Overall, 492 hospitalized patients with COVID-19 were retrospectively analyzed. Patients with reduced SpO2 were significantly older, had more comorbidities, higher body surface area (BSA) and body mass index (BMI), lower lymphocyte counts, impaired renal function, and elevated liver enzymes, c-reactive protein (CRP), and D-dimer levels as compared to those with preserved SpO2. In the multivariable regression analysis, older age (odds ratio (OR) 1.02 per year, p < 0.001), higher BSA  or BMI , lower lymphocyte counts , and elevated CRP  were found to be independent predictors of low SpO2. Severe hypoxemia requiring ventilatory support, older age, and pre-existing comorbidities, including underlying renal dysfunction and heart failure, were found to be significantly associated with in-hospital mortality. These findings suggest that assessment of predictors of hypoxemia early at the time of hospitalization with COVID-19 may be helpful in risk stratification and management. Hypoxemia is a hallmark of coronavirus disease 2019 (COVID-19) severity. We sought to determine predictors of hypoxemia and related adverse outcomes among patients hospitalized with COVID-19 in the two largest hospitals in Jerusalem, Israel, from 9 March through 16 July 2020. Patients were categorized as those who developed reduced (<94%) vs. preserved (≥94%) arterial oxygen saturation (SpO Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic with enormous morbidity and mortality burdens. Risk factors for severe outcomes from COVID-19 infection may include older age, male gender, and chronic underlying health conditions, such as diabetes mellitus (DM), hypertension, obesity, ischemic heart disease, and heart failure (HF) ,4,5. Alt2) is an important marker of disease severity in accordance with World Health Organization (WHO) guidelines [2 < 94% has been associated with moderate to severe disease and high morbidity as compared to patients with preserved blood oxygen saturation (SpO2 ≥ 94%) [2 < 90% despite oxygen supplementation) were associated with increased in-hospital mortality [Development of respiratory complications during hospitalization with COVID-19, ranging from mild hypoxemia to acute respiratory distress syndrome (ARDS) requiring intubation and mechanical ventilation, is an important clinical hallmark of the disease severity . Noninvaidelines . Specifi2 ≥ 94%) ,9. In moortality . Moreoveortality ,11,12. ATherefore, in the present double-center study, we sought to investigate whether there might be unique predictors of the development of hypoxemia during hospitalization due to COVID-19 and to examine their associations with subsequent adverse clinical outcomes. This double-center retrospective cohort study enrolled adult patients (age ≥18 years of both genders) with COVID-19 hospitalized at the only two tertiary medical centers in Jerusalem, Hadassah University Medical Center and Shaare Zedek Medical Center, from 9 March through 16 July 2020. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Boards of the two medical centers, Hadassah University Medical Center (ethics committee number: HMO-0460-12) and Shaare Zedek Medical Center (ethics committee number: SZMC-0158-20). Data were collected separately at each institution and were later submitted into an electronic case report form (eCRF).2 levels for assessment of disease severity within 48 h after arrival to the emergency department: mild/moderate (SpO2 ≥ 94%) or severe (SpO2 < 94%) disease as previously described [Patients were included in the study if they met the following criteria: confirmed COVID-19 infection based on positive nasopharyngeal swab real-time reverse transcriptase polymerase chain reaction (RT-PCR) testing; typical symptoms of a respiratory infection/pneumonia, i.e., fever, cough, dyspnea, etc.; and objective evidence of new-onset pulmonary infiltrates on chest computed tomography (CT) requiring hospitalization. For the purpose of our study, patients were categorized according to their SpOescribed ,8 and as0.5 * height0.5, and body mass index (BMI) measures were calculated according to the formula: BMI = weight/height2. Estimated glomerular filtration rate (eGFR) was calculated using the Cockcroft–Gault (CG) formula. For analyzing the length of stay in hospital and in-hospital mortality, follow-up duration was recorded as the interval (in days) from the date of admission to the date of discharge or the date of death, whichever occurred first. Acute respiratory distress syndrome (ARDS) was defined according to the Berlin Criteria as described previously [Demographic and clinical characteristics were collected from electronic medical records, medical history, and physical examination findings. Measures of complete blood count (CBC) and white blood cell differential, basic metabolic panel, and markers of inflammation, including CRP and D-dimer, were all acquired at the time of admission to the hospital. Weight and height were used to calculate the body surface area (BSA) measures according to the Mosteller formula : BSA = 0eviously .2 < 94%) using the chi-square test for categorical variables (or Fischer’s exact test if the expected count was below 5), t test or analysis of or variance (ANOVA) for normally distributed continuous variables, and Wilcoxon signed rank or Kruskal–Wallis tests for continuous variables with skewed distribution. Univariate followed by multivariate logistic regression models were constructed to identify factors associated with hypoxia. In the multivariable model, we used a backward stepwise analysis by including all variables with p-values < 0.1 obtained in the univariate model. Results were expressed as odds ratios (ORs) with 95% confidence intervals (CIs). We also used a receiver operating characteristic (ROC) curve analysis to determine the optimal cutoff values of the independent variables for predicting low SpO2 based on the threshold yielding the best combination of sensitivity and specificity. A Cox regression model was run to determine associations with in-hospital mortality, expressed as hazard ratios (HRs) with 95% CIs. Data were analyzed using the JMP software, Version 14.1 , with all statistical tests conducted at the 5% significance level.Data were checked for accuracy and out-of-range values by the coordinating unit prior to statistical analysis. Categorical variables were expressed as frequency and percentage, and continuous variables were expressed as mean ± standard deviation (SD) or as median and interquartile range (IQR) where appropriate. Patient characteristics were compared between those with and without reduced oxygen saturation (SpO2 < 94%) and 271 (55%) had preserved oxygen saturation (SpO2 ≥ 94%) during hospitalization. Baseline demographic, clinical, and laboratory characteristics and treatment information of the overall patient cohort and a comparison of those with and without low SpO2 (<94%) are presented in 2 and 28.20 ± 6.10 kg/m2, respectively. Regarding comorbidities, 42% of patients had a history of hypertension, 28% had hyperlipidemia, 29% had DM, 18.8% had a cognitive decline, and 17.8% had atherosclerotic cardiovascular disease (CVD).Overall, 683 COVID-19 confirmed patients were admitted to either one of the two major hospitals in Jerusalem during the study period. After screening, 492 patients were found to have available data at baseline and thus included in the study analysis. When stratified by arterial oxygen saturation, 221 (45%) were found to develop hypoxemia (SpO2 ≥ 94%), patients with low oxygen saturation (SpO2 < 94%) were older , were more likely to be males , and had higher BSA  and BMI  , whereas the use of other medications was similarly distributed between the two groups. Analysis of laboratory data showed that patients with low SpO2 had decreased lymphocyte counts, but similar white blood cell counts, as compared to those with preserved SpO2. Patients with low SpO2 had significantly higher blood urea nitrogen (BUN), creatinine, aspartate transaminase (AST), gamma-glutamyl transferase (GGT), and D-dimer and lower eGFR than those without low SpO2. CRP levels were markedly increased in the low SpO2 group (7.3 (4.0–13.5) vs. 1.5 (0.4–5.2); p < 0.001) compared with the preserved SpO2 group (Compared to patients with preserved oxygen saturation (SpO< 0.001) . Furthero groups . TreatmeO2 group .2 during hospitalization with COVID-19 (p < 0.001), male gender , higher BMI , higher BSA , DM , and hypertension  were found to be significant predictors of low SpO2 in the univariable analysis. Furthermore, treatment with ACE inhibitors/ARBs  and diuretic therapy  were significantly associated with low SpO2. Among the laboratory parameters, blood urea nitrogen (BUN) , CRP , D-dimer , fibrinogen , AST , and lower lymphocyte count  at baseline were significant predictors of low SpO2.Univariable and multivariable regression models were constructed to examine the association of baseline demographic and clinical parameters with development of low SpOCOVID-19 . Older ap value < 0.1 obtained from the univariate model, older age , higher BMI , lower lymphocyte count , and elevated CRP  were independent predictors of low SpO2 . When BSA, instead of BMI, was included in the multivariable regression model, the same independent predictors, including older age , lower lymphocyte count , and elevated CRP  were obtained. Higher BSA was also found to be a significant predictor of low SpO2  in this model  for age, BMI, BSA, lymphocyte count, and CRP was 0.67, 0.65, 0.64, 0.71, and 0.79, respectively. The optimal cutoffs (with sensitivity and specificity) for predicting low SpO2 of these variables were as follows: age of 50 years (yielding a sensitivity of 75% and specificity of 50%), BMI of 27.4 kg/m2 (65% and 62%), BSA of 1.9 m2 (61% and 60%), lymphocyte count of 1400 cells/µL (77% and 59%), and CRP of 4 mg/dL (76% and 71%). When age, BMI, lymphocyte counts, and CRP were all included in the ROC analysis, they demonstrated improved diagnostic performance for low oxygen saturation (AUC 0.81 (95% CI: 0.77–0.85) with a sensitivity and specificity rate of 87% and 62%, respectively, p < 0.001). Substitution of BMI with BSA in multivariate ROC analysis resulted in similar diagnostic performance (AUC 0.80 (95% CI: 0.76–0.84) with a sensitivity and a specificity rate of 80% and 70%, respectively, p < 0.001). Using the optimal cutoffs of the variables found to be independently