Quantum ratchet with Lindblad rate equations.

A quantum random-walk model is established on a one-dimensional periodic lattice that fluctuates between two possible states. This model is defined by Lindblad rate equations that incorporate the transition rates between the two lattice states. Leveraging the system's symmetries, the particle velocity can be described using a finite set of equations, even though the state space is of infinite dimension. These equations yield an analytical expression for the velocity in the long-time limit, which is employed to analyze the characteristics of directed motion. Notably, the velocity can exhibit multiple inversions, and to achieve directed motion, distinct, nonzero transition rates between lattice states are required.

Growth conditions trigger genotype-specific metabolic responses that affect the nutritional quality of kale cultivars.

Kales (Brassica oleracea convar acephala) are fast-growing, nutritious leafy vegetables ideal for year-round indoor farming. However, selection of best cultivars for growth under artificial lighting necessitates a deeper understanding of leaf metabolism in different kale types. Here we examined a curly leaved cultivar Half Tall and a lacinato type cultivar Black Magic under moderate growth light (130 µmol photons m-1s-1/22°C) and high light (800 µmol photons m-1s-1/26°C) conditions. These conditions induced genotype-dependent differences in nutritionally important metabolites, especially anthocyanins and glucosinolates (GSLs), in the kale cultivars. In the pale green Half Tall, growth under high light conditions did not induce changes in either pigmentation or total GSL content. In contrast, the purple pigmentation of Black Magic intensified due to increased anthocyanin accumulation. Black Magic showed reduced amounts of indole GSLs and increased amounts of aliphatic GSLs under high light conditions, with notable cultivar-specific adjustments in individual GSL species. Correlation analysis of metabolite profiles suggested cultivar-specific metabolic interplay between serine biosynthesis and the production of indole GSLs. RNA sequencing identified candidate genes encoding metabolic enzymes and regulatory components behind anthocyanin and GSL biosynthesis. These findings improve the understanding of leaf metabolism and its effects on the nutritional quality of kale cultivars.

PlantFUNCO: Integrative Functional Genomics Database Reveals Clues into Duplicates Divergence Evolution.

Evolutionary epigenomics and, more generally, evolutionary functional genomics, are emerging fields that study how non-DNA-encoded alterations in gene expression regulation are an important form of plasticity and adaptation. Previous evidence analyzing plants' comparative functional genomics has mostly focused on comparing same assay-matched experiments, missing the power of heterogeneous datasets for conservation inference. To fill this gap, we developed PlantFUN(ctional)CO(nservation) database, which is constituted by several tools and two main resources: interspecies chromatin states and functional genomics conservation scores, presented and analyzed in this work for three well-established plant models (Arabidopsis thaliana, Oryza sativa, and Zea mays). Overall, PlantFUNCO elucidated evolutionary information in terms of cross-species functional agreement. Therefore, providing a new complementary comparative-genomics source for assessing evolutionary studies. To illustrate the potential applications of this database, we replicated two previously published models predicting genetic redundancy in A. thaliana and found that chromatin states are a determinant of paralogs degree of functional divergence. These predictions were validated based on the phenotypes of mitochondrial alternative oxidase knockout mutants under two different stressors. Taking all the above into account, PlantFUNCO aim to leverage data diversity and extrapolate molecular mechanisms findings from different model organisms to determine the extent of functional conservation, thus, deepening our understanding of how plants epigenome and functional noncoding genome have evolved. PlantFUNCO is available at https://rocesv.github.io/PlantFUNCO.

Genomic Landscape of Lynch Syndrome Colorectal Neoplasia Identifies Shared Mutated Neoantigens for Immunoprevention.

