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The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters { γ i , β i } i = 0 p − 1 . While most prior work has focused on classically optimizing these parameters, we demonstrate that fixed linear ramp schedules, linear ramp QAOA (LR-QAOA), can efficiently approximate optimal solutions across diverse COPs. Simulations with up to N q  = 42 qubits and p  = 400 layers suggest that the success probability scales as P ( x * ) ≈ 2 − η ( p ) N q + C , where η ( p ) decreases with increasing p . For example, in Weighted Maxcut instances, η (10) = 0.22 improves to η (100) = 0.05. Comparisons with classical algorithms, including simulated annealing, Tabu Search, and branch-and-bound, show a scaling advantage for LR-QAOA. We show results of LR-QAOA on multiple QPUs (IonQ, Quantinuum, IBM) with up to N q  = 109 qubits, p  = 100, and circuits requiring 21,200 CNOT gates. Finally, we present a noise model based on two-qubit gate counts that accurately reproduces the experimental behavior of LR-QAOA.

Solving combinatorial optimization problems (COPs) is a promising application of quantum computation, with the quantum approximate optimization algorithm (QAOA) being one of the most studied quantum algorithms for solving them. However, multiple factors make the parameter search of the QAOA a hard optimization problem. In this work, we study transfer learning (TL), a methodology to reuse pre-trained QAOA parameters of one problem instance into different COP instances. This methodology can be used to alleviate the necessity of classical optimization to find good parameters for individual problems. To this end, we select small cases of the traveling salesman problem (TSP), the bin packing problem (BPP), the knapsack problem (KP), the weighted maximum cut (MaxCut) problem, the maximal independent set (MIS) problem, and portfolio optimization (PO), and find optimal β and γ parameters for p layers. We compare how well the parameters found for one problem adapt to the others. Among the different problems, BPP is the one that produces the best transferable parameters, maintaining the probability of finding the optimal solution above a quadratic speedup over random guessing for problem sizes up to 42 qubits and p=10 layers. Using the BPP parameters, we perform experiments on IonQ Harmony and Aria, Rigetti Aspen-M-3, and IBM Brisbane of MIS instances for up to 18 qubits. The results indicate that IonQ Aria yields the best overlap with the ideal probability distribution. Additionally, we show that cross-platform TL is possible using the D-Wave Advantage quantum annealer with the parameters found for BPP. We show an improvement in performance compared to the default protocols for MIS with up to 170 qubits. Our results suggest that there are QAOA parameters that generalize well for different COPs and annealing protocols.

We consider Type IIB compactifications on an isotropic torus T 6 threaded by geometric and non geometric fluxes. For this particular setup we apply supervised machine learning techniques, namely an artificial neural network coupled to a genetic algorithm, in order to obtain more than sixty thousand flux configurations yielding to a scalar potential with at least one critical point. We observe that both stable AdS vacua with large moduli masses and small vacuum energy as well as unstable dS vacua with small tachyonic mass and large energy are absent, in accordance to the refined de Sitter conjecture. Moreover, by considering a hierarchy among fluxes, we observe that perturbative solutions with small values for the vacuum energy and moduli masses are favored, as well as scenarios in which the lightest modulus mass is much smaller than the corresponding AdS vacuum scale. Finally we apply some results on random matrix theory to conclude that the most probable mass spectrum derived from this string setup is that satisfying the Refined de Sitter and AdS scale conjectures.

