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Neuromorphic computing requires the development of solid-state units able to electrically mimic the behavior of biological neurons and synapses. This can be achieved by developing memristive systems based on ferroelectric oxides. In this work we fabricate and characterize high quality epitaxial BaTiO3-based memristors integrated with silicon. After proving the ferroelectric character of BaTiO3 we tested the memristive response of LaNiO3/BaTiO3/Pt microstructures and found a complex behavior which includes the co-existence of volatile and non-volatile effects, arising from the modulation of the BaTiO3/Pt Schottky interface by the direction of the polarization coupled to oxygen vacancy electromigration to/from the interface. This produces remanent resistance loops with tunable ON/OFF ratio and asymmetric resistance relaxations. These properties might be harnessed for the development of neuromorphic hardware compatible with existing silicon-based technology.

A quantum paraelectric SrTiO3 is a material situated in close proximity to a quantum critical point (QCP) of ferroelectric transition in which the critical temperature to the ferroelectric state is suppressed down to 0 K. However, the understanding of the behavior of the phase transition in the vicinity of this point remains challenging. Using the concentration x of Pb in solid solution Sr1−xPbxTiO3 (PSTx) as a tuning parameter and applying the combination of Raman and dielectric spectroscopy methods, we approach the QCP in PSTx and study the interplay of classical and quantum phenomena in the region of criticality. We obtain the critical temperature of PSTx and the evolution of the temperature-dependent dynamical properties of the system as a function of x to reveal the mechanism of the transition. We show that the ferroelectric transition occurs gradually through the emergence of the polar nanoregions inside the non-polar tetragonal phase with their further expansion on cooling. We also study the ferroelastic cubic-to-tetragonal structural transition, occurring at higher temperatures, and show that its properties are almost concentration-independent and not affected by the quantum criticality.

Abstract In this work, we study timelike and lightlike geodesics in Kalb–Ramond (KR) gravity around a black hole with the goal of constraining the Lorentz symmetry-breaking parameter l. The analysis involves studying the precession of the S2 star periastron orbiting Sgr A* and geodesic precession around the Earth. The ratio of precession frequencies for General Relativity (GR) and KR gravity is computed, with Event Horizon Telescope (EHT) results providing a parameter range for the spontaneous symmetry-breaking of $$-0.185022 \le l \le 0.060938$$ - 0.185022 ≤ l ≤ 0.060938 . Utilizing the geodesic precession frequency from the Gravity Probe B (GP-B), the l parameter is further constrained to $$-6.30714 \times 10^{-12} \le l \le 3.90708 \times 10^{-12}$$ - 6.30714 × 10 - 12 ≤ l ≤ 3.90708 × 10 - 12 , which is consistent with the Schwarzschild limits. Moreover, for timelike geodesics, the innermost circular orbit (ICO) and innermost stable circular orbit (ISCO) are determined and analyzed to illustrate the impact of the symmetry breaking term. Zoom-whirl obstructions are compared with the Schwarzschild solution. Lower and upper limits of the photon sphere for lightlike geodesics are established to demonstrate the influence of KR gravity on the photon sphere. Additionally, the shadow radius is determined for two observers, one situated at a finite distance from the KR black hole, and the other located at an infinite distance, to constrain the symmetry-breaking parameter l, with comparisons made to EHT results. The bounds for l derived from constraints on the photon sphere radius for lightlike geodesics yield $$-0.0700225 \le l \le 0.189785$$ - 0.0700225 ≤ l ≤ 0.189785 using EHT data. The findings of this paper align with experimental results in the $$l \rightarrow 0$$ l → 0 limit.

Abstract Recently, J. Harada proposed a theory relating gravity to the Cotton tensor, dubbed as “Cotton gravity” (CG). This is an extension of General Relativity such that every solution of the latter turns out to be a solution of the former (but the converse is not true) and, furthermore, it is possible to derive the cosmological constant as an integration constant within it. In this work we investigate CG by coupling it to both non-linear electrodynamics (NLED) and scalar fields. We study static and spherically symmetric solutions implementing a bouncing behaviour in the radial function so as to avoid the development of singularities, inspired by the Simpson–Visser black bounce and the Bardeen model, both interpreted as magnetic monopoles. We identify the NLED Lagrangian density and the scalar field potential generating such solutions, and investigate the corresponding gravitational configurations in terms of horizons, behaviour of the metric functions, and regularity of the Kretchsman curvature scalar. Our analysis extends the class of non-singular geometries found in the literature and paves the ground for further analysis of black holes in CG.