associated with low SpO2, we found the mean (SD) oxygen saturation was significantly lower among patients at age ≥ 50 , with BMI ≥ 27.4 kg/m2  or BSA ≥ 1.9 m2 , lymphocyte count <1400 cells/μL , and those with CRP ≥ 4.0 mg/dL   .2 was observed. Furthermore, the proportion of patients with SpO2 < 94% increased according to the number of risk factors; 2.4% of patients who had none of these variables compared with 80.3% of those with all risk factors were found to develop low oxygen saturation  in each patient. As shown in turation b. Similaturation .2 < 94%) due to COVID-19, 41 (18.6%) required ventilation (14 (6.3%) noninvasive and 27 (12.2%) invasive ventilation) and 22 (10.0%) developed ARDS during hospitalization. By comparison, ventilation was required in 11 (4.1%) patients (6 (2.2%) noninvasive and 5 (1.9%) invasive) and ARDS developed in 4 (1.5%) patients among those who did not have early low oxygen saturation. Consequently, early identification of SpO2 < 94% was associated with increased odds of ventilation  and development of ARDS  compared with preserved SpO2. Length of stay in hospital was significantly longer in patients with SpO2 <94% as compared to patients with SpO2 ≥ 94% (8 (5–13) vs. 4 (2–8) days; p < 0.001). Of the 221 patients developing early hypoxemia , with higher BMI  and a trend towards higher BSA , lower lymphocyte count , and low CRP levels  (trend < 0.001) (trend < 0.001), with approximately one out of six patients with all risk factors  developing ARDS vs. none of those without any or only one of these risk factors. Finally, LOS was also significantly longer in the presence of higher risk score  (Consistent with the predictors of low SpO< 0.001) a. The pr< 0.001) b. Simila< 0.001) c.p < 0.001). In-hospital mortality occurred more frequently in patients with low oxygen saturation requiring ventilation  and those who developed ARDS . Invasive ventilation was associated with an 8.6-fold increase in the probability of in-hospital mortality compared with patients who did not require ventilation or were treated only with noninvasive ventilation .In total, 33 patients (6.7%) died during hospitalization for COVID-19. The median (IQR) LOS in hospital for the overall cohort was 6 (3–9) days (5 (3–10) days vs. 10 (6–16) days for those who survived and those who died during hospitalization, respectively; p < 0.001), female gender , underlying HF , established CVD , and the presence of any comorbidity  , but not BMI  or BSA , were significantly associated with increased in-hospital mortality (p = 0.090). After adjustment for age and gender, heart failure , chronic renal failure , and the presence of any comorbidity  remained significantly associated with an increased risk of in-hospital mortality, while the associations of hypertension and CVD with mortality were attenuated (p = 0.036)  15.7, 95% CI: 2.1–115.8; ortality . A trendtenuated . High BM= 0.036) .While most studies have focused on predictors of mortality among patients affected by COVID-19, our study provides insights into unique and clinically plausible risk factors for hypoxemia. By considering hypoxemia as an intermediate outcome, which could be initially silent until deterioration may occur, assessment of these risk factors may be helpful in more appropriate patient triage and aggressive treatment with oxygen supplementation to mitigate disease progression. In this current retrospective double-center study involving hospitalized patients with COVID-19, we report on several key observations regarding risk factors for hypoxemia and subsequent related outcomes in a relatively large sample of moderately to severely ill patients with COVID-19. Our study highlights several salient findings. First, the present data demonstrated that older age, obesity, lymphopenia, and elevated CRP were independent predictors of hypoxemia that occurred early after hospitalization with COVID-19. Besides the individual predictive value of each of these risk factors, the presence of multiple factors in the same patient had an improved diagnostic performance of hypoxemia in this population. Second, BSA was found to be a noninferior measure of body habitus in predicting hypoxemia when compared to BMI, and therefore, it may serve as an additional important prognostic indicator for COVID-19 severity. Third, hypoxemia was associated with respiratory-related adverse events, including requirement for ventilation and development of ARDS, and longer in-hospital LOS. Finally, we found that severe hypoxemia requiring ventilatory support as well as other comorbidity factors, including older age, chronic renal failure, and underlying HF, were significantly associated with increased in-hospital mortality.COVID-19 pneumonia is mainly characterized by progressive hypoxemia that can ultimately lead to ARDS and high mortality rates. Among the potential mechanisms underlying the development of low oxygen saturation in COVID-19 patients are potentiated immune response to viral infiltration, inflammation and proinflammatory cytokine release, pulmonary vasoconstriction, and COVID-19-related intravascular thrombosis and pulmonary emboli ,16. On tThe association of inflammatory markers with high oxygen requirement has not been adequately studied. In 84 Japanese patients admitted with mild to moderate COVID-19, advanced age, lymphopenia, and obesity, but not CRP, were associated with increased oxygen requirements . This isAdditional important finding of our study is the role of body habitus, represented by BMI or BSA, in prediction of COVID-19-related hypoxemia. Morbid obesity has been shown to be an important risk factor for respiratory infections and for severe COVID-19 ,28. AccoIn line with previous reports ,34, the The current study confirmed that increased age, specifically 60 years old or older, was independently associated with in-hospital mortality in patients with COVID-19, similarly to previous reports ,35,36. OThe results of this analysis are subject to limitations inherent to the observational, retrospective, nonrandomized design of our study. Therefore, as in any observational study, we cannot rule out residual confounding and survival treatment selection. For example, as it was the “second wave” of the pandemic, no information was available on anosmia, hyposmia, or treatments for COVID-19 during hospitalization, which varied throughout the study period. As multiple testing was performed using many variables in our models, we cannot rule out an inflated rate of false-positive conclusions. However, in the regression models, we included the most clinically relevant variables that could be implicated in the development of hypoxemia. Although our data is based on ethnically diverse population living in Jerusalem , it needs to be validated in other communities, such as in Asia and South America, where COVID-19 is still an expanding pandemic with limited resources. In conclusion, our double-center cohort analysis demonstrates that among patients hospitalized with moderate to severe COVID-19, older age, lymphopenia, and elevated CRP were independent predictors of hypoxemia and respiratory-related adverse outcomes. Both large body size measurements, as reflected by increased BMI or BSA, were associated with low oxygen saturation. Severe hypoxemia requiring ventilatory support and underlying comorbidities, including older age, chronic renal failure, and underlying HF, were identified as significant predictors of in-hospital mortality. In the context of the current, still-expanding COVID-19 pandemic in many developing countries, which struggle with scarce health and economic resources, detailed assessment of these risk factors at the time of hospitalization may be helpful in appropriate patient triage and early management of hypoxemia and may ultimately contribute to reducing the disease burden in these communities.


Arabidopsis thaliana, seven flowering genetic pathways have been described under specific growth conditions. However, the evidence condensed here suggest that these pathways are tightly interconnected in a complex multilevel regulatory network. In this review, we pursue an integrative approach emphasizing the molecular interactions among the flowering regulatory network components. We also consider that the same regulatory network prevents or induces flowering phase change in response to internal cues modulated by environmental signals. In this sense, we describe how during the vegetative phase of development it is essential to prevent the expression of flowering promoting genes until they are required. Then, we mention flowering regulation under suboptimal growing temperatures, such as those in autumn and winter. We next expose the requirement of endogenous signals in flowering, and finally, the acceleration of this transition by long-day photoperiod and temperature rise signals allowing A. thaliana to bloom in spring and summer seasons. With this approach, we aim to provide an initial systemic view to help the reader integrate this complex developmental process.Flowering is one of the most critical developmental transitions in plants’ life. The irreversible change from the vegetative to the reproductive stage is strictly controlled to ensure the progeny’s success. In  Arabidopsis thaliana (hereafter Arabidopsis), a species from the Brassicaceae family, the Shoot Apical Meristem (SAM) becomes an Inflorescence Meristem (IM), which develops the Floral Meristems (FMs) at its flanks. [Flowering transition is a fundamental trait in plant development that marks the end of the vegetative phase and the beginning of the reproductive state. During this process, in  flanks. ,2. Then, flanks. .Arabidopsis flowering mutant plants were selected under contrasting environments. Historically, four types of late-flowering mutants were found when they grew specifically under long-day (LD) or short-day (SD) photoperiods; those whose bolting time was delayed after vernalization treatment and a fourth group that showed a late-flowering phenotype under both photoperiods, but could be recovered by vernalization treatment [The integration of developmental and physiological cues and the response to environmental signals forecast the best time for flowering to ensure the success in reproduction and the offspring’s viability . In ordereatment . After preatment ,7,8; thereatment ,10,11; treatment ,13,14, areatment ,16.Afterward, many other genes