BACKGROUND & AIMS: Lynch syndrome (LS) carriers develop mismatch repair-deficient neoplasia with high neoantigen (neoAg) rates. No detailed information on targetable neoAgs from LS precancers exists, which is crucial for vaccine development and immune-interception strategies. We report a focused somatic mutation and frameshift-neoAg landscape of microsatellite loci from colorectal polyps without malignant potential (PWOMP), precancers, and early-stage cancers in LS carriers. METHODS: We generated paired whole-exome and transcriptomic sequencing data from 8 colorectal PWOMP, 41 precancers, 8 advanced precancers, and 12 early-stage cancers of 43 LS carriers. A computational pipeline was developed to predict, rank, and prioritize the top 100 detected mutated neoAgs that were validated in vitro using ELISpot and tetramer assays. RESULTS: Mutation calling revealed >10 mut/Mb in 83% of cancers, 63% of advanced precancers, and 20% of precancers. Cancers displayed an average of 616 MHC-I neoAgs/sample, 294 in advanced precancers, and 107 in precancers. No neoAgs were detected in PWOMP. A total of 65% of our top 100 predicted neoAgs were immunogenic in vitro, and were present in 92% of cancers, 50% of advanced precancers, and 29% of precancers. We observed increased levels of naïve CD8+ and memory CD4+ T cells in mismatch repair-deficient cancers and precancers via transcriptomics analysis. CONCLUSIONS: Shared frameshift-neoAgs are generated within unstable microsatellite loci at initial stages of LS carcinogenesis and can induce T-cell responses, generating opportunities for vaccine development, targeting LS precancers and early-stage cancers.

Quantum reinforcement learning in the presence of thermal dissipation.

A study of the effect of thermal dissipation on quantum reinforcement learning is performed. For this purpose, a nondissipative quantum reinforcement learning protocol is adapted to the presence of thermal dissipation. Analytical calculations as well as numerical simulations are carried out, obtaining evidence that dissipation does not significantly degrade the performance of the quantum reinforcement learning protocol for sufficiently low temperatures, in some cases even being beneficial. Quantum reinforcement learning under realistic experimental conditions of thermal dissipation opens an avenue for the realization of quantum agents to be able to interact with a changing environment, as well as adapt to it, with many plausible applications inside quantum technologies and machine learning.

Dichotomous colorectal cancer behaviour.

Colorectal cancer (CRC) is the third most common malignant tumor and one of the deadliest cancers. At molecular level, CRC is a heterogeneous disease that could be divided in four Consensus Molecular Subtypes. Given the differences in the disease due to its anatomical location (proximal and distal colon), another classification should be considered. Here, we review the current knowledge on CRC dichotomic´s behaviour based on two different entities; right and left-sided tumors, their impact on clinical trial data, microbiota spatial composition and the interaction with the nervous system. We discuss recent advances in understanding how the spatial tumor heterogeneity influences the tumor growth, progression, and responses to current therapies.

Environmental factors regulate soil microbial attributes and their response to drought in rangeland ecosystems.

In ecosystems, soil microbial variables characterization are used to determine soil biological health and the response of soils to environmental stress. Although there are strong associations between plants and soil microorganisms, they may respond asynchronously to environmental factors and severe droughts. We aimed to: I) evaluate the special variation of soil microbiome such as microbial biomass carbon (MBC) and nitrogen (MBN), soil basal respiration (SBR) and microbial indexes in eight rangeland sites located across an aridity gradient (distributed from arid to mesic climates); II) analyze the relative importance of main environmental factors (climate, soils, and plants) and their relationships with microbial variables in the rangelands; and III) assess the effect of drought on microbial and plant variables in field-based manipulative experiments. First, we found significant changes of microbial variables along a precipitation and temperature gradient. The responses of MBC and MBN were strongly dependent on soil pH, soil nitrogen (N), soil organic carbon (SOC), C:N ratio and vegetation cover. In contrast, SBR was influenced by the aridity index (AI), the mean annual precipitation (MAP), the soil pH and vegetation cover. MBC, MBN and SBR were negatively related with soil pH compared to the other factors (C, N, C:N, vegetation cover, MAP and AI) that had a positive relationship. Second, we found a stronger soil microbial variables response to drought in arid sites compared to humid rangelands. Third, the responses of MBC, MBN, and SBR to drought showed positive relationships with vegetation cover and aboveground biomass, but with different regression slopes, this suggest that plant and microbial communities responded differently to drought. The results from this study improve our understanding about the microbial response to drought in different rangelands, and may facilitate the development of predictive models on responses of soil microorganisms in carbon cycle under global change scenarios.

Proteomics research in forest trees: A 2012-2022 update.