Abstract Pea (Pisum sativum L.) is an important temperate legume crop providing plant‐based proteins for food and feed worldwide. Pea yield can be limited by several biotic stresses, among which rust represents a major limiting factor in many temperate and subtropical regions. Some efforts have been made to assess the natural variation in pea resistance to rust, but its efficient exploitation in breeding is limited since the resistance loci identified so far are scarce and their responsible gene(s) unknown. To overcome this knowledge gap, a comprehensive genome‐wide association study (GWAS) has been performed on pea rust, caused by Uromyces pisi, to uncover genetic loci associated with resistance. Utilizing a diverse collection of 320 pea accessions, we evaluated phenotypic responses to two rust isolates using both traditional methods and advanced image‐based phenotyping. We detected 95 significant trait‐marker associations using a set of 26,045 Diversity Arrays Technology‐sequencing polymorphic markers. Our in silico analysis identified 62 candidate genes putatively involved in rust resistance, grouped into different functional categories such as gene expression regulation, vesicle trafficking, cell wall biosynthesis, and hormonal signaling. This research highlights the potential of GWAS to identify molecular markers associated with resistance and candidate genes against pea rust, offering new targets for precision breeding. By integrating our findings into current breeding programs, we can facilitate the development of pea varieties with improved resistance to rust, contributing to sustainable agricultural practices and food security. This study sets the stage for future functional genomic analyses and the application of genomic selection approaches to enhance disease resistance in peas.

Abstract Weeds pose a major constraint in lentil cultivation, leading to decrease farmers’ revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.

ABSTRACT Dry pea (Pisum sativum L.) is a highly nutritious cool season food legume or pulse crop within the Fabaceae family that features high levels of protein (20%–25%), prebiotic carbohydrates, and a range of minerals and vitamins. Dry pea is cultivated globally in temperate climates and consumed as a whole food, snack, or protein powder. Dry pea is featured in plant‐based meat items such as the “beyond” branded plant‐based meats. Dry pea is an excellent candidate for plant‐based protein alternatives due to the high protein and low‐fat concentrations present in the mature seed, but improvements are still needed for more widespread use. Breeding efforts are ongoing to further improve dry pea proteins' quality, quantity, and digestibility through biofortification. Global dry pea germplasm contains a wide array of accessions that are vital for dry pea breeding efforts focused on developing cultivars enriched with the most bioavailable forms of plant‐based proteins. The objective of this review is to summarize prior research exploring the factors that contribute to the nutritional value of the dry pea—especially protein quality and quantity.

Abstract Background Stemphylium blight incited by Stemphylium botryosum poses a significant threat to lentil crops worldwide, inducing severe defoliation and causing substantial yield losses in susceptible varieties under favorable conditions. While some moderate levels of resistance have been identified within lentil germplasm, a low number of resistant cultivars are available to farmers. Adding to the common constraints of resistance breeding, a notable challenge is generating a sufficient number of spores for large-scale screenings, which are essential for pinpointing additional sources of resistance for integration into breeding programs. Therefore, there is a pressing need to improve existing screening methods and tailor them for large-scale material selection. In pursuit of this objective, a protocol for the efficient production of fungal material has been adapted. Results Optimization of fungal material production was successfully achieved by comparing the use of fungal mycelia and spores. Spore production was found to be optimal when produced on solid V8-PDA(hi) medium, while liquid Richard’s medium was identified as superior for mycelium yield. Furthermore, a refined screening method was developed by evaluating the resistance of six lentil accessions to stemphylium blight. This assessment included the use of either fungal mycelia (at densities ranging from 1 to 5 g L− 1) or spores (with densities ranging from 5 × 104 to 2 × 105 conidia mL− 1) under three different relative humidity levels (from 50 to 100%). Both humidity levels and inoculum dose significantly influenced the final disease rating (DR) and the relative Area Under the Disease Progress Curve (rAUDPC). Differences among genotypes in final symptom severity (DR) became more pronounced after inoculation with inoculum densities of 5 g L− 1 of mycelium or of 105 and 2 × 105 conidia mL− 1 of spore under 100% relative humidity. Given the challenges associated with the large-scale production of S. botryosum spores, inoculations with 5 g L− 1 of mycelium is highly recommended as a practical alternative for conducting mass-scale screenings. Conclusions The findings from this study underscore the critical importance of maintaining high level of humidity during inoculation and disease progression development for accurately assessing resistance to stemphylium blight. The optimization of mycelial production for suspension inoculation emerges as a more reliable and efficient approach for conducting large-scale screening to assess germplasm resistance against stemphylium blight in lentil crops.