have been discovered to function in flowering transition by reverse genetics and expression profiling . FollowiLFY is one of the first genes induced at the primordial cells committed to forming the FM [It has been considered that different pathways converge into a few transcription factors (TFs) known as integrators of flowering time: FLOWERING LOCUS C (FLC), FLOWERING LOCUS T (FT); SUPPRESSOR OF OVER EXPRESSION OF CONSTANS (SOC1) and, LEAFY (LFY) ,28,29,30g the FM , and it g the FM , while Sg the FM ,34.Arabidopsis reproductive phase change. However, information regarding the individual flowering genetic pathways can be consulted in different reviews [This hierarchical scheme of flowering transition has changed over time as more genes have been uncovered. The current model proposes a complex genetic network of about 300 genes that underlies floral transition ,35,36. I reviews ,37,38,39Arabidopsis, these repressors were identified from early flowering loss of function mutants or late flowering overexpressor mutants [Premature reproduction under suboptimal environmental conditions or at the early stages of development has implications on pollination and seed formation, with repercussions on the species’ fitness . Therefo mutants ,45,46,47FLC [One of these flowering repressors is FLC ,42, a MAFLC ,49,50.SOC1 (a MADS-box gene) and FT, while in the IM, it directly delays the expression of SOC1 and FD [FLC expression. This feedback loop is relevant for both flowering time and seed dormancy [FLC negatively regulates important flowering promoters. In the leaves, it directly represses 1 and FD ,52. Convdormancy ,53.SOC1 and FT in response to temperature changes, vernalization, and photoperiod [FLC and other members of this clade, such as FLOWERING LOCUS M (FLM/MAF1), MADS AFFECTING FLOWERING 2 to 5 (MAF2-5), and SVP, have functional redundancy, partly because of their interchangeable protein protein interactions ,55,56,57toperiod ,59,60,61TEMPRANILLO1 (TEM1) and CONSTANS-LIKE 1 and 4 (COL1/4), while SVP targets SEPALLATA3 (SEP3) and SCHLAFMÜTZE (SMZ) without the requirement of FLC. Furthermore, both proteins can bind independently to FT and SOC1 genes [GA2OX) genes that encode GA-catabolic enzymes, and both FLC and SVP repress GA20OX2, a key GA4 biosynthetic enzyme. Consistent with this, single and double svp flc mutants are early-flowering, and the svp plants contain elevated GA levels [GA2OX genes [Global binding mapping of FLC and SVP to their target loci in mutant backgrounds has shed light on how these MADS-domain proteins act as flowering repressors ,62,63. AC1 genes . InteresA levels ,64. On tOX genes , but itsTARGET OF FLC AND SVP 1 (TFS1) gene to deposit the trimethylation of histone H3 lysine 27 (H3K27me3), which is a repressive epigenetic mark. TFS1 encodes a B3-type TF, and tfs1 plants are late flowering, particularly under short days. After FLC is silenced, SOC1 acts as a pioneer TF that associates with the histone demethylase RELATIVE OF EARLY FLOWERING 6 (REF6) and the chromatin remodeler BRAHMA (AtBRM), allowing the binding of the SQUAMOSA BINDING PROTEIN LIKE 9 (SPL9) TF to the TFS1 locus. Moreover, the RNA-polymerase II (RNAPII) is recruited through the Mediator (MED) complex, resulting in the upregulation of TFS1 at the shoot apex [Another genome-wide study among FLC, SVP, and SOC1 showed that they share common targets, but SOC1 function in an antagonistic manner . FLC andoot apex .FLC, FLM, MAF4, and MAF5 through BRASSINAZOLE-RESISTANT 1 (BZR1), which in the case of FLC recruits EARLY FLOWERING 6 (ELF6), that removes H3K27me3 repressive marks. The other way is by direct BZR1 repression of SOC1 [Interestingly, brassinosteroids (BRs) also inhibit floral transition and promote vegetative growth in two ways. In one of them, BRs induces the expression of  of SOC1 .FLC must be silenced. Multiple proteins participate in FLC transcriptional and posttranscriptional regulation. Although our knowledge is still limited, the chromatin remodeling proteins, such as the histone demethylase FLOWERING LOCUS D (FLD); the HISTONE DEACETYLASES 5 and 6  together with FVE , could be associated in a co-repressor complex at the FLC locus [FLC epigenetic silencing [When plants reach a developmental stage for flowering competence, LC locus ,68,69,70ilencing ,74,75,76FLC mRNA processing: FCA, FPA, and FLOWERING LOCUS KH DOMAIN (FLK) are RNA-binding proteins [FLC transcript accumulation. Some members of the HUA PEPPER (PEP) family promote its messenger stabilization [Besides chromatin modifiers, there is a group of proteins that negatively affect proteins ,78,79; Fproteins , and PCFproteins ,81,82,83lization ,85,86.FLC, FCA and FVE may also act as negative regulators of SVP, since the late-flowering phenotype of fca-9 and fve-3 was suppressed by mutations in the SVP gene [fca-9 and fve-3 may be disrupting the FLC-dependent functions of SVP in flowering.Apart from repressing SVP gene . AlternaFLC expression includes various complex molecular processes in which both chromatin modifiers and RNA-binding proteins participate [COLD INDUCED LONG ANTISENSE INTRAGENIC RNAs (COOLAIR), which are transcribed from the 3’-end of FLC and proximately polyadenylated by FCA, FPA, and FY, and spliced by PRP8 [COOLAIR variants could lead to FLD recruitment, which demethylates H3K4me2, reducing the transcription of both sense and antisense FLC mRNAs [COOLAIR for H3K27me3 deposition at the FLC locus [Far from being a linear pathway, developmental downregulation of ticipate ,69,74. T by PRP8 . Some ofLC mRNAs ,88. AlteLC locus .FLC expression and protein stability or activity. In the ck2 α-subunit triple mutant, non-phosphorylated components of the autonomous pathway led to higher FLC levels and, consequently, a late flowering phenotype [FLC expression, depending on the B subunit of the PP2A trimeric complex [FLC-FLAG construct that mimics FLC in the phosphorylated state are early flowering [Furthermore, Casein kinase 2 (CK2) phosphorylation and phosphatase 2A (PP2A) dephosphorylation may regulate henotype . Meanwhi complex . At the lowering . SUMOylalowering . Moreovelowering .FLM and SVP are also regulated at the posttranscriptional and posttranslational levels [SOC1 and FT regulatory sequences. J3 is expressed throughout Development but it is upregulated by long-day photoperiod, gibberellins, and vernalization in a FLC independent manner [l levels ,61,94. Ll levels . Additiot manner .APETALA 2 (AP2)-like genes directly or indirectly via transcriptional repression of the microRNA 172A (MIR172A) [SOC1 and FT promoters and repress their expression [AP2-like genes by either GIGANTEA (GI) or developmental induction of miR172, promote floral transition [FLC and SVP, but it was completely suppressed in the flm mutant [FT expression was restored [SMZ repression depends strictly on FLM, but the molecular mechanism is still unknown.During the vegetative phase, SVP upregulates MIR172A) ,96. MeanMIR172A) ,97. AP2 pression ,97. Thusansition ,99. Intem mutant . The latrestored . TherefoTEM1 and TEM2 genes are also part of the AP2-like family of TFs, but miR172 does not downregulate them. TEM1 and TEM2 repress the transcription of FT [MIR172 genes [GA3OX1 and GA3OX2 [FT transcription under SD conditions [CO in LD photoperiod [FT in SD. However, GI transcription in this condition is also limited by FAR 1 RELATED SEQUENCE 7 (FRS7) and FRS12 TFs [FT levels in LD [The on of FT , MIR172 72 genes , and thed GA3OX2 , hence inditions  and a ditoperiod . InteresRS12 TFs . Moreovels in LD .FT and SOC1 [MIR156 [FLC, SVP, MAF3, MAF5, AGL18, MIR172, SPL3, AGL19, AGL24, FRUITFULL (FUL), and LFY [agl15 agl18 double mutant showed an additive effect on flowering time acceleration when it was crossed with flc, flm, and svp mutants, indicating that they act independently [AP2 and the AP2-like genes TEM1, TARGET OFEARLY ACTIVATION TAGGED 1 (TOE1), and TOE3, as well as MIR172A, SOC1, and SPL11 [AGAMOUS-LIKE 15 (AGL15) and AGL18 are other flowering repressors belonging to the MADS-box TFs family . Both coand SOC1 ,105 and  [MIR156 . AGL15 a and LFY ,107. Theendently . Interesnd SPL11 ,105,107.nd SPL11 ,105.SOC1 and FT before flowering partially depends on the interaction of PRC2 components CLF, EMBRYONIC FLOWER 2 (EMF2) and MSI1 with the catalytic subunit of DNA Polymerase Ɛ, EARLY IN SHORT DAYS 7 (ESD7) [FLC, FT, and SOC1 genes [The repressed state of 7 (ESD7) ,109. The7 (ESD7) , acts in7 (ESD7) . LHP1 reC1 genes ,114,115 C1 genes ,116. RepC1 genes . Hence, FT and SOC1 repression, respectively [FT and SOC1 by EBS and SHL, the SIN3 LIKE (SNL) proteins function as a scaffold for histone deacetylase assembly complexes to repress TOE1, TOE2, and SMZ, indirectly allowing FT expression in LD growing plants [EARLY BOLTING IN SHORT DAYS (EBS) and its paralog SHORT LIFE (SHL) are required for ectively ,118. Theectively . EBS andectively . Contrarg plants .svp-41 flc-3 ft-10 tsf-1 soc1-2) screening [SPL15, was highly enriched with the H3K4me3 mark in the chr4-2 mutant compared to wild-type, correlating with higher transcript levels of this gene. It seems that CHR4 interacts with many TFs and other chromatin remodelers in protein complexes that differentially affect the floral transition [Recently, another epigenetic component was unraveled from a mutagenized quintuple mutant , TOE1, 2, and 3 via translational inhibition [Another important mechanism involved in vegetative phase maintenance consists on the negative posttranscriptional control of miR156 over  factors ,124,125.ve stage . Transcry sugars ,128 and together ,130. Morpression . Intricatoperiod  and by Ftoperiod . In retuhibition ,132.In conclusion, mutual inhibition between flowering repressors and promoters, in collaboration with epigenetic modifiers, controls the precise moment of flowering transition.Arabidopsis, temperatures between 5–16 °C, negatively affect flowering in many natural accessions [Among the multitude of environmental signals to which plants respond to synchronize their development to adequate conditions, low temperatures affect flowering time in several plant species ,134. In cessions . On the cessions .Arabidopsis natural populations in response to ambient temperature changes. This regulation resides within the noncoding regulatory regions that affect the expression of FLM [The molecular mechanisms that regulate plants’ response to subtle changes in ambient temperature