This review is a compilation of proteomic studies on forest tree species published in the last decade (2012-2022), mostly focused on the most investigated species, including Eucalyptus, Pinus, and Quercus. Improvements in equipment, platforms, and methods in addition to the increasing availability of genomic data have favored the biological knowledge of these species at the molecular, organismal, and community levels. Integration of proteomics with physiological, biochemical and other large-scale omics in the direction of the Systems Biology, will provide a comprehensive understanding of different biological processes, from growth and development to responses to biotic and abiotic stresses. As main issue we envisage that proteomics in long-living plants will thrive light on the plant responses and resilience to global climate change, contributing to climate mitigation strategies and molecular breeding programs. Proteomics not only will provide a molecular knowledge of the mechanisms of resilience to either biotic or abiotic stresses, but also will allow the identification on key gene products and its interaction. Proteomics research has also a translational character being applied to the characterization of the variability and biodiversity, as well as to wood and non-wood derived products, traceability, allergen and bioactive peptides identification, among others. Even thought, the full potential of proteomics is far from being fully exploited in forest tree research, with PTMs and interactomics being reserved to plant model systems. The most outstanding achievements in forest tree proteomics in the last decade as well as prospects are discussed.

Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass.

Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.

The Integration of Data from Different Long-Read Sequencing Platforms Enhances Proteoform Characterization in Arabidopsis.

The increasing availability of massive omics data requires improving the quality of reference databases and their annotations. The combination of full-length isoform sequencing (Iso-Seq) with short-read transcriptomics and proteomics has been successfully used for increasing proteoform characterization, which is a main ongoing goal in biology. However, the potential of including Oxford Nanopore Technologies Direct RNA Sequencing (ONT-DRS) data has not been explored. In this paper, we analyzed the impact of combining Iso-Seq- and ONT-DRS-derived data on the identification of proteoforms in Arabidopsis MS proteomics data. To this end, we selected a proteomics dataset corresponding to senescent leaves and we performed protein searches using three different protein databases: AtRTD2 and AtRTD3, built from the homonymous transcriptomes, regarded as the most complete and up-to-date available for the species; and a custom hybrid database combining AtRTD3 with publicly available ONT-DRS transcriptomics data generated from Arabidopsis leaves. Our results show that the inclusion and combination of long-read sequencing data from Iso-Seq and ONT-DRS into a proteogenomic workflow enhances proteoform characterization and discovery in bottom-up proteomics studies. This represents a great opportunity to further investigate biological systems at an unprecedented scale, although it brings challenges to current protein searching algorithms.

Targeted Mass Spectrometry Analysis of Protein Phosphorylation by Selected Ion Monitoring Coupled to Parallel Reaction Monitoring (tSIM/PRM).

Recent developments in targeted mass spectrometry-based proteomics have provided new methodological solutions for accurate and quantitative analysis of proteins and their posttranslational control, which has significantly advanced our understanding of stress responses in different plant species. Instrumentation allowing high-resolution, accurate-mass (HR/AM) analysis has provided new acquisition strategies for targeted quantitative proteomic analysis by targeted selected ion monitoring (tSIM) and parallel reaction monitoring (PRM). Here we report a sensitive and accurate method for targeted analysis of protein phosphorylation by tSIM coupled to PRM (tSIM/PRM). The tSIM/PRM method takes advantage of HR/AM mass spectrometers and benefits from the combination of highly sensitive precursor ion quantification by tSIM and highly confident peptide identification by spectral library matching in PRM. The detailed protocol describes tSIM/PRM analysis of Arabidopsis thaliana foliar proteins, from the building of a spectral library to sample preparation, mass spectrometry, and data analysis, and provides a methodological approach for specifying the molecular mechanisms of interest.

Watch-and-Wait policy versus robotic surgery for locally advanced rectal cancer: A cost-effectiveness study (RECCOSTE).

