We aimed to determine the predictors of regression to normoglycemia and progression to diabetes among subjects with pre-diabetes in a single model concurrently.The present study included 1329 participants aged 20 to 70 years with prediabetes from the population-based cohort of the Tehran Lipid and Glucose Study, with a 10-year follow-up. Glycemic status at follow-up was categorized as regression to normoglycemia: fasting plasma glucose [FPG] of <5.55 and 2h-plasma glucose [PG] of <7.77 mmol/L, and not taking antidiabetic medications. Glycemic status at follow-up was categorized as progression to diabetes: FPG ≥7 or 2h-PG of ≥11.1 mmol/L, or taking antidiabetic medications. Glycemic status determined whether the patients remained in prediabetes category (isolated impaired fasting glycaemia [iIFG]  (7.77 ≤ 2h-PG<11.1 and FGP<5.55 mmol/L)]. With prediabetes as a reference, multinomial logistic regression was utilized to identify the determinants of glycemic changes.Approximately 40% of participants returned to normoglycemia (n = 578), and similar percentage of participants progressed to diabetes (n = 518). Based on the multivariable multinomial model, regression to normoglycemia was associated with age , female sex , high education level of ≥12 years , and combined IFG/impaired glucose tolerance (IGT) versus IFG . The risk of progression to diabetes increased with body mass index , waist circumference , positive familial history of diabetes , and combined IFG/IGT versus IFG .A small percentage of patients with prediabetes remain in this condition, but the majority go on to develop diabetes or regress to normoglycemia. Both directions had distinct predictors. Prediabetes is understood to be a critical metabolic stage in the onset of diabetes and its complications. In prediabetes, glucose levels are higher than normal but not yet at the threshold for diabetes. The number of people with prediabetes is rapidly rising in all countries around the world. In terms of disease burden, high fasting plasma glucose (FPG) ranked fifth in 2017. Globally, 352 million adults (7.3%) had prediabetes, and that number was projected to rise to 587 million (8.3%) by the year —the first community-based large-scale, long-term cohort study in Iran—was designed  in 1998.Each interview was conducted through a structured questionnaire to collect demographic data, education level, smoking status, medication use, family history of diabetes, history of cardiovascular disease (CVD), or family history of CVD. The mercury column sphygmomanometer was used to measure the systolic and diastolic blood pressure , and the mean of 2 consecutive measurements on the same arm after at least 5 minutes of seated rest in a chair was calculated. The standard measurement techniques were used to determine the body weight, waist sizes, and height. A venous sample was taken between 7:00 AM and 9:00 AM after 12 to 14 hours of fasting for laboratory testing, and all samples were analyzed in the TLGS research laboratory on the day of blood sampling. The details and protocols of the TLGS clinical measurements were published elsewhere  having diabetes , (2) normoglycemia (FPG <5.55 and 2h-PG<7.77 mmol/L and not taking antidiabetic medications), and (3) as prediabetes . If any participant’s first-degree relatives had type 2 diabetes, it was regarded as having a positive family history of the disease. Body mass index (BMI) was calculated as weight in kilograms divided by squared height in meters. Smoking status was categorized as follows: current, former, and nonsmokers. Furthermore, participants were divided into 3 groups based on their length of education: 0 to 5, 6 to 12, and >12 years. The outcome of our study was evaluated by whether patients developed diabetes or normoglycemia for the first time or maintained prediabetes during our follow-up. The event date was taken into account as the point at which the person first experienced normoglycemia or diabetes and last experienced prediabetes; for those without a normoglycemia or diabetes event, the most recent follow-up time was taken into account.P <.2 were included in the multivariable model— all variables were significant in one or both outcomes. The interaction of the selected variables with age and sex was assessed using the likelihood ratio test (LR test). Since the LR test was not significant, the interaction terms were not entered into the multivariable model. We also checked the interaction between type of prediabetes (IFG/IGT) and other predictors and did not find a significant interaction. BMI had a strong correlation with waist circumference (r = 0.78), thus,a sensitivity analysis was performed. Separate models for weight and waist circumference were developed. .Baseline characteristics were summarized as mean and standard deviation for continuous variables and frequencies (%) for categorical variables. The predictive mean matching method and a 5-time imputation with 50 iterations were used to perform multiple imputations for missing data at the baseline (up to 12.4% for different variables) and follow-up (up to 29% in separate examinations). One-way analysis of variance and chi-square tests were used to compare continuous and categorical variables between the groups. Multinomial logistic regression was performed to calculate the relative risk ratio (RRR) and 95% CI for the considered risk factors. First, a univariable analysis of potential predictors were performed that included age, sex, BMI, SBP, DBP, use of antihypertensive drugs, use of antihyperlipidemic drugs, positive familial history of type 2 diabetes, waist circumference, glycemic status, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), personal history of CVD, familial history of CVD, smoking status, and education level. For the next step, variables presenting We assessed 1329 people with prediabetes between 2006 and 2018, and the median follow-up time was 10 years .Baseline clinical characteristics and laboratory data according to transition status during follow-up are presented in We observed an age-related reversion to normoglycemia in the multivariable model. The regression probability decreases by 3% per year . Similarly, baseline combined IFG/IGT had a notable negative effect, and these participants had a 55% lower regression probability  compared with the iIFG participants. Women were 72% more likely to regress . Higher education level (≥12 years) was positively associated with regression to normoglycemia  Table 4.A higher BMI significantly increased the likelihood of developing diabetes from prediabetes. The progression probability increases by 10% for each BMI unit increase , whereas waist circumference had a negative effect on the progression to diabetes (0.97 [0.96-0.99]). The risk of progression was 62% higher for those with a positive family history of diabetes compared with those with a negative history . This predictor had a strong positive correlation with the development of diabetes, in contrast to regression to normal condition, which was inversely related to the combined IFG/IGT. Those with combined IFG/IGT were 2.5 times  more likely to develop diabetes than the participants with iIFG Table 4.As previously explained, due to the significant negative relationship observed between waist circumference and progression to diabetes, the researchers decided to investigate the correlation between waist circumference and BMI. They observed a high correlation, and as a result, sensitivity analysis was done. The relationship in the model containing BMI remained significant . Insulin resistance in subjects with IFG is due to increased hepatic insulin resistance while in subjects with IGT it is related to the increased insulin resistance in skeletal muscles. However, there is a strong association between increased insulin resistance in liver and skeletal muscles. In both kinds of pre-diabetes, insulin resistance combined with β-cell dysfunction would be responsible for the increased risk of type 2 diabetes. :193-9.)Diabetes risk is increased by both IFG and IGT, and it is increased by the two together more than by either one alone. This is consistent with the concept that any rise in glucose is not benign and reflects an endocrine pancreatic defect. The annual incidence of diabetes in people with IFG or IGT varied from 5% to 10%. Compared with normoglycemic people, the meta-analyzed relative risk and 95% CI for diabetes was 5.52 (3.13-7.91) in people with iIGT, 7.54 (4.63-10.45) in people with iIFG, and 12.13 (4.27-20) in people with both IFG and IGT . With thRegression to normoglycemia was more likely to occur in participants with higher education levels. Education level is associated with income, occupation, and physical activity. Education also improves the willingness to seek health information and encourages healthy lifestyle behaviors. The inverse association between education level and diabetes and obesity has been supported by previous studies , 27.In terms of possible clinical and public health significance of our findings, since identifying high-risk populations is considered a critical issue in diabetes prevention and intervention programs, pre-diabetes is an appropriate state in which high-risk individuals could be identified and followed for appropriate interventions. Therefore, identifying high-risk pre-diabetes people who progress to diabetes can help us carry out effective interventions to prevent diabetes, and even better control of these risk factors can increase the regression to normoglycemia.via imputation. Another limitation is the definition of diabetes and normoglycemia, which was determined by a single blood glucose measurement; however, this is common in epidemiological studies. The diagnosis of diabetes in clinical practice is based on at least two measurements of hyperglycemia and using one measurement in epidemiological studies makes the results unreliable. In our study the fluctuation of glucose level could be on both sides, i.e toward diabetes or normoglycemia, so although it may decrease the reliability of the results, a measurement bias is not plausible. Furthermore, although there is a growing body of evidence describing how the types of prediabetes are physiologically different, because of the low sample size we could not separate the analysis based on the type of prediabetes. Nevertheless, the likelihood ratio test did not show a significant interaction between the type of prediabetes and different predictors.The population-based longitudinal study design, multiple measurements from both clinical and paraclinical sources, including tests and questionnaires, repeated blood sampling, extensive follow-up, and use of an analysis that takes into account all outcomes simultaneously are the main strengths of our study. The loss of follow-up is a limitation in our study, as it is in any cohort study, which we tried to resolve The magnitude of regression to normal glucose levels was the same as progression toward diabetes. We did not aim to investigate the reasons why people with prediabetes progressed to diabetes and regressed to normoglycemia, however, we did demonstrate that different factors can predict these related outcomes. Factors associated with regression to normal glucose levels were age, sex, and education level, and factors associated with progression to diabetes were BMI and familial history of type 2 diabetes. The combined IFG/IGT had a notable significant relationship with both, which indicates the major determinant role for prediabetes transitions.In diabetes preventive and intervention programs, identifying high-risk people is thought to be a challenging task. It seems that prediabetes is a state in which high-risk populations should be identified, and essential interventions should be done. Identification of high-risk prediabetes individuals who go on to develop diabetes is crucial for effective diabetes prevention. Prediabetic individuals may progress to normoglycemia if these risk factors are better managed.