have begun to be discovered ,138. Thrn of FLM .FLM is subject to temperature-dependent alternative splicing that results in the inclusion of the second (FLM-β) or the third exon (FLM-δ), respectively [Arabidopsis SPLICING FACTOR 1 (AtSF1) preferentially binds to the first intron branch site of FLM pre-mRNA producing the flowering-repressive FLM-β isoform. Accordingly, the atsf1-2 mutant which has very low levels of FLM-β and significant higher levels of FLM-δ, is early flowering, but it has lost the sensitivity to temperature control [Furthermore, ectively ,61. Inte control .SOC1, FT, and TWIN SISTER OF FT (TSF) expression and promotes TEM2 transcription. Thereby, the SVP-FLM-β complex prevents precocious flowering under suboptimal temperatures [flm-3 loss-of-function mutant, which would be expected if FLM-δ acts as a dominant-negative [FLM transcript levels are reduced through alternative splicing coupled with nonsense-mediated mRNA decay (AS-NMD), resulting in a net loss of SVP-FLM-β complex [Between 10 °C and 16 °C, SVP associates with the FLM-β isoform and represses eratures ,61. On teratures ,61. Aftenegative . Hence, negative ,141. In  complex . Further complex .MAF genes decrease plants’ sensitivity to temperature changes [MAF2 undergoes a temperature-dependent alternative splicing process too [MAF2var1 [As FLM, MAF2 prevents flowering after short periods of cold, and mutations in  changes ,142. MAFcess too ,144. At FCA itself is regulated by alternative splicing and only the FCA-γ mRNA variant produces a functional protein [SPL3 mRNA by miR156 is enhanced at 16 °C. Downregulation of SPL3, results in lowering FT expression, which is a direct target of SPL3 in the leaves, preventing flowering under suboptimal temperatures [There are several miRNAs differentially expressed at 16 °C and 23 °C. From those involved in temperature-dependent regulation of flowering, miR156 and miR169 are upregulated at 16 °C, while miR172 accumulates at 23 °C. Interestingly, accumulation of miR172 depends posttranscriptionally on FCA which is preferentially accumulated at optimal temperatures . FCA its protein ,146. Con protein . Among teratures .cryptochrome 1 and 2 genes (cry1 and cry2) in combination with phytochrome A (phyA) show a drastic flowering delay under 16 °C compared to 23 °C [phyB single mutant and the phyA phyB phyD triple mutant are early flowering at optimal temperatures, but they flower at the same time as wild-type plants at 16 °C. In this case, phyE which is still active in the triple mutant, mediates this response by indirectly repressing FT expression under cooler temperatures and this process occurs independently of FLC and FLM mediation [Mutants in to 23 °C . Also, pediation . Therefoediation .constitutive photomorphogenic 1 (cop1) mutant has an early flowering phenotype that shows almost no delay response to low temperatures. At 16 °C, COP1, a RING-finger E3 ubiquitin ligase, is stabilized and favors GI turnover. Again, this condition abolishes FT direct induction by GI, suppressing in this way flowering induction [The nduction . TherefoArabidopsis plants to flower in autumn or during subtle climate changes.In brief, low temperature triggers different mechanisms that prevent Arabidopsis accessions depends on FRIGIDA (FRI) and, or FLC alleles [Vernalization requirement on the other hand, varies significantly among different plants and even between different natural populations of the same species . Studies alleles .FLC locus is enriched with chromatin marks related to transcriptional activation, such as H3K4me3, H3K36me3, and histone acetylation, deposited by a FRI-supercomplex in plants with an active FRI allele [FLC in summer-annual accessions [Before winter, the I allele ,153. Howcessions .FLC locus are important for its own transcriptional regulation , inhibits COOLAIR expression and consequently promotes FLC expression [COOLAIR at the beginning of vernalization treatment, correlates with drastic reduction in the levels of the encoding FLC transcript, independently of PRC2 [DNA structural conformations at the gulation A. For exve state . SWITCH/pression . The forpression . However of PRC2 ,159,160, of PRC2  , FERTILIZATION-INDEPENDENT ENDOSPERM (FIE), MSI1 and predominantly the SWN methyltransferase initially deposits the H3K27me3 mark at the nucleation region ,166,167.FLC locus in the sense direction: COLD ASSISTED INTRONIC NONCODING RNA (COLDAIR) is transcribed from the first intron [COLD OF WINTER-INDUCED NONCODING RNA FROM THE PROMOTER (COLDWRAP) from the proximal FLC promoter. COLDAIR and COLDWRAP accumulation levels, peak at 20 and 40 days, respectively, after vernalization initiation [FLC [Later during vernalization, two other lncRNAs are transcribed from the t intron , and COLitiation . Interesion [FLC   spreads the H3K27me3 mark throughout the entire FLC gene . LHP1 toilencing ,113. Conilencing ,161  and AGL24 are the only TFs known to participate in flowering transition in response to vernalization. Both of them, are induced by vernalization, independently of lization ,176.AGL19 and AGL24 are repressed by HDA9 under short-day conditions, probably to avoid early flowering [AGL19 is epigenetically silenced by the EMF-2 Polycomb repressive complex in non-vernalized plants [AGL19 is induced when the H3K27me3 marks are reduced, particularly at the 5′ region of the first intron [lowering ,177,178 d plants . Howevert intron .It is known that AGL24 participates in flowering transition in response to other signals ,181. HowPlant’s endogenous cues that participate in flowering transition are present independently of the season, although environmental signals influence them. In this section, we describe the essential role of gibberellins and the effect of the trehalose-6-phosphate signaling, which constitutes a sensor of sugars availability and hence the plant’s reserves to support reproduction ,182,183.Arabidopsis SPL TFs family are posttranscriptionally repressed by miR156 [Two microRNAs, miR156 and miR172, show opposite temporal expression patterns and functions and have an essential role in phase transitions during plants’ development. miR156 is expressed during the early stages of development and is involved in juvenile phase maintenance, while miR172 levels increase with aging and promote adult vegetative traits, as well as the transition to the reproductive stage ,186,187.y miR156 ; from thy miR156 ,192,193.SPL mRNAs accumulation. In turn, SPL9, SPL10, and SPL15 induce reproductive transition by regulating genes related to flowering and binding to the MIR172B promoter [AP2 and AP2-like flowering repressors, which repress SPL3, SPL4, and SPL5 (SPL3/4/5) genes [SOC1 and AP1 genes [As the plant ages, miR156 levels gradually decrease, allowing promoter ,191. Sub5) genes ,187,194.P1 genes .FUL and AP1 are their direct targets. Meanwhile, MED25 enrichment in FUL and AP1 promoters is severely reduced in the triple mutant spl10 spl11 spl2, indicating that these SPLs are required for MED25 recruitment to these loci [SPL10 and its closest homologs SPL11 and SPL2 have been implicated in flowering regulation as well ,193. ChrFUL, LFY, AP1, and MIR172C delaying flowering transition when plants grow under white light. However, under shade conditions, FHY3 and FAR1 protein levels decrease, and SPL3/4/5 can induce those genes [Interestingly, two TFs involved in phyA signaling, FAR-RED ELONGATED HYPOCOTYL 3 (FHY3) and FAR-RED IMPAIRED RESPONSE 1 (FAR1), have been shown to interact with SPL3/4/5. These interactions impede the latter’s binding to the promoters of se genes . This mespl3 spl4 spl5, spl9 spl15, and spl10 spl11 spl2 show a more significant delay in flowering, particularly under SD [spl15-1 flowers extremely late compared to wild-type plants when grown in SD, suggesting that SPL15 plays a relevant role in flowering regulation under this photoperiod [FUL and MIR172. These three genes show a synergistic effect on flowering promotion [SPL impact on flowering time has been relatively difficult to study due to the high functional redundancy among their members. Single knockout mutants do not show a late flowering phenotype, while double and triple mutants such as under SD ,193,194.toperiod . Indeed,romotion 3 or GA4 compounds accelerate flowering time in Arabidopsis, although GA4 seems to be the active molecule in flowering regulation since it is the one that accumulates the most at the shoot apex. High levels of this particular compound correlate with strong induction of LFY and AP1 at the incipient FM [GA constitute a group of tetracyclic diterpene compounds that have multiple functions. It was Lang (1957) who first described the effect of these hormones as bloom inducers . Exogenopient FM .Arabidopsis: REPRESSOR OF ga1-3 (RGA), GIBBERELLIN INSENSITIVE (GAI), and RGA-LIKE 1 (RGL1), RGL2, and RGL3 [FT induction under LD conditions [SOC1 partly through REF6 regulation [GA signaling occurs through the degradation of DELLA proteins ,200. Thiand RGL3 ,203,204.and RGL3 . In thisnditions ,207. On gulation .SLY1 E3 Ubiquitin Ligase complex, leading to ubiquitination of DELLAs and, consequently, to their degradation through the proteasome 26S [GA signaling begins when their levels increase, and they bind to the receptor GIBBERELLIN INSENSITIVE DWARF 1 (GID1). This union induces a conformational change, allowing GID1 to interact with DELLA proteins. The formation of the GA-GID1-DELLA complex then promotes the interaction between DELLAs and the F-box protein SLEEPY1 (SLY1), which is part of the SCFsome 26S ,210,211.SUCROSE 2 (SUC2) or from the IM-specific FD promoter, both delay flowering in LD growing plants. However, only the lines expressed in the IM affect flowering time under SD conditions [Arabidopsis [ga1-3 and ga1-6), or the 35S:miR156 line, show moderate late-flowering phenotypes when grown in LD, whereas they flower very late or even fail to do it under SD [Endogenous cues regulate reproductive transition by activating flowering associated genes in the leaves and the shoot apex, but under SD conditions, signaling at the SAM becomes essential to induce flowering. An illustrative experiment showed that if DELLAs or GA catabolic enzymes are expressed either by the phloem-specific promoter nditions ,212. Thubidopsis . Consistunder SD .no flowering in short day (nfl) affects GA biosynthetic genes expression, and it can be rescued by GA addition, indicating