Background:The etiology of Rheumatoid Arthritis (RA) is not fully understood. Recent studies point to intestinal permeability as an important factor in the establishment and development of RA [1]. Tight junction (TJ) proteins play a major role in intestinal homeostasis, key to the proper functioning of the communication between the internal and external environment that occurs through the intestinal tract [2]. The alteration of this homeostasis has been related to RA. However, the data regarding the underlying mechanisms of the intestinal permeability-tight junction proteins-RA axis are lacking [3].Objectives:This work aimed to quantify the TJ proteins present in feces of both RA patients and healthy controls, analyze the differences, and identify potential biomarkers for diagnosis and severity of RA.Methods:A cross-sectional study including RA patients and sex- and aged-matched healthy controls was performed. RA patients were diagnosed according to the 2010 criteria of the American College of Rheumatology/European League against Rheumatism. During visits to the rheumatologist, feces and other epidemiological, clinical-analytical variables, inflammatory and therapeutic parameters were collected. All subjects gave their informed consent for inclusion before they participated in the study. The quantification of TJ proteins present in feces was carried out by Enzyme-Linked Immuno Sorbent Assay (ELISA), specific commercial kits were used for each protein (Occludin, CSB-EL016263HU, Cusabio; Claudin, CSB-EK005490HU, Cusabio; and Zonulin, CSB-EQ027649HU, Cusabio). The inflammatory variables analyzed were disease activity Score (DAS28), C-reactive protein (CRP), inflammatory cykines (IL-6, IL-1, TNF-α) and oxidized LDL. Statistical analysis was carried out using IBM SPSS Statistics 27 software. TJ proteins values in both groups were compared by Pearson’s χ2 test or t-test, as appropriate. Furthermore, it was calculated the Pearson correlation coefficient between proteins values and RA characteristics. Finally, a multiple linear regression was carried out to identify TJ protein-related factors in RA patients.Results:A total of 164 individuals were included in the study: 82 RA patients and 82 healthy controls. Table 1 shows the main clinical and demographic characteristics of the cohort. 76.8% were women with an average age of 56.3±11.1 years. RA patients present an average DAS28 value of 3.0, average CRP of 3.4 mg/L and 35.4% of them were classified as obese.Figure 1 shows the quantification of the TJ proteins in both groups. Only claudin present significant differences between groups, with lower values in RA patients [RAmean: 19.8(±13.7) pg/mL; Controlsmean: 26.8(±17.3) pg/mL; p: 0.024]. There were no significant differences regarding neither occludin [RAmedian: 10.0 pg/mL (8.5-17.1); Controlsmedian: 9.8 pg/mL (8.1-12.0); p: 0.412] nor zonulin [RAmedian: 3.4 ng/mL (2.2-7.9); Controlsmedian: 4.2 ng/mL (1.9-10.1); p: 0.431].Correlation analysis evidenced a correlation between claudin values and both age (Spearman’s rho: -0.317; p<0.05) and body mass index (Spearman’s rho: 0.326; p<0.05), and between zonulin values and both CRP (Spearman’s rho: 0.326; p<0.05) and TNFα (Spearman’s rho: 0.326; p<0.05). Finally, multivariant analysis showed that claudin and CRP levels are significantly related (β: -0.619; 95CI: -1.222, -0.015; p: 0.045).Conclusion:RA patients present a lower concentration of claudin than healthy controls, which compromise the intestinal homeostasis and would result in an increasing of the intestinal permeability. Furthermore, both claudin and zonulin show correlation with several clinical characteristics of RA. Taken together, our results indicate that TJ proteins are involved in the pathogenesis of the RA and could be used as biomarkers in the context of RA. Future studies are needed to validate the findings.REFERENCES:[1] Blenkinsopp et al. J Am Nutr Assoc, 2024. 43(1):59-76.[2] García MA et al. Cold Spring Harb Perspect Biol, 2018. 10(4):a029181.