Genomic selection (GS) has become an indispensable tool in modern plant breeding, particularly for complex traits. This study aimed to assess the efficacy of GS in predicting rust (Uromyces pisi) resistance in pea (Pisum sativum), using a panel of 320 pea accessions and a set of 26,045 Silico-Diversity Arrays Technology (Silico-DArT) markers. We compared the prediction abilities of different GS models and explored the impact of incorporating marker × environment (M×E) interaction as a covariate in the GBLUP (genomic best linear unbiased prediction) model. The analysis included phenotyping data from both field and controlled conditions. We assessed the predictive accuracies of different cross-validation strategies and compared the efficiency of using single traits versus a multi-trait index, based on factor analysis and ideotype-design (FAI-BLUP), which combines traits from controlled conditions. The GBLUP model, particularly when modified to include M×E interactions, consistently outperformed other models, demonstrating its suitability for traits affected by complex genotype-environment interactions (GEI). The best predictive ability (0.635) was achieved using the FAI-BLUP approach within the Bayesian Lasso (BL) model. The inclusion of M×E interactions significantly enhanced prediction accuracy across diverse environments in GBLUP models, although it did not markedly improve predictions for non-phenotyped lines. These findings underscore the variability of predictive abilities due to GEI and the effectiveness of multi-trait approaches in addressing complex traits. Overall, our study illustrates the potential of GS, especially when employing a multi-trait index like FAI-BLUP and accounting for M×E interactions, in pea breeding programs focused on rust resistance.

Although the transition toward a more sustainable agricultural system is sparking the interest of scientists and farmers around the globe, breeding programs are still focusing on optimizing cultivars intended for the monoculture system, and most cultivars available on the market are not suitable for intercropping. The incorporation of versatile cool-season food legumes (CSFLs) in the intercropping system is a promising way toward more diversified and sustainable cropping systems. However, as the selection of good-performing cultivars under sole cropping does not always lead to a good performance in intercropping, the development of an alternative breeding scheme for intercropping is now a necessity. The case study of faba bean–wheat intercropping was used to select for traits associated with better performance of faba bean, resulting in identifying the combined grain yield, 100-seed weight, number of pods per plant, and canopy height as key traits for faba bean–wheat intercropping suitability. Incorporating these traits in the breeding programs would be the cornerstone of the prospective transition.

Abstract Common bean (Phaseolus vulgaris) is one of the legume crops most consumed worldwide and bean rust is one of the most severe foliar biotrophic fungal diseases impacting its production. In this work, we searched for new sources of rust resistance (Uromyces appendiculatus) in a representative collection of the Portuguese germplasm, known to have accessions with an admixed genetic background between Mesoamerican and Andean gene pools. We identified six accessions with incomplete hypersensitive resistance and 20 partially resistant accessions of Andean, Mesoamerican, and admixed origin. We detected 11 disease severity-associated single-nucleotide polymorphisms (SNPs) using a genome-wide association approach. Six of the associations were related to partial (incomplete non-hypersensitive) resistance and five to incomplete hypersensitive resistance, and the proportion of variance explained by each association varied from 4.7 to 25.2%. Bean rust severity values ranged from 0.2 to 49.1% and all the infection types were identified, reflecting the diversity of resistance mechanisms deployed by the Portuguese germplasm. The associations with U. appendiculatus partial resistance were located in chromosome Pv08, and with incomplete hypersensitive resistance in chromosomes Pv06, Pv07, and Pv08, suggesting an oligogenic inheritance of both types of resistance. A resolution to the gene level was achieved for eight of the associations. The candidate genes proposed included several resistance-associated enzymes, namely β-amylase 7, acyl-CoA thioesterase, protein kinase, and aspartyl protease. Both SNPs and candidate genes here identified constitute promising genomics targets to develop functional molecular tools to support bean rust resistance precision breeding.