INTRODUCTION: Complete surgical resection for locally advanced rectal cancer is the standard treatment after a clinical complete response following chemoradiotherapy. However, some novel clinical approaches could achieve better functional results, such as Robotic Resection, or avoiding surgical procedure and incrementing surveillance intensity, called Watch-and-Wait policy. We use computational techniques to compare these clinical approaches using quality adjusted life years (QALYs). METHODS: A Markov decision analytic model was used in order to perform a cost-utility analysis, comparing standard resection (SR), Robotic Rectal Resection (RRR) and Watch-and-Wait (WW) strategies, estimating the incremental cost-effectiveness ratio per QALY to be gained from patients reaching a clinical complete response to chemoradiotherapy. Model parameter estimates were informed by previously published studies comparing WW to SR and from our database of RRR versus SR. Lifetime incremental cost-utility ratio was calculated among approaches, and a sensitivity analysis were performed in order to estimate the model uncertainty. A willingness-to-pay of per one additional QALY gained was measured to determine which strategies would be most cost-effective. RESULTS: WW is a dominating option over SR ( -75,486. 75 € and +2.04 QALYs) and RRR ( -75,486. 75 € and +0.41 QALYs). The cost-effectiveness plane shows that WW does not always dominate over RRR or SR. WW saves costs in 99.98% of the simulations when compared with either SR or RRR but only 86.9% and 55.38% (respectively) of these fall within the SR quadrant. WW is only more effective than SR 55% of the time which implies a significant uncertainty due to the high utility value assigned to cCR after chemoradiotherapy in the RRR alternative. CONCLUSION: This study provides data of cost-effectiveness differences among Standard Surgery, Watch-and-Wait and Robotic Resection approaches in clinical complete response in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy, showing a benefit for Watch-and-Wait policy.

GWAS on multiple traits identifies mitochondrial ACONITASE3 as important for acclimation to submergence stress.

Flooding causes severe crop losses in many parts of the world. Genetic variation in flooding tolerance exists in many species; however, there are few examples for the identification of tolerance genes and their underlying function. We conducted a genome-wide association study (GWAS) in 387 Arabidopsis (Arabidopsis thaliana) accessions. Plants were subjected to prolonged submergence followed by desubmergence, and seven traits (score, water content, Fv/Fm, and concentrations of nitrate, chlorophyll, protein, and starch) were quantified to characterize their acclimation responses. These traits showed substantial variation across the range of accessions. A total of 35 highly significant single-nucleotide polymorphisms (SNPs) were identified across the 20 GWA datasets, pointing to 22 candidate genes, with functions in TCA cycle, DNA modification, and cell division. Detailed functional characterization of one candidate gene, ACONITASE3 (ACO3), was performed. Chromatin immunoprecipitation followed by sequencing showed that a single nucleotide polymorphism in the ACO3 promoter co-located with the binding site of the master regulator of retrograde signaling ANAC017, while subcellular localization of an ACO3-YFP fusion protein confirmed a mitochondrial localization during submergence. Analysis of mutant and overexpression lines determined changes in trait parameters that correlated with altered submergence tolerance and were consistent with the GWAS results. Subsequent RNA-seq experiments suggested that impairing ACO3 function increases the sensitivity to submergence by altering ethylene signaling, whereas ACO3 overexpression leads to tolerance by metabolic priming. These results indicate that ACO3 impacts submergence tolerance through integration of carbon and nitrogen metabolism via the mitochondrial TCA cycle and impacts stress signaling during acclimation to stress.

Multi-model projections of tree species performance in Quebec, Canada under future climate change.

Many modelling approaches have been developed to project climate change impacts on forests. By analysing 'comparable' yet distinct variables (e.g. productivity, growth, dominance, biomass, etc.) through different structures, parameterizations and assumptions, models can yield different outcomes to rather similar initial questions. This variability can lead to some confusion for forest managers when developing strategies to adapt forest management to climate change. In this study, we standardized results from seven different models (Habitat suitability, trGam, StandLEAP, Quebec Landscape Dynamics, PICUS, LANDIS-II and LPJ-LMfire) to provide a simple and comprehensive assessment of the uncertainty and consensus in future performance (decline, status quo, improvement) for six tree species in Quebec under two radiative forcing scenarios (RCP 4.5 and RCP 8.5). Despite a large diversity of model types, we found a high level of agreement (73.1%) in projected species' performance across species, regions, scenarios and time periods. Low agreements in model outcomes resulted from small dissensions among models. Model agreement was much higher for cold-tolerant species (up to 99.9%), especially in southernmost forest regions and under RCP 8.5, indicating that these species are especially sensitive to increased climate forcing in the southern part of their distribution range. Lower agreement was found for thermophilous species (sugar maple, yellow birch) in boreal regions under RCP 8.5 mostly as a result of the way the different models are handling natural disturbances (e.g. wildfires) and lags in the response of populations (forest inertia or migration capability) to climate change. Agreement was slightly higher under high anthropogenic climate forcing, suggesting that important thresholds in species-specific performance might be crossed if radiative forcing reach values as high as those projected under RCP 8.5. We expect that strong agreement among models despite their different assumptions, predictors and structure should inspire the development of forest management strategies to be better adapted to climate change.