[3] Hecquet S et al. Semin Arthritis Rheum, 2021. 51(4):712-718.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background:Epigenetic modifications can act as biomarkers and are the result of the interaction between genetic and environmental factors. These DNA alterations have been linked to rheumatoid arthritis (RA).Objectives:Identify new potential epigenetic biomarkers for diagnosis and prognosis in RA patients.Methods:Cross-sectional prospective cohort study, in which 32 patients (16 severe RA, 16 non-severe RA) and 32 healthy controls (discovery cohort) were studied. The severity phenotype was defined by cumulative Socre disease activity (DAS28-ESR) ≥3.2, positive rheumatoid factor (RF) and anti-citrullinated peptide antibodies (ACPA), as well as higher counts of Collinsela aerofaciens (OTU ≥ 0.15). (1,2). Global DNA methylation is processed using Infinium Mmethylation EPIC BeadChip (Illumina, San Diego, CA, USA). Validation of the HM850k array results for selected CpGs was performed by pyrosequencing (PyroMark Q48) in both the discovery cohort and the rest of the initial cohort (validation cohort: 78 patients and 78 controls). Pyrosequencing included information on the CpGs adjacent to the CpGs of the array (nomenclature: number of nucleotides with respect to the position of the CpGs of the arrays-Down-code CpG array). A descriptive analysis and bivariate analysis were performed for statistical comparison between the different groups of subjects, in addition an analysis of the area under the ROC curve (AUC) was carried out to identify the diagnostic potential of the validated CpGs.Results:More than half of the subjects were women (≥75%), with a mean age of 56 years. No significant differences were found in most epidemiological characteristics and comorbidities between the compared groups of both cohorts. However, in the patient group there were more smokers (62% vs. 40%; p=0.015 and 44% vs. 29%, p=0.036). Among patients, subjects with severe RA compared to non-severe subjects had a higher average DAS28-ESR (3.6 ± 0.6 vs. 2.9 ± 0.7 mg/l, p = 0.017 and 3. 6 ±0.9 vs. 2.5 ±0.8 mg/l, p<0.001), and elevated ACPA (68% vs. 31%, p=0.034 and 57% vs. 22%c, p=0.004) in both cohorts. Patients with severe RA had a higher frequency of erosions (81% vs. 37%, p=0.012), and treatment with biological therapy (56% vs. 12%, p=0.009), as well as a higher abundance of Collinsela (median [IQR], 0.3 [0.1-1.7] vs. 0.1 [0.0-0.4] mg/l, p=0.003) in the discovery cohort.Regarding the methylation analysis, of all the differentially methylated CpGs in the HM850k matrix, those CpGs annotated in genes or pseudogenes, with minimal change in the β-value ≥ 0.10 between groups, p value ≤0.01, and that were in differentially methylated regions (p<0.05) for validation by pyrosequencing. Differential changes in methylation levels between the compared groups were identified for the CpGs described in Table 1. These CpGs presented a potential diagnosis according to the AUC ROC (Table 2).Conclusion:The level of DNA methylation at selected CpG sites is different in RA and depending on the severity of the disease. These CpGs could act as potential biomarkers in the diagnosis of RA.REFERENCES:1. Ruiz-Limón P, Mena-Vázquez N, Moreno-Indias I, Manrique-Arija S, Lisbona-Montañez JM, Cano-García L, et al. Collinsella is associated with cumulative inflammatory burden in an established rheumatoid arthritis cohort. Biomed Pharmacother. 2022 Sep;153:113518.2. Mena-Vázquez N, Rojas-Gimenez M, Fuego-Varela C, García-Studer A, Perez-Gómez N, Romero-Barco CM, et al. Safety and Effectiveness of Abatacept in a Prospective Cohort of Patients with Rheumatoid Arthritis-Associated Interstitial Lung Disease. Biomedicines. 2022 Jun;10(7).Acknowledgements:FIS Grant PI18/00824 (Instituto Carlos III, Fondos FEDER). “Ayuda de Garantía Juvenil 2020” of the University of Malaga, Spain (SNGJ5Y6-12). Redes de Investigación Cooperativa Orientadas a Resultados en Salud (RICORS) (RD21/0002/0037).Disclosure of Interests:None declared.