Aphanomyces root rot (ARR), caused by Aphanomyces euteiches, is one of the most devastating diseases that affect the production of peas. Several control strategies such as crop rotation, biocontrol, and fungicides have been proposed, but none provides a complete solution. Therefore, the deployment of resistant cultivars is fundamental. ARR resistance breeding is hampered by the moderate levels of resistance identified so far. The available screening protocols require post-inoculation root assessment, which is destructive, time-consuming, and tedious. In an attempt to address these limitations, we developed a non-destructive screening protocol based on foliar symptoms and used it to identify new sources of resistance in a Pisum spp. germplasm collection. Accessions were root inoculated separately with two A. euteiches isolates, and leaf symptoms were assessed at 5, 10, 14, 17, and 20 days after inoculation (DAI). Although the majority of accessions exhibited high levels of susceptibility, thirty of them exhibited moderate resistance. These thirty accessions were selected for a second experiment, in which they were inoculated with both A. euteiches isolates at two inoculum doses. The objective of this second trial was to confirm the resistance of these accessions by evaluating root and biomass loss, as well as foliar symptoms, and to compare root and foliar evaluations. As a result, a high correlation (R2 = 0.75) between foliar and root evaluations was observed, validating the foliar evaluation method. Notably, accessions from P.s. subsp. humile exhibited the lowest symptomatology across all evaluation methods, representing valuable genetic resources for breeding programs aimed at developing pea varieties resistant to ARR.

Abstract We study the completeness of light trajectories in certain spherically symmetric regular geometries found in Palatini theories of gravity threaded by non-linear (electromagnetic) fields, which makes their propagation to happen along geodesics of an effective metric. Two types of geodesic restoration mechanisms are employed: by pushing the focal point to infinite affine distance, thus unreachable in finite time by any sets of geodesics, or by the presence of a defocusing surface associated to the development of a wormhole throat. We discuss several examples of such geometries to conclude the completeness of all such effective paths. Our results are of interest both for the finding of singularity-free solutions and for the analysis of their optical appearances e.g. in shadow observations.

Abstract Background Rust is a damaging disease affecting vital crops, including pea, and identifying highly resistant genotypes remains a challenge. Accurate measurement of infection levels in large germplasm collections is crucial for finding new resistance sources. Current evaluation methods rely on visual estimation of disease severity and infection type under field or controlled conditions. While they identify some resistance sources, they are error-prone and time-consuming. An image analysis system proves useful, providing an easy-to-use and affordable way to quickly count and measure rust-induced pustules on pea samples. This study aimed to develop an automated image analysis pipeline for accurately calculating rust disease progression parameters under controlled conditions, ensuring reliable data collection. Results A highly efficient and automatic image-based method for assessing rust disease in pea leaves was developed using R. The method’s optimization and validation involved testing different segmentation indices and image resolutions on 600 pea leaflets with rust symptoms. The approach allows automatic estimation of parameters like pustule number, pustule size, leaf area, and percentage of pustule coverage. It reconstructs time series data for each leaf and integrates daily estimates into disease progression parameters, including latency period and area under the disease progression curve. Significant variation in disease responses was observed between genotypes using both visual ratings and image-based analysis. Among assessed segmentation indices, the Normalized Green Red Difference Index (NGRDI) proved fastest, analysing 600 leaflets at 60% resolution in 62 s with parallel processing. Lin’s concordance correlation coefficient between image-based and visual pustule counting showed over 0.98 accuracy at full resolution. While lower resolution slightly reduced accuracy, differences were statistically insignificant for most disease progression parameters, significantly reducing processing time and storage space. NGRDI was optimal at all time points, providing highly accurate estimations with minimal accumulated error. Conclusions A new image-based method for monitoring pea rust disease in detached leaves, using RGB spectral indices segmentation and pixel value thresholding, improves resolution and precision. It rapidly analyses hundreds of images with accuracy comparable to visual methods and higher than other image-based approaches. This method evaluates rust progression in pea, eliminating rater-induced errors from traditional methods. Implementing this approach to evaluate large germplasm collections will improve our understanding of plant-pathogen interactions and aid future breeding for novel pea cultivars with increased rust resistance.