that NFL controls flowering transition through regulation of GA biosynthesis [FT expression, independently of CO [FT in a CO antagonistic manner [The basic helix-loop-helix (bHLH) family of TFs is involved in GA biosynthesis and action during the flowering transition. The mutant ynthesis . Furtherly of CO . Moreovec manner .SPL3/4/5 by GA in the SAM is mediated by SOC1 [FUL and MIR172B [SPL10, which indirectly contributes to FT induction via miR172 accumulation in the leaves [Induction of  by SOC1 ,218. Fur MIR172B . Additioe leaves ,123.SOC1 [AP1 transcription, since SPL9-mediated expression of AP1 strongly decreases when plants are treated with GAs [Interestingly, DELLA/GA signaling affects SPL9 function by two opposing mechanisms. On one hand, GA-induced ubiquitination of RGA is required for SPL9 to induce SOC1 . On the with GAs . The latwith GAs ,219,220.SOC1 and FT regulatory regions is enhanced in the presence of RGA; thereby, its degradation by the addition of GA3 reduces FLC repressive action [SOC1 through the activity of NF-Y, or by downregulation of GATA NITRATE-INDUCED, CARBON METABOLISM INVOLVED (GNC), and its paralog GNC-LIKE (GNL), which encode direct repressors of SOC1 [Besides SPLs, GA signaling contributes to flowering transition by regulating the expression and activity of some MADS-box TFs in different manners . For exae action . Moreove of SOC1 ,221.FT, and WRKY71 also binds to LFY, although it is not clear if its TF activity depends on GA signaling [MIR172B, while WRKY13 and SPL10 repress it [FUL expression directly and SOC1 indirectly [Also, DELLA proteins inactivate some of the WRKY TF family members implicated in flowering. WRKY75 and WRKY71 are direct regulators of ignaling ,223. WRKpress it . Both ofdirectly . Subsequdirectly .SOC1 and FT [SOC1 expression [GA20OX2. Thus, by lowering the repressor activity of SVP, GA levels rise, reinforcing flowering transition [XAANTAL2 (XAL2) is another member of the MADS-box family involved in flowering, probably in response to GA and independently of SOC1, since the double mutant xal2-2 soc1-7 was unable to flower in response to GA3 treatment after 88 days under SD conditions [It has been proposed that FUL can also counteract FLC flowering repression by competing for the association with SVP. As said previously, FLC and SVP repress 1 and FT ,54,55. Hpression . Furtheransition . SOC1 anansition . Finallynditions .LFY expression [LFY expression by an independent mechanism. MYB33 accumulates in the shoot apex in response to GA4 addition [LFY promoter. Hence, when this region is mutated, LFY expression is severely reduced under SD photoperiod [GAs regulation of MADS-box genes leads to the induction of pression ,227,229.addition . Furthertoperiod .Arabidopsis and other species generally accelerates flowering, although the effects may vary depending on the sugar concentration and the plant’s developmental stage [FT and its closest homolog TSF in a CO-independent manner [SWEET 10 in the phloem companion Cells which is thought to be important for sugar export to the shoot apex [TPS1 is highly expressed in the IM, and its overexpression reverts the late-flowering phenotype of ft-10, suggesting that T6P acts independently or downstream of FT regulation [The carbohydrates were long considered to be involved in the vegetative to reproductive transition ,232. Indal stage ,183,233.al stage . T6P is al stage . T6P cast manner . In retuoot apex . Additiogulation .SPL3/4/5 at the SAM in a partially independent manner of miR156 decreasing by aging [hxk1 mutant in response to glucose [Under SD photoperiod, T6P positively regulates the expression of by aging . Howeverby aging ,130,235. glucose .The close relationship between SPL and MADS-box TFs, as well as their response to endogenous and environmental cues during plant’s phase transitions, strongly suggest that they are part of the same gene regulatory network . MoreoveA. thaliana flowers under long-day photoperiod during spring and summer [Day length and high permissible temperatures are important signals to induce flowering, particularly for those plants that grow in latitudes where there are significant changes in photoperiod and temperatures throughout seasons. d summer .CO’s mRNA is expressed in circadian cycles having its maximum accumulation levels around 16 h after the first light and dawn when Arabidopsis is grown under LD photoperiod [CO’s repression by CYCLING DOF FACTORs (CDFs) during the morning and the degradation of these factors in the late afternoon. The F-box E3-ubiquitin ligases FLAVIN BINDING, KELCH REPEAT, F-BOX1 (FKF1), and ZEITLUPE (ZTL) are photoreceptors, which in association with GI, target those CDFs for their degradation [CO daytime expression [CO expression in association with TEOSINTE BRANCHED 1/CYCLOIDEA/PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR 4 (TCP4) [CO expression [Detection of photoperiod relies primarily on CO protein, a B-box-type zinc finger TF with a CCT domain, that accumulates during the day in the vascular tissue ,238. CO’toperiod . This osradation ,242,243.pression . GI itsepression ,245 that4 (TCP4) . Additiopression .CRY2, are early flowering at 23 °C [At the posttranslational level, COP1 and SUPPRESSOR OF PHYA-105S 1 (COP1/SPA1) complex ubiquitinates CO protein to be degraded by the proteasome at night ,250,251.at 23 °C ,256. On at 23 °C ,257,258.at 23 °C .FT and SOC1 [Interestingly, complex interconnections between GI, ZTL, and FKF1 proteins, shape CO protein accumulation during the day. GI-ZTL downregulates CO protein levels, while GI-FKF1 stabilizes them. Moreover, GI prevents ZTL-FKF1 union, favoring GI-FKF1 complex formation. These complex regulations lead to high CO protein levels in the late afternoon in LDs but not in SD ,261. Furand SOC1 ,262. Addand SOC1 .FT expression by binding to two CO-responsive elements (CORE) in its promoter [FT is translated in the companion cells of vascular tissue, and the protein constitutes a signal that travels from rosette leaves to the SAM to induce flowering [CO induces promoter ,264. FT lowering ,266. Thelowering . FT assolowering ; next, Flowering   and Landsberg erecta (Ler) flower earlier when grown at 25–27 °C compared to 23 °C in SD photoperiod [ft-10 mutant is insensitive to warm temperature, showing that FT mediates flowering thermal response independently of LD photoperiod [In nature day length and temperature are two factors that usually go in the same direction. When winter ends and days become longer, the temperature also rises. Therefore, it is not surprising that warmer temperatures act as an inductive flowering signal in operiods . Many A.toperiod . Moreovetoperiod .FT and TSF expression in response to high temperature [FT locus, relaxing the chromatin and favoring the union of PIF4 to FT DNA [PHYTOCHROME INTERACTING FACTOR 4 (PIF 4) and its orthologs PIF5 and PIF7 are responsible for inducing perature ,288,289.o FT DNA .FT [FT [Red-light induces the phyB active Pfr state which promotes CO and PIF4 degradation, while a phenomenon called thermal reversion promotes fast change from the Pfr state to the Pr inactive state when temperature increases. This event allows both CO and PIF4 to induce FT ,290,291 FT . Since DFT [FT .Arabidopsis accessions variability to flowering in response to thermal induction could be explained (at least in part) by genetic variation in those alleles [Noteworthy, FLM is required for thermal induction, in contrast to FLC that partially suppresses it. Thus,  alleles . It has  alleles ,292. Mor alleles .The evidence suggests that LD photoperiod and warm temperature signaling can be separated, but more research is required to establish the latter’s influence when plants grow under LD photoperiod.A considerable effort has been made during decades to understand how plants regulate flowering transition in response to different seasons and changing climate conditions. The characterization of mutants that show early or late flowering phenotypes under specific growing conditions and their genetic relationships led to the genetic pathways’ classification. Although this approach is experimentally essential, the information summarized in this review highlights that the complex genetic network that underlies the transition to flowering transcends the genetic pathways.Arabidopsis, in part, by upregulating FT in the leaves and a group of the SPLs and MADS-box genes in the apical meristem. This ensures that flowering happens when the external conditions are optimal for those species. Although the relevance of FT and SOC1 as flowering inducers is indisputable, there is current evidence that they are not the only ones that regulate LFY and AP1 (The actual hierarchical flowering model proposed that different inputs converge into the integrators that transduce these signals to the FMI genes . Alterna and AP1 , supportFLC and other flowering repressors [Different regulation levels are relevant to establish the network’s developmental phase changes, including the epigenetic, transcriptional, posttranscriptional, and posttranslational regulation. At present, there is detailed information about some processes, while it is very little on others. With the evidence summarized here, it can be said that epigenetic regulation is important to maintain the vegetative phase by repressing the flowering inducers and, it is essential in flowering promotion by repressing pressors . On the pressors . Likewispressors ,295,296.pressors ,300,301.pressors ,291.Despite our knowledge in the regulation of flowering, there are processes left to be uncovered. For example, it is still to know the signal transduction triggered by T6P, the effect of vernalization in a broad context, the possible signaling of photoreceptors in the apical meristem, and their activity as thermoreceptors. It is also necessary to continue studying how MADS-domain proteins associate in complexes whose combination affects their function ,306,307.FLC, FLM, and some circadian-cycle genes are fundamental for the adaptation of flowering time to different environments [Arabidopsis and other species will also expand our knowledge on common and divergent mechanisms on flowering regulation [Furthermore, there is much to learn from studies on natural variation, which have shown that ronments ,309,310.gulation ,312.Finally, it would be important to continue implementing theoretical models to integrate the flowering information to infer regulations that cannot be easily detected. In this respect, different models have been developed ,314,315.