There exists an increasing interest from consumers and scientific community in developing edible-natural-biodegradable coatings to replace commercial wax-based coatings for maintaining postharvest quality of vegetables. In this work, the effectiveness of guar gum coating on various quality characteristics of Roma tomato at 22±2°C over a 20 d storage period was investigated. Tomatoes were covered with a 1.5% guar gum coating plasticized with glycerol at 30% and stored at 22±2°C and 40% RH for 20-d. Tomatoes covered with edible coating significantly enhanced firmness and reduced weight loss, delayed changes on soluble-solids-content, retarded loss of total acidity, and decreased respiration rate compared with uncoated-control fruit. Sensory analysis by trained panelists revealed that the use of the edible coating influenced the acceptability of tomatoes. There were significant differences on the scores given by panelists when comparing the coated and uncoated tomatoes. It was concluded that guar gum affected favorably the physicochemical, microbial, and sensorial quality properties of Roma tomato and therefore could be beneficial in delaying the ripening process at 22±2°C.

Novel biomaterials and optimal processing conditions are fundamental in low-cost packaging material production. Recently, a novel biobased intact bitter cassava derivative was developed using an intrinsic, high-throughput downstream processing methodology (simultaneous release recovery cyanogenesis). Processing of intact bitter cassava can minimise waste and produce low-cost added value biopolymer packaging films. The objective of this study was to (i) develop and characterise intact bitter cassava biobased films and (ii) determine the optimal processing conditions, which define the most desirable film properties. Films were developed following a Box-Behnken design considering cassava (2, 3, 4 % w / v ), glycerol (20, 30, 40 % w / w ) and drying temperature (30, 40, 50 °C) and optimised using multi-response desirability. Processing conditions produced films with highly significant ( p  < 0.05) differences. Developed models predicted impact of processing conditions on film properties. Desirable film properties for food packaging were produced using the optimised processing conditions, 2 % w / v cassava, 40.0 % w / w glycerol and 50 °C drying temperature. These processing conditions produced films with 0.3 %; transparency, 3.4 %; solubility, 21.8 %; water-vapour-permeability, 4.2 gmm/m 2 /day/kPa; glass transition, 56 °C; melting temperature, 212.6 °C; tensile strength, 16.3 MPa; elongation, 133.3 %; elastic modulus, 5.1 MPa and puncture resistance, 57.9 J, which are adequate for packaging applications. Therefore, intact bitter cassava is a viable material to produce packaging films that can be tailored for specific sustainable, low-cost applications.

Several health benefits have been associated to probiotics and prebiotics, most of these are involved in the regulation of the host’s gut microbiome. Their incorporation to diverse food products has been done to develop potential functional foods. In the case of bakery products, their incorporation has been seen to improve several technological parameters such as volume, specific volume, texture along with sensorial parameters such as flavor and aroma. Scientific literature in this topic has been divided in three main research branches: nutrition, physical quality and sensory analyzes, however, studies rarely cover all of them. Due to the harsh thermal stress during baking, sourdough technology along with microencapsulation of probiotics, has been studied as an alternative to enhance its nutritional values and increase cell viability, though in few occasions. The potential functional baked goods have maintained acceptable physical characteristics and sensorial acceptability, while in some cases an improvement is seen due to the effect of probiotics and prebiotics. The results obtained from several studies done, have shown the viability of developing functional bakery products by applying prebiotics or probiotics. This could be used as an encouragement for more research to be done in this topic.

Using waste such as prickly pear ( Opuntia lasiacantha P.) peel to obtain value-added compounds such as pectin is possible with emerging technologies. This study used the Taguchi optimization model to maximize the extraction of chelating-soluble pectin (CSP) through an ohmic heating (OH) process. The maximum pectin yield obtained was 3.32% under the best processing conditions, and the galacturonic acid content was 726.26 mg/g, as well as a range of pectin with a low degree of esterification. The electric field and sodium hexametaphosphate concentration significantly affected the quality and yield of CSP. Additionally, the flow of electrical current during pectin extraction was governed by the concentration of added sodium hexametaphosphate (SHMP), which acted as an electrolyte and chelating agent for CSP. The use of OH in the recovery of CSP from red prickly pear with potential application and care of the proportions of GalA and %yield is presented as an effective option for the recovery of value-added additives from agro-industrial waste.

Solving combinatorial optimization problems (COPs) is a promising application of quantum computation, with the quantum approximate optimization algorithm (QAOA) being one of the most studied quantum algorithms for solving them. However, multiple factors make the parameter search of the QAOA a hard optimization problem. In this work, we study transfer learning (TL), a methodology to reuse pre-trained QAOA parameters of one problem instance into different COP instances. This methodology can be used to alleviate the necessity of classical optimization to find good parameters for individual problems. To this end, we select small cases of the traveling salesman problem (TSP), the bin packing problem (BPP), the knapsack problem (KP), the weighted maximum cut (MaxCut) problem, the maximal independent set (MIS) problem, and portfolio optimization (PO), and find optimal β and γ parameters for p layers. We compare how well the parameters found for one problem adapt to the others. Among the different problems, BPP is the one that produces the best transferable parameters, maintaining the probability of finding the optimal solution above a quadratic speedup over random guessing for problem sizes up to 42 qubits and p = 10 layers. Using the BPP parameters, we perform experiments on IonQ Harmony and Aria, Rigetti Aspen-M-3, and IBM Brisbane of MIS instances for up to 18 qubits. The results indicate that IonQ Aria yields the best overlap with the ideal probability distribution. Additionally, we show that cross-platform TL is possible using the D-Wave Advantage quantum annealer with the parameters found for BPP. We show an improvement in performance compared to the default protocols for MIS with up to 170 qubits. Our results suggest that there are QAOA parameters that generalize well for different COPs and annealing protocols.