolome and important molecular resources for improvement of wheat nutritional quality.

Reactive oxygen species are, at high levels, harmful to plant cells, whereas, at a balanced and controlled level, they are involved in transduction of oxidative signaling. The apoplast, also known as the extracellular matrix plays a vital role in transferring the extracellular signals to internal organelles and the signal from cell to cell. Moreover, having a lower level of antioxidants renders it a favorable compartment for ROS production and maintenance. Multiple routes for H2O2 production exist in the apoplast; however, a prominent source is the NADPH oxidases, also named respiratory burst oxidase homologs (RBOHs). Many stimuli, such as pathogens, extracellular ATP, hormones, and abiotic stresses can trigger the RBOH-dependent ROS production in the apoplast. RBOHD and RBOHF are extensively studied and proposed typical roles in stomatal conductance and pathogen responses. In this review, we provide an update on RBOH enzymes and the regulatory mechanisms controlling the key enzyme of the family, RBOHD. Furthermore, we performed a phylogenetic analysis by including the RBOH protein family of Arabidopsis and some important crop species which have not been studied before, such as Brasssica rapa, Brassica oleracea, Oriza sativa, Glycine max, and Zea mays to characterize the evolutionary relationship of these isoforms in order to better classify them. We further describe how ROS are perceived and transduced inside the cell and how this interlinks with other systemic signals, including hormones, and abiotic stress responses such as those toward light and salt stress.

Abstract Photorespiration (PR) is the pathway that detoxifies the product of the oxygenation reaction of Rubisco. It has been hypothesized that in dynamic light environments, PR provides a photoprotective function. To test this hypothesis, we characterized plants with varying PR enzyme activities under fluctuating and non-fluctuating light conditions. Contrasting our expectations, growth of mutants with decreased PR enzyme levels was least affected in fluctuating light compared with wild type. Results for growth, photosynthesis and metabolites combined with thermodynamics-based flux analysis revealed two main causal factors for this unanticipated finding: reduced rates of photosynthesis in fluctuating light and complex re-routing of metabolic fluxes. Only in non-fluctuating light, mutants lacking the glutamate:glyoxylate aminotransferase 1 re-routed glycolate processing to the chloroplast, resulting in photooxidative damage through H2O2 production. Our results reveal that dynamic light environments buffer plant growth and metabolism against photorespiratory perturbations.

Abstract Background People living with chronic obstructive pulmonary disease (COPD) have an increased risk of experiencing cardiovascular (CV) events, particularly after an exacerbation. Such CV burden is not yet known for incident COPD patients. We examined the risk of severe CV events in incident COPD patients in periods following either moderate and/or severe exacerbations. Methods Persons aged ≥ 40 years with an incident COPD diagnosis from the PHARMO Data Network were included. Exposed time periods included 1–7, 8–14, 15–30, 31–180 and 181–365 days following an exacerbation. Moderate exacerbations were defined as those managed in outpatient settings; severe exacerbations as those requiring hospitalisation. The outcome was a composite of time to first severe CV event (acute coronary syndrome, heart failure decompensation, cerebral ischaemia, or arrhythmia) or death. Hazard ratios (HR) were estimated for association between each exposed period and outcome. Results 8020 patients with newly diagnosed COPD were identified. 2234 patients (28%) had ≥ 1 exacerbation, 631 patients (8%) had a non-fatal CV event, and 461 patients (5%) died during a median follow-up of 36 months. The risk of experiencing the composite outcome was increased following a moderate/severe exacerbation as compared to time periods of stable disease [range of HR: from 15.3 (95% confidence interval 11.8–20.0) in days 1–7 to 1.3 (1.0–1.8) in days 181–365]. After a moderate exacerbation, the risk was increased over the first 180 days [HR 2.5 (1.3–4.8) in days 1–7 to 1.6 (1.3–2.1) in days 31–180]. After a severe exacerbation, the risk increased substantially and remained higher over the year following the exacerbation [HR 48.6 (36.9–64.0) in days 1–7 down to 1.6 (1.0–2.6) in days 181–365]. Increase in risk concerned all categories of severe CV events. Conclusions Among incident COPD patients, we observed a substantial risk increase of severe CV events or all-cause death following either a moderate or severe exacerbation of COPD. Increase in risk was highest in the initial period following an exacerbation. These findings highlight the significant cardiopulmonary burden among people living with COPD even with a new diagnosis.

