Quantum machine learning has made remarkable progress in many important tasks. However, the gate complexity of the initial state preparation is seldom considered in lots of quantum machine learning algorithms, making them non-end-to-end. Herein, we propose a quantum algorithm for the node embedding problem that maps a node graph\'s topological structure to embedding vectors. The resulting quantum embedding state can be used as an input for other quantum machine learning algorithms. With O ( log ( N ) ) qubits to store the information of N nodes, our algorithm will not lose quantum advantage for the subsequent quantum information processing. Moreover, owing to the use of a parameterized quantum circuit with O ( poly ( log ( N ) ) ) depth, the resulting state can serve as an efficient quantum database. In addition, we explored the measurement complexity of the quantum node embedding algorithm, which is the main issue in training parameters, and extended the algorithm to capture high-order neighborhood information between nodes. Finally, we experimentally demonstrated our algorithm on an nuclear magnetic resonance quantum processor to solve a graph model.

Cyclic peptides present a robust platform for drug design, offering high specificity and stability due to their conformationally constrained structures. In this study, we introduce an updated version of the Cyclic Peptide Matching program (cPEPmatch) tailored for the identification of cyclic peptides capable of mimicking protein-glycosaminoglycan (GAG) binding sites. We focused on engineering cyclic peptides to replicate the GAG-binding affinity of antithrombin III (ATIII), a protein that plays a crucial role in modulating anticoagulation through interaction with the GAG heparin. By integrating computational and experimental methods, we successfully identified a cyclic peptide binder with promising potential for future optimization. MD simulations and MM-GBSA calculations were used to assess binding efficacy, supplemented by umbrella sampling to approximate free energy landscapes. The binding specificity was further validated through NMR and ITC experiments. Our findings demonstrate that the computationally designed cyclic peptides effectively target GAGs, suggesting their potential as novel therapeutic agents. This study advances our understanding of peptide-GAG interactions and lays the groundwork for future development of cyclic peptide-based therapeutics.

Aquaculture contributes to the sustainable development of food security, marine resource conservation, and economy. Shifting aquaculture feed from fish meal and oil to terrestrial plant derivatives may result in cost savings. However, many carnivorous fish cannot be sustained on plant-derived materials, necessitating the need for the identification of important factors for farmed fish growth and the identification of whether components derived from terrestrial plants can be used in feed. Herein, we focused on the carnivorous fish leopard coral grouper (P. leopardus) to identify the essential growth factors and clarify their intake timing from feeds. Furthermore, we evaluated the functionality of starch, which are easily produced by terrestrial plants. Results reveal that carbohydrates, which are not considered essential for carnivorous fish, can be introduced as a major part of an artificial diet. The development of artificial feed using starch offers the possibility of increasing the growth of carnivorous fish in aquaculture.

Fermentation-a process of compound degradation by microorganisms-is a traditional food processing method utilized worldwide for the long-term preservation of fresh foods. In recent years, fermented foods have gained attention as health foods. Fermentation increases the nutritional value of ingredients, producing complex flavors and aromas. To identify unknown components in fermented foods, it is necessary to analyze compounds and conditions nondestructively and comprehensively. We performed intact-state nuclear magnetic resonance (NMR) spectroscopy using intermolecular single quantum coherence (iSQC) to detect the degradation of vegetables directly and nondestructively. We used two types of vegetables and a rice bran bed (nukazuke), which is used for traditional vegetable fermentation in Japan. Major metabolites such as saccharides, organic acids, and amino acids were identified in iSQC-sliced spectra. Comparing NMR signal intensities during degradation revealed the transition of metabolites characteristic of lactic acid fermentation. A pathway-based network analysis showed pathways involved in amino acid metabolism and lactic acid fermentation. Our analytical approach with intact-state NMR spectroscopy using iSQC demonstrated that it may be effective in other experimental systems, allowing for the evaluation of phenomena that have been conventionally overlooked in their true state.

Amyotrophic lateral sclerosis (ALS) is a fatal neuromuscular disease type of motor neuron disorder characterized by degeneration of the upper and lower motor neurons resulting in dysfunction of the somatic muscles of the body. The ALS condition is manifested in progressive skeletal muscle atrophy and spasticity. It leads to death, mostly due to respiratory failure. Within the pathophysiology of the disease, muscle energy metabolism seems to be an important part. In our study, we used blood plasma from 25 patients with ALS diagnosed by definitive El Escorial criteria according to ALSFR-R (Revised Amyotrophic Lateral Sclerosis Functional Rating Scale) criteria and 25 age and sex-matched subjects. Aside from standard clinical biochemical parameters, we used the NMR (nuclear magnetic resonance) metabolomics approach to determine relative plasma levels of metabolites. We observed a decrease in total protein level in blood; however, despite accelerated skeletal muscle catabolism characteristic for ALS patients, we did not detect changes in plasma levels of essential amino acids. When focused on alterations in energy metabolism within muscle, compromised creatine uptake was accompanied by decreased plasma creatinine. We did not observe changes in plasma levels of BCAAs (branched chain amino acids; leucine, isoleucine, valine); however, the observed decrease in plasma levels of all three BCKAs (branched chain alpha-keto acids derived from BCAAs) suggests enhanced utilization of BCKAs as energy substrate. Glutamine, found to be increased in blood plasma in ALS patients, besides serving for ammonia detoxification, could also be considered a potential TCA (tricarboxylic acid) cycle contributor in times of decreased pyruvate utilization. When analyzing the data by using a cross-validated Random Forest algorithm, it finished with an AUC of 0.92, oob error of 8%, and an MCC (Matthew\'s correlation coefficient) of 0.84 when relative plasma levels of metabolites were used as input variables. Although the discriminatory power of the system used was promising, additional features are needed to create a robust discriminatory model.