We study the space-time geometry generated by coupling a free scalar field with a noncanonical kinetic term to general relativity in (2+1) dimensions. After identifying a family of scalar Lagrangians that yield exact analytical solutions in static and circularly symmetric scenarios, we classify the various types of solutions and focus on a branch that yields asymptotically flat geometries. We show that the solutions within such a branch can be divided in two types, namely naked singularities and nonsingular objects without a center. In the latter, the energy density is localized around a maximum and vanishes only at infinity and at an inner boundary. This boundary has vanishing curvatures and cannot be reached by any time-like or null geodesic in finite affine time. This allows us to consistently interpret such solutions as nonsingular, lump-like, static compact scalar objects whose eventual extension to the (3+1)-dimensional context could provide structures of astrophysical interest.

Faba bean is an important legume crop worldwide, which is grown both for food and feed. As for many legume crops, postemergence weed control is difficult. The aim of this work was to assess the potential of intercropping in weed management by assessing the effect of mixing faba bean with different crops (wheat, barley, and pea) on weeds in the South of Spain. Four field trials were conducted over four consecutive seasons, and the results found that the addition of alternate intercropping of faba bean and barley achieved high levels of weed control, both for coverage and biomass (92.7% and 76.6%, respectively). Intercropping with wheat did not reduce weed coverage but did decrease weed biomass by 46.1% as compared with the faba bean monocrop. Intercropping with pea did not provide significant reductions in weed coverage or weed biomass. The diversity of the weed community was not altered by the different crop combinations tested. Additional experiments under controlled conditions were carried out to determine the possible role of barley allelopathy in weed suppression. A strong allelopathic effect entailing a reduction in the number of plants and biomass was detected for four weeds including Sinapis arvensis, Polypogon monspeliensis, Matricaria camomilla, and Medicago truncatula. It can be concluded that intercropping faba bean with barley is an excellent strategy for weed control in Southern Spain.

Rusts of the genus Puccinia are wheat pathogens. Stem (black; Sr), leaf (brown; Lr), and stripe (yellow; Yr) rust, caused by Puccinia graminis f. sp. tritici (Pgt), Puccinia triticina (Pt), and Puccinia striiformis f. sp. tritici (Pst), can occur singularly or in mixed infections and pose a threat to wheat production globally in terms of the wide dispersal of their urediniospores. The development of durable resistant cultivars is the most sustainable method for controlling them. Many resistance genes have been identified, characterized, genetically mapped, and cloned; several quantitative trait loci (QTLs) for resistance have also been described. However, few studies have considered resistance to all three rust pathogens in a given germplasm. A genome-wide association study (GWAS) was carried out to identify loci associated with resistance to the three rusts in a collection of 230 inbred lines of tetraploid wheat (128 of which were Triticum turgidum ssp. durum) genotyped with SNPs. The wheat panel was phenotyped in the field and subjected to growth chamber experiments across different countries (USA, Mexico, Morocco, Italy, and Spain); then, a mixed linear model (MLM) GWAS was performed. In total, 9, 34, and 5 QTLs were identified in the A and B genomes for resistance to Pgt, Pt, and Pst, respectively, at both the seedling and adult plant stages. Only one QTL on chromosome 4A was found to be effective against all three rusts at the seedling stage. Six QTLs conferring resistance to two rust species at the adult plant stage were mapped: three on chromosome 1B and one each on 5B, 7A, and 7B. Fifteen QTLs conferring seedling resistance to two rusts were mapped: five on chromosome 2B, three on 7B, two each on 5B and 6A, and one each on 1B, 2A, and 7A. Most of the QTLs identified were specific for a single rust species or race of a species. Candidate genes were identified within the confidence intervals of a QTL conferring resistance against at least two rust species by using the annotations of the durum (cv. ‘Svevo’) and wild emmer wheat (‘Zavitan’) reference genomes. The 22 identified loci conferring resistance to two or three rust species may be useful for breeding new and potentially durable resistant wheat cultivars.