ACONITASE 3 is part of theANAC017 transcription factor-dependent mitochondrial dysfunction response.

Mitochondria are tightly embedded within metabolic and regulatory networks that optimize plant performance in response to environmental challenges. The best-known mitochondrial retrograde signaling pathway involves stress-induced activation of the transcription factor NAC DOMAIN CONTAINING PROTEIN 17 (ANAC017), which initiates protective responses to stress-induced mitochondrial dysfunction in Arabidopsis (Arabidopsis thaliana). Posttranslational control of the elicited responses, however, remains poorly understood. Previous studies linked protein phosphatase 2A subunit PP2A-B'γ, a key negative regulator of stress responses, with reversible phosphorylation of ACONITASE 3 (ACO3). Here we report on ACO3 and its phosphorylation at Ser91 as key components of stress regulation that are induced by mitochondrial dysfunction. Targeted mass spectrometry-based proteomics revealed that the abundance and phosphorylation of ACO3 increased under stress, which required signaling through ANAC017. Phosphomimetic mutation at ACO3-Ser91 and accumulation of ACO3S91D-YFP promoted the expression of genes related to mitochondrial dysfunction. Furthermore, ACO3 contributed to plant tolerance against ultraviolet B (UV-B) or antimycin A-induced mitochondrial dysfunction. These findings demonstrate that ACO3 is both a target and mediator of mitochondrial dysfunction signaling, and critical for achieving stress tolerance in Arabidopsis leaves.

Hemogram-derived ratios as prognostic markers of ICU admission in COVID-19.

BACKGROUND: The vast impact of COVID-19 call for the identification of clinical parameter that can help predict a torpid evolution. Among these, endothelial injury has been proposed as one of the main pathophysiological mechanisms underlying the disease, promoting a hyperinflammatory and prothrombotic state leading to worse clinical outcomes. Leukocytes and platelets play a key role in inflammation and thrombogenesis, hence the objective of the current study was to study whether neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), the systemic immune-inflammation index (SII) as well as the new parameter neutrophil-to-platelet ratio (NPR), could help identify patients who at risk of admission at Intensive Care Units. METHODS: A retrospective observational study was performed at HM Hospitales including electronic health records from 2245 patients admitted due to COVID-19 from March 1 to June 10, 2020. Patients were divided into two groups, admitted at ICU or not. RESULTS: Patients who were admitted at the ICU had significantly higher values in all hemogram-derived ratios at the moment of hospital admission compared to those who did not need ICU admission. Specifically, we found significant differences in NLR (6.9 [4-11.7] vs 4.1 [2.6-7.6], p <  0.0001), PLR (2 [1.4-3.3] vs 1.9 [1.3-2.9], p = 0.023), NPR (3 [2.1-4.2] vs 2.3 [1.6-3.2], p <  0.0001) and SII (13 [6.5-25.7] vs 9 [4.9-17.5], p <  0.0001) compared to those who did not require ICU admission. After multivariable logistic regression models, NPR was the hemogram-derived ratio with the highest predictive value of ICU admission, (OR 1.11 (95% CI: 0.98-1.22, p = 0.055). CONCLUSIONS: Simple, hemogram-derived ratios obtained from early hemogram at hospital admission, especially the novelty NPR, have shown to be useful predictors of risk of ICU admission in patients hospitalized due to COVID-19.