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the ethics committee of Shahid Beheshti University of Medical Sciences . The patients/participants provided their written informed consent to participate in this study.The authors confirm contribution to the paper as follows: study conception and design: FH, FA, and DK. Data collection: FH, FA, and DK. Analysis and interpretation of results: ZA, KK, and DK. All authors contributed to the article and approved the submitted version.The main project has been funded by Shahid Beheshti University of Medical Sciences.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Schizophrenia Spectrum Disorders (SSD) and Autism Spectrum Disorders (ASD) are considered separate entities, but the two spectra share important similarities, and the study of these areas of overlap represents a field of growing scientific interest. The PANSS Autism Score (PAUSS) was recently developed specifically to assess autistic symptoms in people living with SSD reliably and quickly. The aims of the present systematic review were to provide a comprehensive assessment of the use of the PAUSS scale in available literature and to systematically analyze cognitive, functional and neurobiological correlates of autistic symptoms measured with this instrument in SSD. The systematic literature search included three electronic databases  as well as a manual search in Google Scholar and in reference lists of included papers. Screening and extraction were conducted by at least two independent reviewers. Out of 213 identified records, 22 articles referring to 15 original studies were included in the systematic review. Studies were conducted in several different countries by independent groups, showing consistent scientific interest in the use of the scale; most works focused on cognitive and functional correlates of ASD symptoms, but some also considered neurobiological features. Results of included studies showed that autistic symptoms in people with SSD are consistently associated with worse cognitive performance, especially in the social cognition domain, and with worse psychosocial functioning. However, the presence of autistic symptoms appears to also have a protective role, particularly on functioning, in subjects with more severe psychotic symptoms. Further exploring the impact of autistic symptoms could be of significant scientific and clinical interest, allowing the development of tailored interventions to improve treatment for people living with SSDs. Schizophrenia Spectrum Disorders (SSD) and Autism Spectrum Disorders (ASD) are currently considered two distinct entities. According to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), SSD belong to a different section with respect to ASD, which are described in the chapter detailing neurodevelopmental disorders . The eleThe two spectra are characterized by some remarkably different features, such as the age of onset, the course of the disorder, the response to treatment, and the fact that the presence of psychotic symptoms is not essential for a diagnosis of ASD; in particular, the age in which the first symptoms can be observed represents a very important difference in a clinical and diagnostic perspective. These distinctions are also associated with specific neurobiological and genetic characteristics, leading some researchers to theorize that SSD and ASD represent opposite models of neurobiological alteration .Although these distinctions are of clinical relevance, the two spectra also share many common features: in fact, the term “autism” was developed more than a century ago by Eugen Bleuler to describe one of the four essential aspects of schizophrenia, and only in 1943 with Leo Kanner it was associated with a distinct set of clinical and behavioral characteristics that could be observed in children, leading to the subsequent conceptualization of ASD .For instance, alterations in social interaction that can be observed in ASD are similar to schizophrenia's negative symptoms, and alterations in non-verbal communication are comparable to schizophrenia's social isolation; the absence of social and emotional reciprocity that is typical in ASD seems to match delusional patients' affective blunting, and the stereotyped language and behavior of ASD seem to recall schizophrenia's thought and behavioral disorganization –10.These observations are also supported by epidemiologic evidence. In a vast cohort of patients recruited by the National Institute of Health, 30% of young subjects with early-onset schizophrenia presented with a concomitant diagnosis of ASD .Moreover, several studies showed that subjects with a childhood diagnosis of autism are frequently diagnosed with a SSD during adolescence and early adulthood , 12–15.Some studies also observed that the presentation of early onset schizophrenia in younger patients, especially before the onset of hallucinations and/or delusions, is difficult to clinically differentiate from ASD , 17.Not only these disorders have common clinical features, but they also share important correlates in different cognitive domains: a recent study underlined that cognitive deficits measured with the MATRICS Consensus Cognitive Battery (MCCB) are present in both disorders and have similar characteristics . These rIn particular, the cognitive domain where important overlaps between SSD and ASD can be observed is the domain of social cognition: deficits in this area are a central characteristic of both disorders –22.A meta-analytic work including 19 different studies comparing social-cognitive performances in subjects with SSD and subjects with ASD, showed how social cognition deficits are similar in the two disorders: no significant differences in the Theory of Mind, emotional intelligence, and social skills tests were observed. Although subjects with schizophrenia spectrum disorders showed a better performance in the field of emotions' processing, this difference was modest .An even more recent work evaluated more comprehensively the social-cognitive performance in subjects with SSD, ASD and healthy controls, confirming that the level of social-cognitive impairment is very similar in the two disorders, showing minimal differences that became non-significant when corrected for symptom severity .Finally, different overlaps between the two spectra can be observed at a neurobiological level: if some important differences are present when considering neural network connectivity , 26 and From a genetic perspective, both disorders are often present as comorbid conditions in genetically determined neurodevelopmental disorders, such as in the 22q11.2 deletion syndrome, and in the SHANKk3 and locus 7q11.23 duplications of the Williams syndrome , 35.Additionally, many alterations in known loci were found to be associated to an increased risk of developing both disorders: among these there are SNPs, copy number variations and, more rarely, chromosomal anomalies, usually related to deficits in the cyto-architectural organization of the central nervous system –39.The gold standard scales for the diagnosis of an autism spectrum disorder in the general population are the Autism Diagnostic Observation Scale (ADOS)  and the The ADOS is a semi-structured observational scale, while the ADI-R is a specific structured clinical interview that is usually administered with the parents of the investigated subject. While these instruments have high validity, they are quite complex and lengthy to administer, and they are difficult to use to evaluate the autistic traits of subjects affected by schizophrenia, especially as reaching and interviewing with complex tools the parents of adults living with schizophrenia might not be considered practical in routine clinical contexts, and in some cases might not be possible at all . To addrTo structure the PAUSS scale, eight specific items of the Positive and Negative Syndrome Scale (PANSS)  correspoIn detail, the included items are: N1 “blunted affect,” N3 “poor rapport,” N4 “passive/apathetic social withdrawal,” N5 “difficulty in abstract thinking,” N6 “lack of spontaneity and flow of conversation,” N7 “stereotyped thinking,” G5 “mannerisms and posturing,” G15 “preoccupation,” with a total score ranging from 8 to 56. The scale can also be divided in three sub-scales, based on core dimensions of ASD: “difficulties in social interactions” , “difficulties in communication” (N5 and N6) and “limited, repetitive and stereotypic patterns of behavior” .The original validation study included a group of 1,156 patients diagnosed with schizophrenia and 256 controls diagnosed with other psychiatric disorders and with a suspected diagnosis of an ASD, 165 of which had the diagnosis confirmed during the study. The PAUSS scale showed a good convergence with the ADOS diagnosis, whereas other instruments (such as the Autism Questionnaire – AQ – and the Empathy Quotient – EQ –) didn't show similar characteristics.Therefore, the PAUSS scale represents an accurate and practical tool and, to this day, is the only validated instrument allowing to evaluate autistic symptoms specifically in people living with SSD.The aims of this systematic review are to obtain a global and comprehensive evaluation of the use of the PAUSS scale to measure autistic symptoms in people living with SSD, and to comprehensively evaluate the neurocognitive, socio-cognitive, clinical, therapeutic, genetic, neuroanatomical, molecular, and neurobiological correlates of the presence of autistic symptoms, when measured with the PAUSS scale.The main hypothesis of the present study is that the PAUSS scale, even if developed recently, has already been used in different studies from various research centers, and that there is a diverse literature allowing to define a variety of correlates of autistic symptoms.This systematic review was conducted following the Preferred Reported Items for Systematic Review and Meta-Analyses (PRISMA) statement, using its newest edition , 46.th, 2022, without time limitations. The following terms were used for the search: (schizophrenia OR “SSD” OR “psycho*”) AND (“PAUSS” OR “PANSS autism severity score”). Adaptations of the search strategy for the different databases are reported in the A systematic review of the available literature was conducted on 3 electronic databases  from April 19The inclusion criteria were defined through the PICOS Reporting System  as folloOutcomes of the present systematic were the correlates of autistic symptoms in people living with SSD measured with the PAUSS: data on neurocognitive, socio-cognitive, clinical, genetic, neurobiological and treatment correlates were all taken into account, including data from the scale validation studies.Two independent reviewers (NN and EI) assessed the reports and extracted the data; disagreements