Chili peppers (Capsicum annuum L.) are economically valuable crops belonging to the Solanaceae family and are popular worldwide because of their unique spiciness and flavor. In this study, differences in the metabolomes of landrace (Subicho) and disease-resistant pepper cultivars (Bulkala and Kaltanbaksa) widely grown in Korea are investigated using a 1H NMR-based metabolomics approach. Specific metabolites were abundant in the pericarp (GABA, fructose, and glutamine) and placenta (glucose, asparagine, arginine, and capsaicin), highlighting the distinct physiological and functional roles of these components. Both the pericarp and placenta of disease-resistant pepper cultivars contained higher levels of sucrose and hexoses and lower levels of alanine, proline, and threonine than the traditional landrace cultivar. These metabolic differences are linked to enhanced stress tolerance and the activation of defense pathways, imbuing these cultivars with improved resistance characteristics. The present study provides fundamental insights into the metabolic basis of disease resistance in chili peppers, emphasizing the importance of multi-resistant varieties to ensure sustainable agriculture and food security. These resistant varieties ensure a stable supply of high-quality peppers, contributing to safer and more sustainable food production systems.

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BACKGROUND: Acute flaccid paralysis (AFP) is a complex clinical syndrome with various aetiologies. If untreated, AFP may lead to death due to failure of respiratory muscles. Tick paralysis, which is a noninfectious neurologic syndrome of AFP, occurs following tick attachment, engorgement, and injection of tick saliva toxins. There is no specific diagnostic test for tick paralysis, and mortality increases as definitive diagnosis is delayed. Although metabolomic investigation of tick saliva was conducted, there is a lack of research on metabolomic evaluation of hosts affected by tick paralysis.
OBJECTIVE: Thus, the aim of this study is to investigate metabolomic changes in serum samples of dogs with tick paralysis due to Rhipicephalus sanguineus using NMR-based metabolomics and to identify potential diagnostic/prognostic markers.
METHODS: Forty dogs infested with R. sanguineus, with clinical findings compatible with AFP and with a confirmed tick paralysis diagnosis ex juvantibus, constituted the Paralysis Group. Ten healthy dogs, which were admitted either for vaccination and/or check-up purposes, constituted the Control Group. After the confirmation tick paralysis, medical history, vaccination and nutritional status, body surface area and estimated tick numbers of all the dogs were noted. Physical examination included body temperature, heart and respiratory rate, capillary refill time evaluation and Modified Glasgow Coma Scale calculation. Serum samples were extracted from venous blood samples of all the dogs and were prepared for NMR analysis, and NMR-based metabolomics identification and quantification were performed.
RESULTS: NMR-based serum metabolomics of the present study revealed distinct up/down-regulated expressions, presenting a promising avenue. Moreover, it was observed that energy metabolism and especially liver functions were impaired in dogs with tick paralysis, and not only the respiratory system but also the kidneys were affected.
CONCLUSIONS: It was concluded that the present approach may help to better understand the pathological mechanisms developing in cases of AFP due to tick paralysis.

Flowers are gaining considerable interest among consumers as ingredients in food, beverages, cosmetics, and natural health products. The supply chain trades in multiple forms of botanicals, including fresh whole flowers, which are easier to identify than dried flowers or flowers processed as powdered or liquid extracts. There is a gap in the scientific methods available for the verification of flower species ingredients traded in the supply chains of multiple markets. The objective of this paper is to develop methods for flower species ingredient verification using two orthogonal methods. More specifically, the objectives of this study employed both (1) DNA-based molecular diagnostic methods and (2) NMR metabolite fingerprint methods in the identification of 23 common flower species ingredients. NMR data analysis reveals considerable information on the variation in metabolites present in different flower species, including color variants within species. This study provides a comprehensive comparison of two orthogonal methods for verifying flower species ingredient supply chains to ensure the highest quality products. By thoroughly analyzing the benefits and limitations of each approach, this research offers valuable insights to support quality assurance and improve consumer confidence.

Timber plantations across the world are suffering from the effects of increasingly frequent wildfires, which potentially degrade the wood of affected trees, depending on the exposure temperature and time. However, it is rather complicated to determine the exact temperature of the fire, or the temperature to which the wood was exposed. This study aimed to determine the exposure temperature of wood retrospectively through solid-state NMR analysis. Models were developed from softwood and hardwood samples exposed to defined temperatures, which successfully linked the NMR signal to the exposure temperature. Various fit equations were developed to link the half-width or peak area of the NMR signal to the exposure temperatures. Hard- and softwoods displayed noticeable differences: a linear function best described the half-width in the higher temperature region for Pine and Eucalyptus, whereas a parabolic function for the peak area of Eucalyptus yielded the best correlation to the entire temperature range. This non-destructive and direct method offers a valuable evaluation method to determine, if wood in burnt trees is degraded and can be processed. An informed choice can be made on the decision to use, or discard burnt wood.