Spin dynamics under the influence of elliptically rotating fields: Extracting the field topology from time-averaged quantities.

Systems that can be effectively described as a localized spin-s particle subject to time-dependent fields have attracted a great deal of interest due to, among other things, their relevance for quantum technologies. Establishing analytical relationships between the topological features of the applied fields and certain time-averaged quantities of the spin can provide important information for the theoretical understanding of these systems. Here, we address this question in the case of a localized spin-s particle subject to a static magnetic field coplanar to a coexisting elliptically rotating magnetic field. The total field periodically traces out an ellipse which encloses the origin of the coordinate system or not, depending on the values taken on by the static and the rotating components. As a result, two regimes with different topological properties characterized by the winding number of the total field emerge: the winding number is 1 if the origin lies inside the ellipse, and 0 if it lies outside. We show that the time average of the energy associated with the rotating component of the magnetic field is always proportional to the time average of the out-of-plane component of the expectation value of the spin. Moreover, the product of the signs of these two time-averaged quantities is uniquely determined by the topology of the total field and, consequently, provides a measurable indicator of this topology. We also propose an implementation of these theoretical results in a trapped-ion quantum system. Remarkably, our findings are valid in the totality of the parameter space and regardless of the initial state of the spin. In particular, when the system is prepared in a Floquet state, we demonstrate that the quasienergies, as a function of the driving amplitude at constant eccentricity, have stationary points at the topological transition boundary. The ability of the topological indicator proposed here to accurately locate the abrupt topological transition can have practical applications for the determination of unknown parameters appearing in the Hamiltonian. In addition, our predictions about the quasienergies can assist in the interpretation of conductance measurements in transport experiments with spin carriers in mesoscopic rings.

The impact of submucosal fatty tissue during colon endoscopic submucosal dissection in a western center.

OBJECTIVES: Obesity is associated with submucosal fatty tissue. The main aim of this study was to assess the impact of submucosal fatty tissue on the success of colonic endoscopic submucosal dissection (C-ESD) in a western population. METHODS: This was a retrospective analysis of 125 consecutive C-ESDs performed between October 2015 and July 2017. Fatty tissue sign was defined as positive when the submucosal layer was covered with fatty tissue. The complexity of performing an ESD was assessed by the performing endoscopist, defined by the occurrence of intraprocedural perforation, inability to complete an en-bloc resection or a procedure time exceeding 180 min. RESULTS: Fatty tissue sign positive was present in 44.8% of the procedures. There were 28 (22.4%) c-ESD defined as complex. Factors associated with complex ESD included; fatty tissue sign [odds ratio (OR) 12.5; 95% confidence interval (CI), 1.9-81.9; P = 0.008], severe fibrosis (OR 148.6; 95% CI, 6.6-3358.0; P = 0.002), poor maneuverability (OR 267.4; 95% CI, 11.5-6212.5; P < 0.001) and polyp size ≥35 mm (OR 17.2; 95% CI, 2.6-113.8; P = 0.003). In patients demonstrating the fatty tissue sign, BMI and waist-to-height ratio (WHtR) were higher (27.8 vs. 24.7; P < 0.001 and 0.56 vs. 0.49; P < 0.001, respectively) and en-bloc resection was achieved less frequently (76.8 vs. 97.1%, P = 0.001). Multivariate analysis revealed higher risk of fatty tissue sign positive associated with WHtR ≥0.52 (OR 26.10, 95% CI, 7.63-89.35, P < 0.001). CONCLUSION: This study demonstrates that the fatty tissue sign contributes to procedural complexity during C-ESD. Central obesity correlates with the likelihood of submucosal fatty tissue and as such should be taken into account when planning procedures.

System size synchronization.

In this paper we bring out the existence of a kind of synchronization associated with the size of a complex system. A dichotomic random jump process associated with the dynamics of an externally driven stochastic system with N coupled units is constructed. We define an output frequency and phase diffusion coefficient. System size synchronization occurs when the average output frequency is locked to the external one and the average phase diffusion coefficient shows a very deep minimum for a range of system sizes. Analytical and numerical procedures are introduced to study the phenomenon, and the results describe successfully the existence of system size synchronization.