were resolved by a third author [GN. The Joanna Briggs Institute assessment for critical reviews , 48 was The results of the systematic search are reported in A total of 213 original records were identified. Sixteen articles, referring to 13 primary studies, were included through electronic database search. Six additional articles, of which 4 were referred to previously included studies, were included through manual search.At the end of the screening procedure a total of 22 papers referring to 15 studies was included in the systematic review.Eight studies were conducted in Italy, one in Germany, two in Spain, one in Norway, one in Scotland, one in the United States of America and one multicentric study included participants from Germany and the United Kingdom. The studies performed in Italy were ideated and performed by four independent groups.The patients' samples of the included projects were mostly small: all but four included <100 subjects.The larger studies were the original validation study for the PAUSS scale  which inA description of the main characteristics of included studies is reported in Results of included studies are summarized in Studies focused on the validity and on psychometric proprieties of the PAUSS had an overall high level of methodological quality.The initial validation of the PAUSS scale  was testp values < 0.00001, all coefficients positive, 16 correlations had a coefficient >0.4).The scale showed good internal consistency, with a Cronbach's alpha of 0.857 and Spearman's correlations being statistically significant among all items . Every item on the PAUSS scale showed a correlation with the total ADOS score (p < 0.00001) with a coefficient higher than 0.4; one item (N3) had a correlation >0.5 and 5 items  >0.6.The accuracy of the PAUSS was compared to the ADOS scale, and they were strongly correlated  and with autistic schizophrenia , respectively.A PAUSS score of 13.5 showed a 0.804 sensibility and a 0.680 specificity, whereas a score of 14.5 showed a 0.723 sensibility and a 0.711 sensitivity, setting the cut-off at 14 as the tipping-point between the two parameters. Then, based on the entire sample's scores' distribution, “extreme values” were set at 10 and 30, representing subjects without autistic traits  of the ADOS scale had an Area under the Curve (AuC) of 0.916, whereas the PAUSS scale's AuC was 0.824.A study by Deste et al.  confirmen = 14) presented with significantly higher PAUSS scores compared to subjects with a negative ADOS . When compared to subjects with a negative ADOS score, subjects positive at the ADI-R (n = 9) had similar characteristics, even though the PAUSS score in this group was yet higher, leading to a greater effect size of the comparison .Subjects with a positive ADOS  or ASD  were included. In the SSD group, the Cronbach's alpha of the PAUSS was 0.869. The PAUSS score was correlated with the ADOS-G score and the ADI-R scores, calculated through specific algorithms, and with the Social Responsiveness Scale .Another study  replicatThe results of all these studies homogeneously suggest that the PAUSS scale is a valid tool for the evaluation of subjects with a diagnosis of SSD: it is characterized by a good internal consistency and an optimal accuracy, making it as valid as more complex diagnostic tools.r = 0.095, p > 0.2), whereas the ARS emerged as significantly correlated to the positive dimension of the PANSS scale . This result, as commented by the Authors, suggests that the two instruments have essential differences that are based on the nature of the analyzed autistic characteristics  scores. The overall scores of the two scales were not significantly correlated . The score was negatively correlated with the ADOS score as well, but the correlation was weaker .In the original scale's validation study , the totp = 0.013, d = 0.61), vocabulary , arithmetic , similarities , picture completion , symbol search  and block design . Also, patients with autistic schizophrenia presented with a worse socio-cognitive performance, measured with the Facial Emotion Identification Test (FEIT) .In the 2018 study by Deste et al. , subjectvia the Emotion Recognition-40 (ER-40) test , and in the mental state attribution domain , measured through the Hinting Task  and The Awareness of Social Inferences Task .According to the analyses performed on the SCOPE study database (which included 361 participants diagnosed with SSD) , the sevn = 56, PAUSS < 10), subjects with intermediate autistic traits  and subjects with autistic schizophrenia . Significant differences between the three groups were found: subjects with more prominent autistic symptoms showed worse cognitive performance in the processing speed (p = 0.010), attention (p = 0.011), verbal memory (p = 0.035), and social cognition (p = 0.001) domains and in the global cognition index (p = 0.010).In the INRP study , which ip < 0.0001). These patients also showed a worse cognitive performance in the processing speed (p < 0.0001), executive functions (p < 0.001) and social cognition (p < 0.0001) domains.In a study including 97 participants with a diagnosis of schizophrenia , more sen = 23, PAUSS > 30), compared to other participants, all diagnosed with schizophrenia, had lower verbal IQ (p = 0.01), performance IQ (p = 0.01) and total IQ (p = 0.01). These patients also showed a worse cognitive performance in the domains of verbal memory (p = 0.02), working memory (p = 0.0005), processing speed (p = 0.03) and executive functions (p = 0.0005). Finally, these patients also showed a worse performance in the Picture Sequencing Task in the questionnaire score (p = 0.03), the sequencing score (p = 0.052) and the total score (p = 0.01).In another study by Bechi et al. , measurip = 0.89 vs. p < 0.0001; time x group effect p = 0.03, F = 4.57).Of particular interest are the results observed in this sample at the end of the cognitive remediation intervention: unlike other participants, subjects with autistic schizophrenia did not show a significant improvement in Theory of Mind abilities . Also, the group with the more severe autistic symptoms showed a reduction in the number of errors due to over-mentalization (p = 0.002).However, other studies suggest that the relationship between autistic symptoms and cognition could be more complex: in a study including 81 subjects with a diagnosis of schizophrenia or schizoaffective disorder , a combip = 0.003).Additionally, similar results were observed in a group of 29 patients affected by schizotypal personality disorder  : a high The results of these studies suggest that autistic traits, even if correlated to a worst cognitive performance, can also play a protective role on some cognitive abilities in subjects with more severe psychotic symptoms. Although promising, these results have to be considered preliminary in light of the small number of studies investigating this topic, the small size of recruited samples and the heterogeneity in the included diagnoses.Functional correlates of autistic symptoms represent another area of particular interest in the studies emerging from the systematic literature search. Studies focusing on functional correlates of autistic symptoms showed a high level of methodological quality.p < 0.01, g = 0.99), and at the HoNOS scale, with a moderate effect size .In a study by Deste et al.  publishep < 0.001, β = −0.189).In the SCOPE study, real-world functioning was measured with the Specific Level Of Functioning (SLOF) scale. In one of the articles illustrating the results of this study  more sevr = −0.40, p < 0.001), but also with a stronger bias in the subjective evaluation of interpersonal functioning  and of work abilities , measured as the discrepancies observed between the self-rated and the informant-rated assessments.Another paper, reporting data on a sub-group of patients from the SCOPE study , shows tn = 60) and with impaired functioning (n = 63). Better functioning was predicted by a lower score in the PAUSS “difficulties in social interactions” subscale  and in the PAUSS “difficulties in communications” subscale . However, having a higher score at the PAUSS' “stereotyped and repetitive interests” subscale  emerged as a significant predictor for a better functioning.In a study by Bechi et al. , 123 subp = 0.004), and worse real-world functioning in interpersonal relations (p < 0.001) and in participation in community activities (p < 0.001). However, considering the correction for the psychotic symptoms' severity, they also showed better social acceptance (p = 0.019). This observation could be due to the style of social interaction of individuals with autistic traits, which are more prone to social isolation and could therefore be perceived as more socially acceptable compared to other patients with severe psychotic symptoms.In the INRP study  functionEven if the literature agrees that autistic symptoms are correlated to a worse psychosocial functioning, as was observed for cognitive performances, some studies show a protective effect of autistic symptoms on patients with a more severe positive symptomatology.p = 0.005) and at the Social Functioning Scale .In a study by Vaskinn and Abu-Akel  the corrp = 0.01, F = 6.178) and worse self-directness ; however, no significant difference was observed in the subscales regarding the domains of relationships and work.Quality of life was evaluated in two studies by Bechi et al. , 62. In p < 0.001, β = −0.29). However, positive symptoms' severity and autistic symptoms' severity were interactively associated in improving the quality of life of the subgroup of patients with less severe symptomatology .In the second study , resultsp < 0.001 for the schizophrenia sample model and β = 1.09, p = 0.014 for the first episode psychosis sample model): participants with either severe positive symptoms or with high levels autistic symptoms had worse functioning than participants showing high levels of both. These findings represent the strongest available evidence supporting the hypothesis that autistic symptoms have a protective effect in limiting the negative impact of psychotic symptoms on psychosocial functioning.A large and recent study  includedp < 0.001 for both); however, no significant difference was observed in subjective well-being. and in global internalized stigma. Considering the different factors of the ISMI, no between-group differences were observed regarding experiential stigma and stereotypes endorsement: however, participants with autistic schizophrenia showed better stigma resistance (p = 0.022), suggesting that autistic traits could also have a protective effect in the internalization of stigma.Finally, another recent study , includiGenetic correlates of autistic symptoms measured with the PAUSS scale have been analyzed in three investigations which are part of the GRAS study, which also allowed the original scale validation.r = 0.103, p = 0.0008).The work by Stepniak et al.  shows hop = 0.030). This association was not significant in males (p = 0.101).In a paper by Mitjans et al.  it is unp = 0.038). The comparison between extreme groups (subjects with 0/1 SNP vs. subjects with 6/7 SNPs) showed an even stronger correlation (p = 0.003).Finally, in a study by Ehrenreich et al.  various r = −0.30, p = 0.028); this correlation remained significant also when considering the group of patients with the first psychotic episode  