Faba bean (Vicia faba) is a temperate grain legume of major importance for food and feed. Powdery mildews are an important group of diseases in many crops, although in faba bean, it is still considered to be of only minor and local relevance. Here, we report the occurrence of powdery mildew in southern Spain, which was identified through ITS sequencing as Erysiphe trifolii. Resistance screenings allowed the identification of a wide range of responses to the disease, with accessions BPL-710 and ILB-4708 outstanding due to their high levels of resistance. Histological studies showed that the mechanisms of resistance may involve the inhibition of germination and impairment of fungal development, as shown by a limited number of primary and secondary hyphae compared to those of the susceptible accessions. This work permitted a better understanding of the interaction of faba bean and powdery mildew, laying the ground for breeding programs for resistance if needed in the future.

Abstract Peyronellaea pinodes is a devastating pathogen of pea crop. Quantitative trait loci (QTL) associated with resistance have been identified, as well as genes differentially expressed between resistant and susceptible pea lines. The key question is which of these many genes located into these QTLs, or differentially expressed, are the key genes that distinguish resistant from susceptible plants and could be used as markers. To identify these key genes, in the present study we applied MACE (Massive Analysis of cDNA Ends) -Seq to a whole Recombinant Inbred Line population segregating for resistance to this disease and their parental lines and identified those genes which expression was more correlated with the level of resistance. We also compared gene expression profiles between the most resistant and the most susceptible families of the RIL population. A total of 6780 transcripts were differentially expressed between the parental lines after inoculation. Of them, 803 showed the same expression pattern in the bulks formed by the most resistant and most susceptible RIL families. These genes, showing a consistent expression pattern, could be used as expression markers to distinguish resistant from susceptible plants. The analysis of these genes also discovered the crucial mechanisms acting against P. pinodes.

Abstract We study three aspects of the early-evolutionary phases in low-mass stars within Eddington-inspired Born–Infeld (EiBI) gravity, a viable extension of General Relativity. These aspects are concerned with the Hayashi tracks (i.e. the effective temperature-luminosity relation); the minimum mass required to belong to the main sequence; and the maximum mass allowed for a fully convective star within the main sequence. Using analytical models accounting for the most relevant physics of these processes, we find in all cases a dependence of these quantities not only on the theory’s parameter, but also on the star’s central density, a feature previously found in Palatini f(R) gravity. Using this, we investigate the evolution of these quantities with the (sign of the) EiBI parameter, finding a shift in the Hayashi tracks in opposite directions in the positive/negative branches of it, and an increase (decrease) for positive (negative) parameter in the two masses above. We use these results to elaborate on the chances to seek for traces of new physics in low-mass stars within this theory, and the limitations and difficulties faced by this approach.

Abstract Neoadjuvant chemotherapy (NAT) in breast cancer (BC) has been used to reduce tumor burden prior to surgery. However, the impact on prognosis depends on the establishment of Pathological Complete Response (pCR), which is influenced by tumor-infiltrating lymphocyte levels and the activation of the antitumor immune response. Nonetheless, NAT can affect immune infiltration and the quality of the response. Here, we showed that NAT induces dynamic changes in the tumor microenvironment (TME). After NAT, an increase of regulatory T cells and a decrease of CD8+ T cells was found in tumor, correlated with the presence of metastatic cells in lymph nodes. In addition, an increase of polymorphonuclear myeloid-derived suppressor like cells was found in luminal patients post-NAT. pCR patients showed a balance between the immune populations, while non-pCR patients presented an inverse relationship in the frequency of CD68+ versus CD3+, CD8+, and CD20+ cells. Moreover, activated T cells were found in peripheral blood, as well as an increase in T cell clonality with a lower diversity post-NAT. Overall, these results shown that NAT induces an activation of immune response, however, a balance in the TME seems to be related to a better antigenic presentation and therefore a better response to treatment.