Abstract Enhancing the dietary properties of rice is crucial to contribute to alleviating hidden hunger and non-communicable diseases in rice-consuming countries. Germination is a bioprocessing approach to increase the bioavailability of nutrients in rice. However, there is a scarce information on how germination impacts the overall nutritional profile of pigmented rice sprouts (PRS). Herein, we demonstrated that germination resulted to increase levels of certain dietary compounds, such as free phenolics and micronutrients (Ca, Na, Fe, Zn, riboflavin, and biotin). Metabolomic analysis revealed the preferential accumulation of dipeptides, GABA, and flavonoids in the germination process. Genome-wide association studies of the PRS suggested the activation of specific genes such as CHS1 and UGT genes responsible for increasing certain flavonoid compounds. Haplotype analyses showed a significant difference (P

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources.

Abstract Background Plants growing in the field are subjected to combinations of abiotic stresses. These conditions pose a devastating threat to crops, decreasing their yield and causing a negative economic impact on agricultural production. Metabolic responses play a key role in plant acclimation to stress and natural variation for these metabolic changes could be key for plant adaptation to fluctuating environmental conditions. Results Here we studied the metabolomic response of two Arabidopsis ecotypes (Columbia-0 [Col] and Landsberg erecta-0 [Ler]), widely used as genetic background for Arabidopsis mutant collections, subjected to the combination of high salinity and increased irradiance. Our findings demonstrate that this stress combination results in a specific metabolic response, different than that of the individual stresses. Although both ecotypes displayed reduced growth and quantum yield of photosystem II, as well as increased foliar damage and malondialdehyde accumulation, different mechanisms to tolerate the stress combination were observed. These included a relocation of amino acids and sugars to act as potential osmoprotectants, and the accumulation of different stress-protective compounds such as polyamines or secondary metabolites. Conclusions Our findings reflect an initial identification of metabolic pathways that differentially change under stress combination that could be considered in studies of stress combination of Arabidopsis mutants that include Col or Ler as genetic backgrounds.

Abstract Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.

Real-time gait monitoring of older adults and gait-impaired individuals while providing real-time biofeedback has the potential to help reduce trip-related falls. A low or unsuccessful Minimum Toe Clearance (MTC) is considered a predictor of tripping risk. Thus, increasing the MTC can be a key component in minimizing the likelihood of tripping. This paper discusses a proof-of-concept wearable system that estimates the MTC in real-time using two Time-of-Flight (ToF) sensors and provides auditory biofeedback to alert users if they have a low MTC during everyday walking activities. Ten healthy female adults were asked to perform two experiments: 1) walk at a predetermined speed to evaluate the proposed real-time MTC detection algorithm, and 2) walk in four conditions: baseline, biofeedback with no distraction, biofeedback with distraction 1 (talking on the phone), and biofeedback with distraction 2 (playing a simple mobile game). The average MTC values were significantly greater during all feedback conditions than the baseline, indicating that the proposed system could successfully warn users to increase their MTC in real-time.

Tele-rehabilitation (Tele-rehab) is changing the landscape of virtual care by redefining assessment and breaking accessibility barriers as a convenient substitute for conventional rehabilitation. The COVID-19 pandemic resulted in a rapid uptake of virtual care. Researchers and health professionals have started developing new tele-rehab platforms, e.g., in the form of video conferencing. Albeit useful, these platforms still require the clinicians’ time and energy. Integrating a biofeedback system that can reliably distinguish between “Correctly Executed” from “Incorrectly Executed” exercises into tele-rehab platforms can help patients to perform rehab exercises correctly, avoid injuries, and enhance recovery. To address this gap, this paper proposes an automated system that uses machine learning to classify correct and incorrect executions of 9 rehabilitation gestures. The model is trained on 24 angle signals extracted from different body sections. The angle signals are obtained in 3D space, and 10 features are extracted from each signal. Six different classifiers, including Random Forest, Multi-Layer Perceptron Artificial Neural Networks, Naïve Bayes, Support Vector Machine, K-Nearest Neighbors, and Logistic Regression, are used, and evaluated with 10-Fold and Leave One Subject Out (LOSO) cross validations. The best classifiers achieved an average accuracy of 89.86% ± 3.38% and F1-Score of 72.84% ± 11.98% for 10-Fold and an average accuracy of 88.21% ± 3.90% and F1-Score of 68.16%±13.28% for LOSO. The proposed system has great potential to be integrated into tele-rehab platforms to help patients perform their exercises reliably.© 2017 Elsevier Inc. All rights reserved.