29 participants aged less than 18 years with a first psychotic episode, 30 children diagnosed with ASD and 26 healthy volunteers. In the group of patients with a psychiatric diagnosis, worse autistic symptoms were negatively correlated to the left posterior insular volume ( episode .p = 0.031) and a higher cortical inhibition (p = 0.044). Additionally, the inhibition/excitation proportion, calculated for each patient, was positively correlated to the severity of the autistic symptoms . No significant differences were observed among the groups regarding the intracortical facilitation (p = 0.143).Finally, in the study by Oliveira et al. , 20 malep = 0.034, d = 0.278), better neurocognitive performance , less severe symptoms , better functional capacity , better social functioning , better social cognitive performance  and better real world functioning in the areas of interpersonal relationships , community activities  and working activities . Better functional capacity , better social capacities , less severe psychotic symptoms , better neurocognitive performance , better socio-cognitive performance  and better functioning in the interpersonal relationships' areas  also emerged as predictors of absence of autistic symptoms.Only one paper, derived from the SCOPE study , focusedScoring of each study on all items of the Joanna Briggs Institute checklist is reported in the All included studies were conducted on well-characterized and well-described samples, with clear inclusion criteria and an appropriate diagnostic evaluation. Study outcomes were well-defined and accurately assessed in all studies, and statistical analyses were appropriate. Some of the earliest cross-sectional studies did not consider some relevant confounding factors, such as potential overlaps between autistic symptoms severity and global symptoms severity, positive symptoms severity or non-autistic symptoms severity, or did not include these elements in dedicated control analyses. These elements were however taken into account in more recent studies in several different ways.Quality of the individual outcomes results was considered high for the evidence regarding clinical, cognitive, functional and social cognition correlates of autistic symptoms measures, as the results of included studies were showed high levels of consistency, directness and precision. In particular, differences in the results of single studies that could lead to doubts regarding consistency and precision of the findings were explained by the moderating effect of positive symptoms severity, which were replicated in several studies with coherent results.As regards genetic, neurobiological and treatment outcomes, high-quality individual studies are present but in very limited number, so further research is needed to provide comprehensive evidence.Since its original validation , the PAUIn this review, 22 different articles were included, describing the results of 15 studies performed in different countries by independent groups.Most of the studies that used the PAUSS scale to evaluate autistic symptoms in schizophrenia included small samples, but some large studies were found as well. The global quality of included studies was high, and all studies showed a low risk of bias. This observation is in line with the recent publication of these works, which were all performed in the last 10 years: the fact that more recent studies are characterized by better methodological quality is well described in meta-analytic literature , 78.Cognition, and more specifically social-cognition, and functional outcomes emerged as the most frequently explored correlates of autistic symptoms.Included studies showed that autistic symptoms appear to have a negative impact on cognitive performance, and this result is quite homogeneous among the different works, representing one of the main topics of larger studies , 66. SubThis represents an expected result, as social cognitive deficits are one of the essential characteristics of both spectra –22, 79. As regards functional outcomes, the presence of autistic symptoms appears to have an important negative impact: real-world functioning is globally more compromised in subjects with more severe autistic symptoms, especially when considering social functioning , 68, 73.Autistic symptoms also appear to worsen quality of life in people with SSD , 63.Although all the above-mentioned issues are described in most of the included studies, some evidences suggest that, when considering a specific group of patients, autistic symptoms can also have a protective effect: in cases of severe positive symptoms, autistic traits appear to be associated with better attention , 75, betThis effect could be a consequence of the typical relational style of subjects with prominent autistic traits: being more prone to social isolation could limit their interactions with other people, leading them to be considered more socially adequate compared to other patients with severe psychotic symptoms. Additionally, if on one hand being immersed in personal autistic experiences can lead to worse functioning, on the other hand it also lead to higher bias in the evaluation of one's own abilities , which cRegarding biological correlates of autistic symptoms measured with the PAUSS scale, available literature is still limited. The most explored area is genetic research: different studies have identified polymorphisms that could be considered “pro-autistic” , 69, 74.Regarding the study of the neuroimaging correlates, only one study was found, and it included only very young participants with a first, early-onset psychotic episode : the resNo included study provided a longitudinal evaluation of autistic symptoms, which is necessary to analyze the stability or the trend of variation of the PAUSS score. At the present moment, it is not possible to say for sure if autistic characteristics measured with the PAUSS scale represent a trait, stable in time and associated with a specific genotype and phenotype, or rather a symptomatologic dimension that could be modifiable with treatment. The genetic studies identified through the systematic search point toward the first option, but this hypothesis remains to be confirmed.Another topic that needs to be further investigated is the relationship between negative symptoms and autistic traits, as they present several phenomenological and clinical similarities. The overlap becomes even more evident when considering that several items from the PAUSS belong to the negative sub-scale of the PANSS. Investigating more thoroughly the areas of overlap and the differences between the two domains using different measures of negative symptoms severity such as second-generation assessment tools, which are more accurate , represeThe relationship between autistic features and stigma, and particularly internalized stigma, also requires further study. Internalized stigma represents a feature that has an important impact on the lives of people with schizophrenia, strongly influencing their identity, their functioning and their quality of life –86. OnlyNeurobiological correlates of the autistic symptoms in schizophrenia are another area of interest and should be studied more thoroughly: since functional and structural neuroimaging studies underline many similarities but also remarkable differences between the two spectra , 25, 27,Finally, whether the presence of autistic symptoms represents a marker for the response to specific treatments remains to be more thoroughly evaluated, as only one study regarding this topic emerged from the systematic literature search. Results of the study suggest that the presence of more severe autistic symptoms is correlated to lack of response to a specific cognitive remediation therapy aiming to improve social cognition in the Theory of Mind domain . This reConsidering all these issues, evaluating the presence of autistic symptoms and their correlates could allow the design and implementation of tailored and targeted treatment and rehabilitation programs, in line with the objective of developing precision medicine also in psychiatry .A point of strength of the present systematic review is the accuracy of the search, conducted according to the most recent methodological indications , and theAmong the limitations of the present study is the inability to perform meta-analytic analyses: the high level of heterogeneity of the included outcomes and the differences in the use and cut-offs of the scale adopted in the included works did not allow to perform a quantitative synthesis, which could be possible in future studies with a more limited research scope. While the broad research question of the present systematic review led to the inclusion of studies with heterogeneous methods and outcomes, different important aspects and correlates of autistics symptoms were explored, providing valuable insight on the impact of the autistic dimension in people living with schizophrenia.The PAUSS scale represents the only validated instrument available to assess the severity autistic symptoms specifically in people living with SSD: since its development, it has been used more and more in the context of clinical research.The analyzed literature shows that more severe autistic symptoms are associated with worse cognitive performance, especially in the social cognition domain, and with worse psychosocial functioning. However, the presence of autistic symptoms appears to also have a protective role in some instances in subjects with more severe psychotic symptoms.Future research should focus on studying more thoroughly the correlates on the autistic symptoms, not only in a clinical but also in a neurobiological perspective. It should also focus on longitudinally assessing autistic symptoms and evaluating their stability over time, with the aim of developing tailored care projects and interventions: this could improve the therapeutic and rehabilitation offer for people living with SSD.The original contributions presented in the study are included in the article/Conceptualization and methodology: GN, SB, and AV. Data curation: GN, SB, NN EI, and DD'O. Investigation: IC-P, NN, EI, DD'O, and JL. Supervision: GN, SB, GD, and AV. Writing, review and editing: GN, SB, IC-P, and AV. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The efficiency with which plants use nutrients to create biomass and/or grain is determined by the interaction of environmental and plant intrinsic factors. The major macronutrients, especially nitrogen (N), limit plant growth and development (1.5–2% of dry biomass) and have a direct impact on global food supply, fertilizer demand, and concern with environmental health. In the present time, the global consumption of N fertilizer is nearly 120 MT (million tons), and the N efficiency ranges from 25 to 50% of applied N. The dynamic range of ideal internal N concentrations is extremely large, necessitating stringent management to ensure that its requirements are met across various categories of developmental and environmental situations. Furthermore, approximately 60 percent of arable land is mineral deficient and/or mineral toxic around the world. The use of chemical fertilizers adds to the cost of production for the farmers and also increases environmental pollution. Therefore, the present study focused on the advancement in fertilizer approaches, comprising the use of biochar, zeolite, and customized nano and bio-fertilizers which had shown to be effective in improving nitrogen use efficiency (NUE) with lower soil degradation. Consequently, adopting precision farming, crop modeling, and the use of remote sensing technologies such as chlorophyll meters, leaf color charts, etc. assist in reducing the application of N fertilizer. This study also discussed the role of crucial plant attributes such as root structure architecture in improving the uptake and transport of N efficiency. The crosstalk of N with other soil nutrients plays a crucial role in nutrient homeostasis, which is also discussed thoroughly in this analysis. At the end, this review highlights the more efficient and accurate molecular strategies and techniques such as N transporters, transgenes, and omics, which are opening up intriguing possibilities for the detailed investigation of the molecular components that contribute to nitrogen utilization efficiency, thus expanding our knowledge of plant nutrition for future global food security. Efforts to end hunger are as old as human civilization, and they have affected the history of humanity. The concern for global food security results primarily from saturated crop yields and also an imbalance between the supply and demand of the major food crops  . Increas2) to active forms of nitrogen. Total global consumption of N fertilizer was 112.5 million tons in 2015, 118.2 million tons in 2019, and likely to reach 7.9–10.5 billion by 2050 (Nitrogen (N) plays a prominent role in the plant metabolic system ,b. Nitro by 2050 . The dem by 2050 .Nitrogen use efficiency (NUE) is defined as the yield of grain achieved per unit of N available to the crop from soil and applied fertilizer, and it can be divided into two biological components, N uptake efficiency (NUpE) which is the efficiency of absorption/uptake of supplied N, and N utilization efficiency (NUtE) which is the efficiency of assimilation and remobilization of plant N to ultimately produce grain . It has TaPT4, TaNRT2.2, and TaAMT1.2 was down-regulated by arbuscular mycorrhizal (AM) colonization only when roots of host plants received phosphate or nitrogen nutrient signals. However, the expression of TaPHT1.2, TaNRT2.1, and TaNRT2.3 was down-regulated by AM colonization, regardless of whether there was nutrient transfer from AM hyphae. The expression of TaNRT1.2 was also down-regulated by AM colonization even when there was no nutrient transfer from AM hyphae  are linked with higher NUE in plants . ImproviM hyphae . Nitrogebidopsis . In the In healthy plants, nitrogen concentrations range from 3 to 4%. When compared to other nutrients, this is a substantially higher amount. In plant cells, nitrogen is a significant source of various morphological, genetic, and metabolic components. The biological combination of nitrogen with C, H, O, and S to form amino acids, the building blocks of proteins, makes nitrogen a key component of protein . ProtoplAs of today, the primary strategy for preserving and increasing agriculture production is the administration of mineral fertilizers, such as nitrogen. Commercial fertilizers contain N which is highly soluble, making it easy for plants to absorb and assimilate. Only 30–40% of the applied nitrogen is utilized by crops since the N compounds are often available in the form of nitrate and ammonium and are highly mobile in the soil . NUE canNitrate is a key source of nitrogen for plants; in fact, the majority of plants spend a substantial percentage of their carbon and energy reserves on its uptake and assimilation . NitrateNRT1 and NRT2. The NRT 2 family encodes transporters to the high-affinity uptake system whereas NRT 1 family is more complex, including nitrate transporters with dual affinity or low affinity. The nitrate uptake is driven by the proton gradient against the plasma membrane and its uptake is driven by ATPases  constitutive high-affinity transporters (cHATS); (b) nitrate-inducible high-affinity transporters (iHATS); (c) constitutive low-affinity transporters (cLATS); and (d) nitrate-inducible low-affinity transporters (iLATS) . In plan ATPases . In comp ATPases . Initialhia coli . Howeverhia coli . AttemptFertilizers play a pivotal role in enhancing and sustaining crop yield. It is reported that a 50% yield increment is contributed by nitrogen (N) fertilizer. However, about 40–50% of the applied N is lost by ammonia volatilization, leaching, run-off, and denitrification. Therefore, in place of conventional chemical fertilizers, the use of modern fertilizers could be a potential alternative . These f2O5, 25% K2O, 3% S, and Zn 0.5%). It encompasses both macro and micro-nutrients required by selected crops in specific regions. Adoption of such fertilizers would enhance NUE which is currently 40% for N, 20% for P, 50% for K, and 2–5% for other micronutrients (Customized fertilizers (CF) are a multi-nutrient carrier that contains macro and micro nutrient forms . “Paras utrients . Many scutrients . The quautrients .2 influenced the availability of P by increasing its mobility. It also boosted the NUE by decreasing the demand for P and N fertilizer for the growth of plants. Foliar application of NFs (chitosan-NPK) enhanced the productivity and nutritional status of wheat (–1 soil) enhanced the accumulation of Zn in plants grown under Zn deficient soil (–1 soil) of nano-ZnO in sorghum enhanced the productivity, uptake, and NUE  to tomato plants improved the growth, uptake, and accumulation of plant nutrients  and phosphate solubilizing bacteria (PSB) improve the plant growth by producing phytohormones, liberating nutrients, and stimulating induced systemic resistance  that consist of distinct chemical compositions. Clinoptilolite is the most widely found zeolite. It is attributed with high cation exchange capacity, surface area, base saturation, and porosity which make it a potential candidate for improving the chemical properties of soil . Zeolitelication . It has lication . KavoosiMalaysia . The appMalaysia . Surfaceironment . Ammoniuironment .Precision farming is an information and technology oriented farm input handling approach that aims to identify, analyze, and manage spatial and temporal variation present within the field by performing all practices of crop production in right place at right time in the right way for optimum profitability, sustainability, and protection of land resources . Global The GPS provides location information in real-time while it is moving. After getting specific location details, the collection of soil and crop location data could be accomplished efficiently. GPS receivers can be kept along with farm implements, which permits the users to return to precise locations for managing those areas. GIS are computer systems that utilize features, characters, and location data for obtaining maps. They also store remotely sensed data and soil nutrient levels. Remote sensors of N are managed in an experienced way for evaluating the demand for N to be fertilized into the cropping system . In sensA leaf color chart (LCC) is used for evaluating the leaf N concentration based on the chlorophyll content of the leaves . It is a–1), NUE (19.2 kg kg–1), and RE (54.3%) were found higher under N followed the management with LCC in different rice genotypes in Gujarat. Application of N at LCC4 was found better than LCC5 and LCC3 in terms of yield and nitrogen saving  is also called a chlorophyll meter that measures the chlorophyll concentration of leaves. It is used to determine the effectiveness of top-dressed N for improving the productivity and protein concentration in the crop plants . The appDiversified crop rotation is one of the major components of conservation farming. It has a tremendous role in optimum utilization of resources and enhancement of resource use efficiency. Adoption of diversified crop sequences ensures precise application of inputs (nutrients and moisture) to crops for maintaining the sustainability of the agricultural production system . InclusiThe term “4R” refers to the use of the right source, right rate, right time, and right place in nutrient management . 4R nutrThe application of nutrients to crops through a drip system is called drip fertigation. It is the most advanced method in nutrient as well as in water management. Farmers are practicing drip fertigation, particularly for winter wheat, across the globe owing to significant improvement in WUE and NUE. Drip fertigation matches the water and N supply with crop demand which eventually enhances water productivity and NUE . It has Crop models are a collection of mathematical equations that were developed for predicting plant growth and development in precise ways . Also, tNitrogen is the major essential nutrient required by the plants and it interacts with almost all the other essential nutrients. N has synergistic interaction with most of the nutrients that leads to enhanced NUE. However, the kind of interaction depends on the number and amount of interacting nutrients present in the soil and their application rate. If both the interacting nutrients have an imbalanced amount in the soil it could cause antagonistic interaction . Jiang JPhysiological attributes play a pivotal role in improving NUE in plant species. Among those attributes, the root system is crucial in the acquisition of water and nutrients through its ability of soil exploration which is the main determinant of NUE . NUE depDue to the major role of the root system in NUE, its genetic basis is also subjected to study. A research study was conducted to understand the genetic association between root traits of maize seedlings and NUE through QTL analysis. Recombinant inbred lines of maize were sown under low and high nitrogen conditions in which 9 traits of RSA and 10 traits of NUE were evaluated in three hydroponic and four field conditions, respectively. A significant correlation was observed between uptake efficiency of nitrogen and RSA . Almost 331 QTLs in total were identified including 147 QTLs of RSA and 184 QTLs of NUE. Almost 70% of NUE-QTLs coincided with the QTL clusters of RSA which indicated the significant genetic association between traits of NUE and RSA. This association can aid in the selection of RSA-traits for improvement of NUE in the maize .