Despite an initially indolent course, all WHO grade II, LGGs inevitably transform to malignant, WHO grades III and IV, without current curative options. Malignant transformation (MT) remains unpredictable with limited prognostic markers to steer timing of interventions. The aim of this study was to review and assign predictive value to specific clinical, molecular, and radiological markers impacting MT, thereby justifying timely therapeutic interventions.Searches of MEDLINE, Embase, and Cochrane databases were conducted from inception to April 28, 2021 and outputs were analysed in accordance with PRISMA protocol.From an initial 5,032 articles, 33 articles were included, totalling 5672 patients. Forty-three prognostic factors were registered to significantly impact MT. These were categorised as 7 clinical; 14 neuroimaging; 8 biological/molecular; 3 volumetric; 5 topological; 3 histological; and 3 treatment-related. Following analysis, 10 factors were highlighted: the pre-operative prognosticators were 1. presentation with epileptic seizures; 2. VDE > 8 mm/y; 3. VDE > 4 mm/y; 4. rCBV > 1.75; 5. PTV ≥ 5 cm (65 ml); 6. PTV ≥ 100 ml; and 7. cortical involvement. The post-operative prognosticators were: (1) IDH-wt, (2) TP53 mutation, and (3) temozolomide monotherapy.The management of LGGs remains controversial, as conservative and invasive treatment may be associated with MT and impaired quality of life, respectively. Our review indicates that MT can be predicted by specific metrics in VDE, PTV, and rCBV, alongside cortical involvement. Additionally, patients with IDH-wt tumours TP53 mutations, or receiving TMZ monotherapy are more likely to undergo MT. Our data may form the basis of a predictive scoring system. MT of LGGs remains unpredictable with limited prognostic markers.We identified 43 distinct markers significantly impacting MT and ten were highlighted.Routine neuroimaging and clinical data, may identify higher risk cohorts justifying early intervention.Malignant transformation of LGGs remains largely unpredictable with prognostic markers limited. No practice guidelines or direction for timing of interventions presently exist. Our aim was to systematically review, identify and assign prognostic weight to specific clinical, molecular, and radiological markers impacting MT in LGGs. Analysis of the 33 qualifying articles, totalling 5672 patients, identified 43 prognosticators significantly impacting MT and 10 prognosticators were highlighted: (1) presentation with epileptic seizures, (2) VDE > 8 mm/y, (3) VDE > 4 mm/y, (4) rCBV > 1.75, (5) PTV ≥ 5 cm (65 ml), (6) PTV ≥ 100 ml, (7) cortical involvement, (8) IDH-wt, (9) TP53 mutation, and (10) TMZ monotherapy. To our knowledge, this is the first systematic review aiming to prognosticate categorical factors, based on both post-, and more importantly, pre-operative factors. Our results indicate that neuroimaging and clinical data, may identify higher risk LGG patients, justifying early invasive interventions. Although, not a primary aim, a scoring system may be introduced.1–6 Patients harbouring LGGs can continue to work and perform well for considerable periods of time, often years, without treatment and minimal radiological progression, providing a false sense of security, as the tumours progress unpredictably but, invariably, to malignant variants.7World Health Organisation (WHO) grade II supratentorial low-grade gliomas (LGGs), are generally slow-growing, infiltrating primary brain tumours, however, they can also constitute an ultimately and uniformly fatal disease of, usually, fully functioning young adults presenting with a degree of neuro-cognitive decline (mean age 41 years) with overall survival (OS) averaging between 5 and 15 years.8 with an incompletely understood natural history ranging from indolent to biologically aggressive behaviour, resulting ultimately in neurological decline and death secondary to malignant transformation (MT).9–13 In addition, compared to its 2007 predecessor, the 2016 update of the WHO classification of CNS tumours has included molecular features with histology to create an integrated diagnosis.14 Despite the discovery of several biomarkers such as mutations in the isocitrate dehydrogenase (IDH) genes 1 and 2, in combination with ATRX loss or 1p/19q co-deletion, and very recently, the additional validation of the relevance of CDKN2A/B homozygous deletions, representing remarkable milestones in stratifying LGGs, an objective, reproducible and prognostically relevant classification remains elusive.15LGGs compose a heterogenous group of tumours with distinct molecular, clinical, and histological features16 highlighting the variability of MT and potential multifactorial contributions to a catastrophic event. The vast majority of LGG studies focus on general prognostic factors of survival, mainly devised before the 2016 update of the WHO classification on CNS tumours, including eloquent location, Karnofsky performance score (KPS) > 80, age < 50 years, or tumour diameter < 4 cm, confirmed with Cox proportional hazards modelling or, alternatively, loosely defined progression outcomes which do not necessarily equate to MT.17The reported frequency of LGG MT ranges from 25% to 72% in the published literature18 Although a number of factors have been reported to be associated with MT including preoperative tumour size,19 velocity of diametric expansion (VDE),21 astrocytoma histology,9 and extent of resection23 they have not yet been studied in a systematic way.Understanding the non-linear, unpredictable process of MT is critical to planning therapeutic interventions, as resective surgery or radiotherapy may be associated with neurological morbidity in a typically highly functioning cohort of patients.In the current systematic review, employing a strict definition of MT and minimising the biases of false positive results, we aim to comprehensively and critically appraise the modern literature extracting all relevant metrics of MT, thereby presenting the first systematic review of the literature, producing clinical, molecular and radiological factors predictive of MT in LGGs.24–26The systematic review was conducted in accordance with the PRISMA  guidelines, Cochrane Methods Prognosis Group's review template, and Riley's guide to a systematic review and meta-analysis of prognostic factor studies.Prospective and retrospective original studies investigating prognostic factors for MT in LGGs, written in English, were included. Studies investigating prognostic factors in cell lines/xenograft models were excluded. Case reports, reviews, conference abstracts, and editorials were also excluded.27–29Age threshold was set to adult and adolescent patients (≥15 years of age) reflecting a dichotomy in paediatric and adult services. Mixed adult and child (<15 years) populations were included if adult cohorts could be analysed separately. Diagnoses included were WHO grade II gliomas . Studies with pilocytic astrocytomas, gangliogliomas, and ependymomas were excluded as typically belong in WHO grade I tumours.The outcomes of MT and reported prognosticators were recorded. The aim was identification of high-impact MT markers with potential of validation and further assessment in future studies.To account for disparities in MT definitions in the literature and ensure reproducible MT interpretations, a strict definition was applied, as the progression of a WHO grade II tumour  to a higher WHO grade III or IV tumour  confirmed histologically by surgical specimen or radiologically as new/increased contrast enhancement on T1 weighted MRI scan after the administration of gadolinium.Electronic searches of Ovid MEDLINE, Embase, and Cochrane library databases were conducted from the inception of each database to April 28, 2021. Full details of the search protocols are provided in the All search results were assessed for eligibility. Initially, records were examined by title and abstract while in the second round, full text retrieval and review were employed. Qualifying studies were included in the systematic review. Results of the literature search were imported to EndNote X9 . Software was used to reduce data entry errors and to deduplicate search results. Any further duplicates found during screening were manually excluded. Data recorded in a Microsoft Excel spreadsheet included: author, publication year, and journal citation; patient inclusion and exclusion criteria; study design; study population; tumour details at diagnosis ; length of follow-up; prognostic factors investigated; rate of MT; significant association between factors of interest and MT; other key results; definition of MT adhered to by the study.31 The criteria list was adjusted to establish criteria for follow-up and drop out percentage.32 Each criterion was scored with “yes,” “no,” or “don’t know,” which led to the overall scoring of low, moderate, or high risk of bias for the following 6 domains of potential biases: (1) study participation, (2) study attrition, (3) measurement of prognostic factors, (4) measurement and control for confounders, (5) measurement of outcomes, and (6) analysis  tool with a list of considerations.analysis . All criThe electronic search yielded a total of 6009 abstracts. After deduplication, 4314 abstracts were screened by title and abstract for eligibility. In accordance with the inclusion criteria, 4637 records were excluded, and 323 publications were flagged for full-text review. Following a full-text assessment of each record, a total of 33 articles were identified for the final data extraction. Details outlining the reasons for exclusion and full flow of information, in accordance with the PRISMA format, are presented in molecular/biological, 8 prognosticators; radiological/imaging, 14 prognosticators; clinical, 7 prognosticators; tumour volumetry, 3 prognosticators; topological/anatomical, 5 prognosticators; histological, 3 prognosticators; treatment-related, 3 prognosticators  age > 45 years in two studies35, and >35 years in one study,36(2) male gender in two studies,37 (3) increased intracranial pressure (ICP) at diagnosis, in two studies,38 (4) neurological deficit at diagnosis in two studies,34 (5) duration of pre-operative symptoms >2 years in one study,34 and (6) KPS ≤ 70 