–1) and high nitrogen level (5 mml–1). The panel was further genotyped with an SNP marker of 542,796 high density. Various root traits were observed to be increased under low nitrogen conditions such as total root length, dry weight of root, root-to-shoot ratio, lateral and axial root length of the primary root. Furthermore, a wider heritability range of 0.43–0.82 was observed under low nitrogen conditions than the range of 0.25–0.55 under high nitrogen conditions. After marker-assisted analysis, it was observed that under low nitrogen conditions, gene encoding DELLA protein was in association with the lateral root-zone of primary root and protoporphyrinogen IX oxidase-2 gene was in association with the surface area of the root. While under high nitrogen conditions the histone-deacetylase gene was in association with the plant height which can be further used to exploit genetic improvement in root traits through better NUE of maize  under high and low nitrogen hydroponic conditions. Results indicated the significant correlation of root size (trait related to RM) with N-uptake and dry biomass of plant while no correlation was observed with the efficiency of nitrogen utilization (NUtE). Approximately 23 stable QTLs out of a total of 129 were detected in both high and low nitrogen conditions. Most of the stable QTLs (20/23) were observed to be related to RM traits under both high and low nitrogen conditions which lead to the suggestion of regulating the root morphology through NUE is more feasible than through regulating the nitrogen efficiency in rapeseed . Anotherof maize . The impCereals, such as rice, wheat, and maize, are the most important sources of calories and nutrition for humans. Modern varieties differ in key NUE characteristics . HoweverNUE is a polygenic trait with a number of factors. As a result, identifying individual genetic effects involves quantitative genetics strategies, and such effects have been usually characterized as QTL. There are several methods for identifying genes that control NUE and utilizing them in breeding. Associations genetics could be based on genetic panels that are well-suited to the researcher’s test environment, sample multiple alleles, and provide extremely high genetic resolution. Furthermore, association genetics requires a good balance of alleles at each location analyzed, with low-frequency alleles  being excluded from the research. Segregating populations derived from two diverse parents is the best-established way of QTL identification. Recombinant Inbred Lines and Single Seed Descent or the doubled haploids are statistically strong because only the two parental alleles are segregating at anyone locus and the population is comprised 50% of each allelic class.A number of studies on NUE QTLs have been well known by this approach for example in rice . Multi PRecently the development of cultivars with improved NUE is of utmost essential as after decades of green revolution application of N fertilizer is increased tremendously to meet grain yield demands. Simultaneously, its negative impact may be witnessed in the form of the increased cost of cultivation and hazardous effect on the ecosystem. The transcription factors, allosteric control, and post-transcriptional modification all play a vital role in the expression of a complex trait like NUE . BecauseSelection of genotypes having root structure association (RSA) based NUE is recommended in wheat due to a limitation of full comprehension regarding the genetic background of NUE and associated G × E interactions. Wheat QTL analyses for all RSA characteristics are also available. Numerous wheat QTLs for NUE attributes have been discovered at the physiological and agronomic levels . DespiteOsNRT2.1 expression with the OsNAR2.1 promoter  produced two co-expression modules containing PtoNRT genes. Moreover, PtoNRT genes defined thousands of eQTL signals. WGCNA and eQTL provided a comprehensive analysis of poplar nitrogen-related regulatory factors, including MYB17 and WRKY21.A meta-QTL (MQTL) study appears to be a viable technique for overcoming the aforesaid constraints in employing QTLs for the production of wheat cultivars with greater NUE, as it permits identification of the most robust and stable MQTLs. Because MQTLs have lower confidence intervals (CIs) and better phenotypic variation explained (PVE %) than QTLs, they are more useful in marker-assisted selection (MAS). MQTLs have also been demonstrated to be effective in identifying interesting candidate genes (CGs) linked to the trait of interest. Already, this approach has been utilized in the identification of MQTLs in various major crops like wheat, rice , barley promoter . Moreove in rice . PreviouSimilarly, in maize plants, it has been reported by many authors that some gene domains/families which are responsible for other gene regulations were also found to be engaged with NUE. For example, kinase domain (98 genes), for protein-containing F-box like domain (79 genes), for cytochrome P450 proteins (40 genes), for glycoside hydrolases (32 genes), for UDP-glucosyltransferases (13 genes), for NAC TFs (16 genes), for expansions (14 genes), for early nodulin-93 proteins (13 genes), for GRAS TFs (10 genes), and ABC transporter proteins (10 genes), respectively, were associated with NUE . PreviouNRT1 gene families are responsible for coding LATS and AtNRT1.1 and AtNRT1.2 govern the nitrate uptake. The transcription factor TaNCA2-5A plays a significant role in the expression of transporters associated with nitrate uptake and happens to be a key controller in N supervisory system , and iron (Fe) concentration at the time of senescence by delaying the senescence period . The bety system . The impGS1, GS2, GOGAT, AlaAT, GDHA, Nia1, and Nia2 to develop genetically engineered NUE cereals mainly in rice, corn, wheat, and rapeseed-mustard. The major studies report that the gene used for improved NUE was mainly plant-based except for some bacterial genes and tested in both model plant Arabidopsis as well as in other crop plants also. The most extensively plant-based gene used for NUE was the gene that is involved in GS biosynthesis which makes GS a major source for N movement from source to sink. It has also been evident that over-expression of this gene in cereal crops, improves the NUE, foliage, and grain yield, however, it has not been reported in dicots due to mismatch or poor promoter (TaNRT2.1 was very well associated with uptake of nitrate, the gene code for root nitrate transporter, and correlated with high protein and grain yield in wheat (OsNRT1 is expressed under low N conditions in rice (AtNRT2.1 and AtNRT2.1 well correlated with nitrate uptake and showed 75% high affinity under a scarcity of N content, suggesting that expression of these two genes related with better performance under low N conditions in Arabidopsis (ZmNRT2.1 and ZmNRT2.2 through sequence homology approach accounts for increased resistance to low N concentration (Gln1-3 and Gln1-4 through virus promoter, which codes for GS biosynthesis, results in the 30% increase in maize kernel yield (OsNRT1.1B and OsNRT2.3b were identified as nitrate transporter genes. By using this promoter gene, when barley AlaAT gene was transferred in canola and rice, enhanced the NUE by 40 and 12% in canola and rice, respectively, recently many private companies are using OsNRT2.3b in various crops like maize, rice wheat, and soybean to accelerate grain yield through improved NUE (E. Coli, GDHA, expressed in tobacco via plant virus promoter improved the biomass by 10% under deficient N concentration (TaNAC2-5A aided grain yield and N movement in wheat plants and suggested that the gene can be utilized in wheat breeding programs to increase grain production through the development of high NUE varieties (LeNRT2.3 leads to enhance nitrate uptake and N movement (OsATG8b gene of the rice plant, which plays a key role in N mobilization in rice plant (OsENOD93-1 resulted in improved NUE under both the conditions low as well as in optimal N conditions (Through the transgenic approach defect removal in any cell is made possible by integrating a single foreign gene sequence in the host’s genome background via transformation method is only a quick and time-efficient technique over the conventional methods. Many insect-pest resistant, disease resistant, and genetically modified crops have been released for their cultivation in 28 countries across the world: the United States, Brazil, Canada, Argentina, China, and India among them . Researcpromoter . A previin wheat . The gen in rice . AtNRT2.bidopsis . In maizntration  while thel yield . In the oved NUE ,b. The Antration , 2006. Tarieties . In tomamovement . Geneticmovement  and alsoce plant . Similarnditions . Similarnditions . The impThe increase in N uptake from the seedling stage to the pre-flowering stage and increased N-translocation at the post-flowering stage are the two ways to improve NUE in any plant. Because there is a link between N uptake and rhizosphere nitrification, as well as the contribution of nitrate to N uptake, current high yield-crop breeding initiatives that modify the expression of nitrate transporters in new crops will enhance the balance between nitrate-N and ammonium-N uptake. Anticipating, germplasm-related differences in nitrate transporter activity will be revealed in the future, and employing transporters to improve N absorption and translocation, and therefore increase NUE, will be discovered.By virtue of the necessity of precise identification of genes involved in N uptake, mobilization, and recycling at various plant growth stages from seedling to maturity, taking the benefits of many omics data sets that include transcriptomics, proteomics, and metabolomics which could further be accessed in an interactive manner by using bioinformatics, computational, and mathematical techniques. Previous researchers have investigated rice transcriptome under N deficient conditions by using high scale data set to identify the specific N responsive genes and miRNA .However, these findings were restricted to single type RNA like, mRNA or small RNAs, and also have not provided an overview of transcriptome responses to alter N mobility. 3– sensing and signaling in Arabidopsis (Arabidopsis was reported by Brassica rapa based agroecosystem using multi-omics and integrated informatics approaches and revealed complex interactions among multiple network modules of NUE. bidopsis . Amiour Global food security with nutritional security is the most crucial task for future generations. However, the efforts of scientists or agricultural researchers can achieve this task and somehow they succeed in finding numerous technologies and ways through which they are trying to complete. Although, in modern times several new problems such as climate change, abiotic stresses, and problematic soils cause the loss of natural resources, and together amplify our food security target. In this scenario, there is an emergency need to reduce the cost of cultivation and degradation of natural resources. Therefore, increasing the NUE in economically important crops is a great challenge to secure environmental sustainability. However, the advancement in agronomical approaches has achieved some milestones in the last decades such as precision farming and nano-fertilizers. On the other hand, recent advancements in molecular biology and tools speed up the process and have a bright future in developing higher NUE efficient crops. However, still there is a huge gap in targeted NUE and also reduced during the last decades because of higher use of N fertilizers, especially urea. Therefore, it is recommended that the new fertilizer policy is based on the alternatives to urea for N sources such as customized, bio, and nano-fertilizers, which might be a breakthrough in enhancing NUE and reducing N pollution. Also, there might be a decision support system for best management practices at a local basis, which can directly benefit to the farmer in enhancing NUE and yield. Therefore, we combined these two crucial approaches in respect to improving NUE and might be game-changing for enhancing NUE in near future. Moreover, future trends and expectations should be aimed at cracking the current main hurdles to crop plants. Modern genome-editing tools can provide a permanent solution by developing varieties with enhanced NUE, although further studies are needed to reach these goals. The integration of all these approaches will lead to the sustainable production of crops, through the effective management of environmental stresses under the present scenario of changing climate. In addition, plant epigenetics, which is a conserved gene expression regulatory mechanism including histone modification, DNA methylation, non-coding RNA, and chromatin remodeling, represents an emerging and efficient tool to better understand biological processes in response to nitrogen enhancement.TJ and RKS: conceptualization. II, TJ, RKS, RS, and AS: writing—original draft preparation. PK, AS, DJ, MAS, PD, DSa, HA, RA, and DSi: writing—review and editing. DSi and RA: funding acquisition. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Although cognitive functioning is strongly associated with biological changes in the brain during the aging process, very little is known about the role of sociocultural differentials between the western and eastern parts of the world. We examined the associations between individual socioeconomic markers  and contextual levels characteristics  with memory performance and memory decline over up to 8 years of follow-up in England and China.n = 6,687) and the China Health and Retirement Longitudinal Study . Mixed linear models were employed to examine the association between baseline individual socioeconomic markers  and contextual-level characteristics (urbanicity) on the change in memory over time.The analytical samples included participants aged 50+ from the English Longitudinal Study of Aging (Our analyses showed that higher education and wealth were associated with better baseline memory in both England and China. Still, the impact of contextual-level characteristics such as urbanicity differed between the 2 countries. For English individuals, living in a rural area showed an advantage in memory, while the opposite pattern was observed in China. Memory decline appeared to be socioeconomically patterned by higher education, wealth, and urbanicity in China but not in England.Our findings highlight substantial socioeconomic and contextual inequity in memory performance in both England and China, as well as in the rate of memory decline primarily in China. Public health strategies for preventing memory decline should target the socioeconomic gaps at the individual and contextual levels to protect those particularly disadvantaged. Socioeconomic status (SES) is a key determinant of health, with notable and marked disparities within and between various individuals and regions worldwide . The heaHowever, the role of education and other socioeconomic determinants on the rates of cognitive decline in the Pacific-Asian countries is less clear. There are considerable variations between levels of compulsory education across countries and in access to health systems, with cultural differences in lifestyle behaviors that could account for some of the discrepancies observed in cognitive aging . A compaFindings from epidemiologic and clinical studies suggest a myriad of biological, behavioral, social, and environmental factors contributing to cognitive decline  or higheIn addition to individual-level factors such as education and wealth, there are other important inequalities in terms of contextual and geographical characteristics. These relate to issues such as neighborhood quality, the accessibility of healthy food outlets, walkability, recreational areas, access to cultural engagement, and health care. Previous findings from the English Longitudinal Study of Ageing (ELSA) showed that the Index of Multiple Deprivation, an aggregate measure of neighborhood quality in the United Kingdom, was associated with cognitive performance in older age, independent of education or individual-level SES . SimilarNevertheless, associations with neighborhood factors have been inconsistent. For example, Meyer and colleagues showed that neighborhood SES across areas of Northern California had limited associations with baseline executive function and semantic memory, but individuals with dementia living in higher socioeconomic neighborhoods experienced faster rates of cognitive decline in these domains. Yet, these associations were explained by individual-level factors such as education, ethnicity, and vascular risk factors .education and wealth) and contextual-level characteristics (urbanicity), as well as their interaction on memory performance and memory decline in two nationally representative cohorts of English and Chinese. We hypothesized that participants with lower levels of education or wealth or living in a rural area would have a lower baseline memory performance and steeper decline over time in both England and China.Until recently, very little research attention has been paid to socioeconomic risk factors affecting the rates of cognitive decline in contemporary Chinese society compared with Western countries such as England or the United States. Therefore, we aimed to examine comparatively the relative contributions of different socioeconomic markers  and contextual area-level characteristics , were measured in each study at baseline (Wave 5—ELSA and Wave 1—CHARLS). Employing a coordinated approach of data harmonization , educatiSeveral covariates were considered within each cohort based on previous findings (15) and the best model fit. These were baseline age (centered to 66 in ELSA and 61 in CHARLS), sex, marital status, a history of heart problems (yes/no), diabetes mellitus (yes/no), depressive symptoms (yes/no), alcohol (yes/no), and smoking (yes/no). Being younger, male, married, having no heart problems, diabetes, depressive symptoms, and not smoking or drinking was used as the reference group.The analytical subsamples included only data from core members aged 50 and older in each study at their baseline wave see , and modSD = 2.80) in ELSA and 3.05 (SD = 2.56) in CHARLS. Demographics and memory scores at baseline and each follow-up wave for the two studies (ELSA and CHARLS) are presented in The average follow-up period was 3.53 (SD = 9.09) in ELSA and 61.27 (SD = 7.57) in CHARLS. There was a balanced number of men and women in each cohort, and most participants were married. A third of the English sample was educated to a low level, while 70% of the Chinese sample were not educated or educated to a low level. About 70% of ELSA participants live in an urban area, while 77% of CHARLS participants live in a rural area. The overall memory performance was higher and relatively stable across all waves in ELSA participants. In contrast, in CHARLS participants, the overall performance was lower and declined steeper across waves (see The mean baseline was 66.65 (aves see  and S4.The unstandardized regression coefficients and 95% CIs for the baseline memory (intercept) and linear change (slope) across the two cohorts are shown independently in relation to each socioeconomic marker within each study in fully adjusted models for all the covariates see .p ≤ .001 and showed an annual decline of −0.22 (95% CI: −0.28 to −0.016), p ≤ .001 memory points per year. In comparison with those with no formal education, ELSA participants with higher levels of education showed significant increments in the baseline memory score with 1.04 (95% CI: 0.85 to 1.23), p ≤ .001 for low level, 1.63 (95% CI: 1.43 to 1.83), p ≤ .001 for medium, and 2.37 (95% CI: 2.13 to 2.60), p ≤ .001 for higher levels. No significant associations were observed between higher levels of education and the rate of memory decline in ELSA , ELSA see .p ≤ .001 and showed an annual decline of −0.44 (95% CI: −0.51 to −0.36), p ≤ .001 memory points per year. CHARLS participants with higher levels of education also showed significant increments in the baseline memory score with 1.09 (95% CI: 0.95 to 123), p ≤ .001 for those with up to low levels, 2.19 (95% CI: 2.02 to 2.35), p ≤ .001 for those with medium level, and 3.67 (95% CI: 3.38 to 3.95), p ≤ .001 for those with high levels of education. Higher levels of education showed significant protective effects on the rate of memory decline in CHARLS with 0.21 points (95% CI: 0.17 to 0.24), p ≤ .001 slower rates of annual memory decline for those with up to low levels, 0.33 (95% CI: 0.29 to 0.37), p ≤ .001 for those with medium level, and 0.27 (95% CI: 0.19 to 0.35), p ≤ .001 for those with a high level of education , tion see .p ≤ .01 for those in the second lowest quintile, up to 1.73 (95% CI: 1.48 to 1.98), p ≤ .001 for those in the highest quintile of wealth. No significant associations were observed between higher levels of wealth and the rate of memory decline in ELSA , ELSA see .p ≤ .01, and 0.98 (95% CI: 0.79 to 1.16), p ≤ .001, in comparison with those in the lowest quintile. In relation to memory decline, the highest top quintiles of wealth showed a protective effect with a 0.08 (95% CI: 0.03 to 0.13), p ≤ .001 slower change over time , time see .p ≤ .001 but no significant differences in memory decline over time. By contrast, a greater disadvantage was observed for those living in rural China in terms of memory performance with −1.41 (95% CI: −1.55 to −1.27), p ≤ .001, and a slightly steeper decline over time with −0.08 (95% CI: −0.12 to −0.04), p ≤ .001, compared with those living in an urban area  and urbanicity, but these were nonsignificant in both cohorts.The pattern of results was maintained when all SES markers were mutually adjusted, except for the role of urbanicity on memory slope in CHARLS, which was further explained by socioeconomic makers see . Sex-strThis cross-cohort investigation examined various socioeconomic markers and contextual differentials in relation to memory and memory decline over an almost a decade follow-up period within two nationally representative samples of the English and Chinese population, highlighting significant differences in terms of education, wealth, and urbanicity. This comparative examination suggests that the average baseline memory scores were generally lower in China compared with England when controlling for individual markers of socioeconomic position such as education or wealth and a wide range of covariates, including sociodemographic characteristics, health conditions, and lifestyle behaviors, while the rate of memory decline was much steeper for the Chinese counterparts compared to English participants when accounting for education.The overall findings illustrate substantial advantages conferred by the individual socioeconomic characteristics such as education and wealth in terms of baseline memory in both English and Chinese participants and a slower rate of memory decline in China but not in England. Such differences are particularly interesting because several studies  and systThe specific country differences captured here could be explained by several factors. One is that English participants had overall higher baseline memory scores and declined less over time, while the Chinese respondents started with significantly lower scores and dropped a bit faster. Second, the access to education and pattern of lifestyle behaviors influencing overall health and cognitive performance might be different between England and China. Furthermore, the difference in baseline memory scores could be related to the overall lower level of literacy in China  in England, whereas the associations were more uniform in China at both individual- and group-level SES characteristics. Overall results indicate that both English and Chinese