in two studies.35History of epileptic seizuresP <.001), independent prognostic factor of delayed MT, with MT occurring from diagnosis at a mean time of 65.1 ± 54.8 and 39.5 ± 28.3 months, in subgroups with and without epileptic seizure at diagnosis, respectively. Interestingly, the same study reported that the probability of seizures was not affected by tumour volume or growth velocity, cortical location, and histological or molecular subtyping.33In a retrospective multi-institutional observational study involving 1509 patients, history of epileptic seizures at diagnosis was a statistically significant  velocity of diametric expansion (VDE) ≥ 8 mm/y38 with lower VDE of >3mm/y in one study,41 (3) volumetric difference between preoperative tumor volumes on T2- and T1-weighted MRI studies (∆VT2T1) > 30 cm,43 (4) presence of contrast enhancement on MRI/CT,44 (5) low apparent diffusion coefficient (ADC),39 (6) high normalised tCr (creatine/phosphocreatine) in magnetic resonance spectroscopy (MRS),44 (7) high mean and maximal choline/creatine ratio in MRS,41 (8) fluorescence with five-aminolevulinic acid (5-ALA),45 (9) tumour growth in 6 months interval scanning,40 (10) mean18F-FET (O-(2-18F-fluoroethyl)-L-tyrosine) uptake >1.1,46 (11) early tumour recurrence (within 2 years of primary surgery),47 and (12) high velocity radiological progression .47Twelve negative prognosticators included (1) high regional cerebral blood flow (rCBV) in three studies,P < .001). Furthermore, MFS was significantly longer in patients with VDE < 4 mm/y than those with VDE ≥ 4 mm/y (P < .001). Likewise, patients with VDE ≥ 4 and <8 mm/y had significantly longer MFS than patients with VDE ≥ 8 mm/y (P < .001), and those with VDE ≥ 8 and < 12 mm/y had significantly longer MFS than with VDE ≥ 12 mm/y (P =.044). Of note, the VDE was significantly slower in tumors with 1p19q codeletion (P =.008) and with complete 1p deletion (P = .042) and was significantly faster in tumors with p53 overexpression (P = .003).20 Another study of 168 patients demonstrated that VDE ≥ 4 mm/y, VDE ≥ 8 mm/y, and VDE ≥ 12 mm/y all statistically conferred significantly shorter MFS compared to tumours with VDE < 4 mm/y . Interestingly, subventricular zone (SVZ) involvement predicted high VDE in the same study: patients with SVZ involvement (7.16 ± 6.53 mm/y) had a significantly higher VDE than patients without (4.38 ± 5.35 mm/y) (P = .003).21In a retrospective study of 380 patients, fast VDE (≥8 mm/y) was an independent prognostic factor, significantly associated with reduced malignant progression free survival (MFS), with the mean time to MFS being significantly longer in the slow subgroup (<8 mm/y)  compared to the fast subgroup . Additionally, the study showed that a threshold of rCBV = 1.742 was of optimal sensitivity (61.9%) and specificity (83.3%) in differentiating the group of patients with progression from the progression-free group.42 In another prospective study of 34 patients, the risk of MT was 1.75× higher per each additional standard deviation (SD) of rCBV at study entry . Interestingly, in the subgroup of pure astrocytomas (n = 20) this effect was heightened as the risk of MT was 12.99× higher per SD of rCBV at study entry .40 Finally, 2 further studies involving 7839 and 21 patients,41 reported high rCBV, defined as increased rCBV compared to the contralateral normal white matter, to have a negative prognostic effect on MT. A circumscribed tumour on MRI46 and local recurrence location47 had a positive prognostic effect.The effect of rCBV on MT was demonstrated in 4 studies. In a case-series prospective study of 63 patients, high rCBV (>1.75) was found to be independently associated with shorter MFS; 45 (2) p53 overexpression,49 (3) TP53 mutation,51(4) triple combination of IDH-mutated/MGMT-methylated/TP53 positive,52 (5) positive vascular endothelial growth factor (VEGF) staining,35 (6) microvessel density >7 microvessels,35 (7) Ki 67 labelling index over expression,48 and (8) intact 1p/19q.53 The positive and negative prognostic effects of 1p/19q codeletion were confirmed by different study groups and not by reverse assumptions.Seven factors were negative prognosticators and included: (1) IDH1 wild-type (wt),P < .001), with the 5-year estimates of MT delay of 82% for IDHwt and 92% for IDHmut/codel tumours. In the same study, patients with IDHwt tumours were at a 5.5-fold increased risk of MT.37 In a further study involving 74 patients, IDHwt was a significant poor prognostic factor for MT with MFS being significantly shorter in IDHwt tumors  than in IDHmut tumours  (P = .043) and was associated with around a 3-fold higher risk of MT.45In a retrospective cohort study of 486 patients, IDHwt tumours were significantly more likely to undergo MT than IDH mutated and 1p/19q co-deleted (IDHmut/codel tumours) (P < .03).50 In a further study with 36 patients, TP53 was strongly and statistically associated with MT (P = .0344), specifically, 9 of 14 tumors (75%) harbouring TP53 mutations showed MT within 12 ± 75 months (median 37 months), compared to 9/22 tumors (41%) wild type TP53 tumours.51 Only 1p/19q co-deletion had a positive prognostic effect on MT.54In a retrospective study involving 159 patients, positive TP53 mutation status (but not P53 overexpression) was the lone risk factor with respect to MT  and size were a negative prognosticator in both pre-operative MRI scans, and post-operative residual volume, when surgery was performed, with a greater extent of resectionP = .03). Specifically, tumours ≥ 3 cm had a 2.6-fold increase in undergoing MT.9 Another study with 74 patients, also found tumour size >3 cm to be statistically significant for freedom from MT (P < .05).35 In a retrospective study of 353 patients, tumour size ≥ 5 cm was a statistically significant, independent prognosticator for MT (P < .001), with 3.5-fold higher risk for tumours of this size.37 A further study of 148 patients revealed tumours > 5 cm  to be a significantly associated with worsened MFS (P = .047).34A retrospective study involving 191 patients, tumour size of the largest tumour dimension ≥3 cm was an independent factor associated with increased risk of MT and was found to have the greatest statistical significance compared to other parameters investigated in the study  and MT was supported extensively in the literature but without setting specific thresholds.56Tumour volume (TV) prognostication was reported in several studies but with three different thresholds of >20 mlP = .01).36 A study of 62 patients found tumour volume of >60 ml at diagnosis to be strongly predictive of increased MT risk (P < .001).53 Finally, a threshold of ≥100cm3 of tumour volume at diagnosis was demonstrated to significantly impact MT in 2 studies. The first study involving 1509 patients found this to be an independent prognostic factor for worsened MFS (P = .007),33 the second study, consisting of 380 patients also found this to be a significant factor (P = .008), associated with a 1.76-fold increase in MT risk.20 Five studies reported a statistically significant link between greater preoperative volume (cm3) and increased risk of MT, in a sum of 539 patients across all 5 studies.56In a long-term retrospective study of 239 patients, pre-treatment tumour volume of >20 ml was significantly associated with increased risk of MT , either in absolute post-operative TV volumes43 or in relation to original TV (EOR ≥ 90%).47 Similarly, gross total resection (GTR) conferred a positive prognostic effect.57 Furthermore, first line surgical resection compared to surveillance20 partial resection compared to biopsy34 and subtotal resection also compared to biopsy33 were all found to have a positive prognostic effect. Similarly, a postoperative residual tumour volume of ≤5 ml resulted in delayed MT compared to greater residual volumes.58 The converse was also confirmed in different studies, with watchful waiting compared to resection59 and smaller EOR42 having a negative prognostic effect on MT.Studies reporting TV in post-operative settings either established a threshold of >30 ml,21 (2) parietal tumour location,38 (3) presence of cortical involvement,33 (4) eloquent tumour location,34 and (5) multilobar involvement.56All the following five identified factors appeared to be associated with MT: (1) SVZ involvement,P = .004).33 In a retrospective study involving 168 patients, SVZ involvement predicted a significantly shorter MFS (P = .033) and was independently associated with higher VDE (P = .003).21 The link between eloquent tumour location and MT was reported in 2 studies involving 148 patients and 216 patients, where it was shown to be significantly associated with worsened MFS (P < .001 and P = .006).34The presence of cortical involvement was shown to be an independent negative prognosticator for MT in a retrospective study of 1509 patients (43 (2) pure astrocytoma,53 and (3) gemistocytic astrocytoma.53 In a study of 190 patients fibrillary astrocytomas were significantly more likely to undergo MT than oligodendrogliomas or oligoastrocytomas, with the associated risk being 3.2-fold higher in these tumours (P = .003).43 In a further retrospective study involving 191 patients undergoing resection, fibrillary astrocytoma pathology was an independent negative prognostic factor for MT (P = .04).9Three histological subtypes were identified to be prone to MT: (1) fibrillary astrocytoma,33 radiotherapy (RT),43 and adjuvant chemo-radiotherapy54 all retarded MT. In accordance with these results, CT monotherapy (vs. RT followed by adjuvant CT)37 was found to have a negative prognostic effect on MT. However, in a retrospective study involving 472 patients, temozolomide (TMZ) monotherapy was a statistically significant and independent negative prognostic factor for MT (P = .08) when compared to patients who received both CT and RT. Interestingly, in the same study patients with IDHmut 1p/19qcodel tumours, which was the subgroup at lowest risk of MT, were more likely to be treated with adjuvant TMZ alone (P < .001).37Finally, treatment with chemotherapy (CT),According to QUIPS assessment tool, 26 of the 31 included studies were rated as high quality, meaning that the risk of bias was deemed as low or moderate across all 6 of the domains considered. Of the studies that were considered of low quality, 3 out of 4 of these were due to high risk of bias in the confounding factor domain. All studies had a low risk of bias in the study participation and outcome  domains. The results of the quality assessment are presented in 61Malignant transformation represents a critical and irreversible event in the course of LGGs, and the inability to predict its occurrence on a linear timeline renders timing of therapeutic interventions uncertain or, even, arbitrary. Studies balancing MT predictability, on preoperative data, are extremely sparse in the literature. To our knowledge, this is the first systematic review aiming to prognosticate categorical factors, based on both post-, and more importantly, pre-operative factors. In addition, recent molecular prognosticators render the group of LGGs challenging to precisely define. For example, IDH-wt mutations in previously defined WHO grade II gliomas tend to be treated as glioblastomas, although growing evidence suggests that this is an inhomogeneous group, that needs to be further stratified.Based on review of 31 articles, out of 3808 reviewed abstracts, totalling 5193 patients, the current study has identified a total of 43 distinct, prognostic factors, spanning 7 categorical domains, with significant impact on MT in LGGs. The impact of the 43 factors was evaluated based on (1) statistical significance, (2) cohort size per study, (3) study quality, and (4) practical applicability, which led to the emergence of 10 prognostic factors, subdivided into 7 pre-operative, and 3 post-operative prognosticators, based on availability of histological and molecular analysis following surgical intervention. Five of the highlighted factors were described as binary (present or absent) and 5 were categorical, grouped by numerical thresholds. The pre-operative prognosticators were (1) presentation with epileptic seizures, (2) VDE > 8 mm/y, (3) VDE > 4 mm/y, (4) rCBV > 1.75, (5) PTV ≥ 5 cm (65 ml), (6) PTV ≥ 100 ml, and (7) cortical involvement. The post-operative prognosticators were (1) IDH-wt, (2) TP53 mutation, and (3) TMZ monotherapy . It is e62 while VDE ≥ 12 cm/y are infrequently encountered, setting two accepted thresholds at ≥4 mm and ≥8 mm/y, with the latter weighing worse prognostication. In addition, the presence of SVZ involvement appears to compound VDE and initial tumour volume appears to compound VDE.62Two parameters were identified recurrently in numerous studies, with varied numerical thresholds and levels of significance. The velocity of tumour growth or VDE appeared in four studies, with thresholds at ≥4 mm/y, ≥8 mm/y, and ≥12 cm/y. Incidentally discovered LGGs were found to grow 2.93 mm/y,54 For example, Smith et al reported that a minimum EOR of >90% of original volume is required to produce survival benefit and, more recently, absolute residual tumour volumes stratified between 0 cm3; 0.1–5.0 cm3 and >5.0 cm3 were associated with, consecutively decreasing survival benefit, for each group.22 Also, in a “near-randomised” trial, Roelz et al reported that survival benefit was recorded in patients with residual tumour volume of <15 cm3 and patients, in their series, where this threshold was not reached, fared similarly to the biopsy only group.63 Finally, accounting also for molecular subtyping, a recent large retrospective trial showed that any residual postoperative volume affected negatively the OS, even if the residual volume was only 0.1–5.0 cm3 regardless of the tumour's molecular profile.64 Nevertheless, these data refer to post-surgery volumes and not to the risk of MT in cohorts of patients that are followed up with serial imaging or post stereotactic biopsy.The significance of tumour volumetry appears in keeping with EOR studies examining PFS and OS in surgical series.35 and for the latter >20 ml, >60 ml, and >100 ml.53 An older, 2002 EORTC study, based on 288 patients identified a threshold of ≥6c m as an unfavourable prognosticator.65 Not significantly deviating from this original observation, our analysis suggests a PTV of ≥5 cm was an independent MT prognosticator (P < .001)37; extrapolating the findings and converting radius to a volume with the formula V = (4/3)πr, indicates that a PTV ≥ 100 ml is a clear MT prognosticator, although the significance of lower thresholds cannot be disputed.However, multiple studies have shown that pre-operative volume, despite inconsistent definitions, in centimetres of maximum diameter or three-dimensional volume in millimetres, are distinct MT prognosticators. Numerical thresholds for the former definitions included ≥3 cm, and ≥5cm42 The effect of rCBF on MT may be predictable, as for every SD of rCBF the risk of increased MT was estimated ×12.99.40 In addition, cortical and SVZ involvement were both independently associated with MT .The quantification and definition of increased rCBF compared to contralateral white matter varies across published studies but has been linked to MT in four studies. A threshold of rCBF = 1.742 appears to offer the best combination of sensitivity and specificity at 61.9% and 83.3%, respectively.66 has been identified as a positive prognosticator in a number of studies, including a multi-institutional observational study confirming delay of MT (P < .001).33 The grade of tumours appears to be inversely related to incidence of seizures with grade I tumours such as dysembryoblastic neuroepithelial tumours (DNET) and gangliogliomas having an incidence of 80–100%, LGGs 60–85%, and HGGs a lower rate of 40–60%.67 It is likely that the destructive rather than irritative growth process in HGGs confers lower epilepsy incidence. To that end, oligodendroglial histology, conferring better prognosis compared to astrocytic one, also is associated with higher risk of epilepsy.68 Alternatively, seizures may trigger the earlier identification of the tumour resulting in a greater lead time to MT.Epileptic seizures, a common presentation in most patients with LGGs,P < .03).50 In addition, the triple combination of IDH mutation/MGMT methylation/TP53 confers a negative prognostic effect. Interestingly, although IDH mutation is associated with longer OS, the triple mutation, had significantly higher hazard to MT compared to IDHwt (P = .0452).52 In addition, positive and negative prognostication conferred by 1p/19q co-deletion, were independently confirmed with no reversed assumptions.54Following molecular analysis of surgical specimens, our review identified a series of seven negative prognosticators: in addition to previously well-described IDHwt, Ki 67 labelling index over-expression, and positive VEGF, the cancer-protecting TP53 gene, either overexpressed or mutated, is also significant negative prognosticator in LGGs  genes, resulting in the accumulation of hypermutations, has been proposed.65 Six years later the San Francisco group based on a series of 281 patients harbouring LGGs introduced a four-factor system scoring age >50 years; KPS < 80; presumed eloquent location; and maximum diameter > 4 cm.68As the growth rates, biological behaviour, and malignant transformation points of LGGs contain paucity of data, a number of scoring systems attempted to stratify hazards of poorer outcomes and early interventions were proposed. In 2002, Pignatti and colleagues used an EORTC database to score LGGs in five categories: age ≥ 40 years; astrocytoma cytology; tumour diameter ≥ 6 cm; tumour crossing the midline and presence of neurological deficit.The evolution of molecular data and neuroimaging modalities as well as the accumulated experience of the last two decades resulted in accumulation of valuable data in the literature that the current study attempted to analyse and critically interpret. Although it is not our aim to propose a new scoring system, future efforts may include the 10-factor list, with weighing based on quantitative thresholds. For example, VDE > 4 mm/y and > 8 mm/y would add one and two points respectively, as this factor is categorical and not binary. Similarly, PTV ≥ 65 ml and PTV ≥ 100 ml would add one and two points respectively. Conversely, the presence of epileptic seizures would detract one point. However, this would remain a theoretical frame, and its validation is beyond the aim of this systematic review.Consequently, an initial, proposed classification scheme for LGGs MT risk stratification is included , divided“physicians must approach each case individually and weigh the risks and benefits of each intervention until further evidence is available”,72 and that the timing of intervention could be weighed against the estimated risks of MT. The current systematic review offers a quantitative and measurable prognosticator system.Currently, no practice guidelines exist as to the ideal management of low-grade gliomas. Two Cochrane totalling 4139 and 2764 citations concluded that 33 as such the reports may contain duplicated patients. Finally, the majority of the studies included lacked information on the glioma molecular subtype, limiting the analysis as the prognostic factors could not be analysed with respect to molecular subgroup. To that end, the definition of what constitutes as a LGG has also been redefined in light of the molecular era, which some older studies in this review failed to appreciate by not differentiating between astrocytoma, oligodendroglioma, and oligoastrocytoma, the latter of which is considered to be entirely redundant. The prognostic factors should be addressed with respect to molecular status in future studies.Limitations of our review included inconsistencies in definitions of MT across some studies, measurements of tumour volume, and quality of outcome measurements, although our critical analysis attempted to reconciliate such inconsistencies, where possible. Additionally, some studies reported data from the same patient datasets,LGGs do not follow a linear, predictable growth plot line, but display rather exponential intervals of accelerated, aggressive biological behaviour. Even when imaging appears to confer assurance to a static lesion, the background molecular changes cannot be displayed by current imaging modalities. The current systematic review has introduced 43 measurable, distinct, categorised prognosticators with numerical thresholds, and critically reviewed and weighted their importance. Although not the aim of this review, the analysed prognosticators can form the basis of a future, comprehensive scoring system.vdab101_suppl_Supplementary_MaterialsClick here for additional data file.