middle-aged and older participants benefitted from better memory scores at baseline with higher levels of education and wealth. Among Chinese individuals with relatively no education, higher levels of education were associated with slower linear decline coupled, and a similar pattern was also observed for those with the highest level of wealth. However, the most substantial effects were observed for individuals living in rural China, who experienced the most substantial memory decline over time compared to those living in an urban area. It is important to acknowledge the considerable income disparity between China’s rural and urban residents driven by the residency (hukou) and health care systems. This could be related to the geographic disparities in health status, differences in government expenditure between urban and rural areas, as well as population lifestyle and personal behaviors that could contribute to chronic illness and mental decline . FurtherA growing body of evidence has suggested that an individual sustained cultural and educational engagement across life could help build cognitive reserve and mental capital, sculpting an individual’s brain architecture and offering increased neurogenesis  and resiNeuroimaging studies show a strong link between brain structure and level of educational attainment in adulthood, with increases in white matter integrity and fractional anisotropy as well as a decrease in mean diffusivity . RelevanOur conclusions should be interpreted in light of a number of limitations that need to be acknowledged. We relied on self-report measures of education and household wealth, although we benefitted from objective records for memory and urbanicity. Furthermore, although we controlled for several important covariates known to be associated with both socioeconomic circumstances and memory, the possibility of some biases arising from attrition, survival effects, or uncontrolled confounding may not have been accounted for. Even though the mixed model analyses use maximum likelihood estimation to account for attrition over the 8-year follow-up period, the population sample may be initially selected on critical variables. Those with more education, better financial circumstances, and better memory were more likely to accept the initial invitation to participate in the study. Another limitation of this study is the relatively low representation of mixed ethnicity within ELSA. Furthermore, both ELSA and CHARLS did not cover participants living in institutional settings, so the current results can only be generalized to older people living in the community in England and China, respectively. However, this comparative cross-country investigation was matched in terms of data harmonization for all measures and the follow-up period across the two studies between 2011 and 2019, although independent observation of ELSA would have benefited from a more extended follow-up study period (2002–2019).Strengths of our study include the coordinated approach analysis of the same cognitive measure and choice of covariates in each of these two nationally representative samples of English and Chinese middle-aged and older populations. Another strength of this study is the use of several measurement occasions to objectively measure memory change (five time points in ELSA and four in CHARLS) and the rich exploration of various baseline socioeconomic markers within each of these cohorts. To the best of our knowledge, this is the first investigation to explore comparatively the role of multiple socioeconomic and contextual markers on cognitive decline in England and China. To untangle their underlying influence on the level of baseline memory and rate of decline, we employed linear mixed models over five measurement occasions in England spanning over 8 years and four measurement occasions in China spanning across a 7-year follow-up period. Mixed linear methods represent a robust measure of examining change in repeated measures of cognition over time when investigating association mapping in the presence of geographic population structure and/or another cryptic relatedness. A particular advantage is that mixed linear models prevent false-positive associations due to these types of systems and provide an increased power specific to the sample structure . To avoiIn English and Chinese nationally representative populations, we found strong socioeconomic and contextual differentials as indicated by the level of education, household wealth, and urbanicity affecting memory performance in both countries and the rate of decline, particularly in China. Educational and regional public health policies within each country play a key role in explaining observed differences in health gaps, and substantial efforts should be considered to reduce these inequalities worldwide.gbac163_suppl_Supplementary_MaterialClick here for additional data file.


Zoonoses are public health threats that cause severe damage worldwide. Zoonoses constitute a key indicator of One Health (OH) and the OH approach is being applied for zoonosis control programmes of zoonotic diseases. In a very recent study, we developed an evaluation system for OH performance through the global OH index (GOHI). This study applied the GOHI to evaluate OH performance for zoonoses in sub-Saharan Africa.The framework for the OH index on zoonoses (OHIZ) was constructed including five indicators, 15 subindicators and 28 datasets. Publicly available data were referenced to generate the OHIZ database which included both qualitative and quantitative indicators for all sub-Sahara African countries (n = 48). The GOHI algorithm was used to estimate scores for OHIZ. Indicator weights were calculated by adopting the fuzzy analytical hierarchy process.Overall, five indicators associated with weights were generated as follows: source of infection (23.70%), route of transmission (25.31%), targeted population (19.09%), capacity building (16.77%), and outcomes/case studies (15.13%). Following the indicators, a total of 37 sub-Sahara African countries aligned with OHIZ validation, while 11 territories were excluded for unfit or missing data. The OHIZ average score of sub-Saharan Africa was estimated at 53.67/100. The highest score was 71.99 from South Africa, while the lowest score was 40.51 from Benin. It is also worth mentioning that Sub-Sahara African countries had high performance in many subindicators associated with zoonoses, e.g., surveillance and response, vector and reservoir interventions, and natural protected areas, which suggests that this region had a certain capacity in control and prevention or responses to zoonotic events.This study reveals that it is possible to perform OH evaluation for zoonoses in sub-Saharan Africa by OHIZ. Findings from this study provide preliminary research information in advancing knowledge of the evidenced risks to strengthen strategies for effective control of zoonoses and to support the prevention of zoonotic events.The online version contains supplementary material available at 10.1186/s40249-022-01020-9. One Health (OH) is an integrated and unifying approach that aims to sustainably balance and optimize the health of people, animals and ecosystems. Hence, OH performance index is referred to as the capacity to prevent or respond to humans, animals, and the environment health threats . The OH In 2018, three major international organizations, the World Health Organization (WHO), the United Nations’ Food and Agriculture Organization (FAO), and the World Organization for Animal Health (OIE), put the OH vision into practice by consolidating a formal partnership and strengthening their joint action to combat human-animal-environment health risks . This cuZoonoses are infections that are naturally transmitted between human beings and other vertebrates and can spread from food, water or the environment directly. Zoonoses alone represent 60% of world known infectious diseases, with a high proportion (70%) of pathogens coming from wildlife hosts . With thThe development degree of a country or area has great significance for its governance capacity of zoonoses. Developed countries have huge advantages in medical treatment, public health, economic construction, scientific research input and social welfare that most developing settings lack . Sub-SahOne Health initiative on zoonoses, including governance capacity in surveillance and research activities, has been carried out in many countries/territories across the African continent . In KenyIn this study, we formulated indicators for zoonoses and applied OH principles , 23 to dOH principles were applied to evaluate OH performance for zoonoses in sub-Saharan Africa. This study defines the OH index on zoonoses (OHIZ) as an indicator to assess the capacity of a country/territory to respond to or prevent zoonotic events associated with the holistic health of the human-animal-environmental interface. Figure Selection of the OHIZ database for zoonoses was based on seven principles as reported by Zhang and colleagues . These dAccordingly, three elements (indicators) of infectious diseases were included in the OHIZ framework and were referred to as the source of infection, route of transmission, and targeted population. Given that the OH approach covers areas of policy support, scientific research, and infrastructure construction, an indicator termed capacity building was also set. A further indicator referred to as outcomes (case studies) was added to form a five-indicator panel for OHIZ. Indicators that did not meet the OHIZ principles were excluded. Subindicators were conceived following the abovementioned indicators and information from previous studies , 25, 26.The panel of indicators was classified into qualitative and quantitative indicators according to the database sets that were consulted. Data collection was applied to qualitative indicators, while data were retrieved for quantitative indicators , 23, 27.OHIZ database building referred to internationally published authoritative databases. A total of 28 comprehensive sets of OHIZ data were identified, including 13 datasets retrieved from the WHO database , four daThe OHIZ algorithm from the robust global One Health index (GOHI) algorithm system that was reported recently , 23, wasAccording to the WB classification criteria for countries and regions, there are 47 countries/territories in sub-Saharan Africa. OHIZ was analyzed for all sub-Sahara African countries (n = 47). Criteria of data of the same indicators from three similar countries were used to exclude biased data or countries with missing data. When there were more than 160 missing data points for an indicator, the indicator was excluded. When there were more than 50% missing data for a country, the country was excluded from the final list. A total of 37 sub-Sahara African countries were retained for the OHIZ Fig. .Fig. 2OHThis study identified 28 datasets for zoonoses under 15 subindicators and five OHIZ indicators, which were all associated with weights , overall. The indicator scores obtained for the route of transmission, source of infection, and outcomes (case studies) were 60.64 ± 12.43, 55.41 ± 12.52, and 35.27 ± 10.03, respectively  in sub-Sahara African countries was 45.05. The average score for policy adoption of insecticide-treated mosquito nets was 90.93, that for policy adoption of indoor residual spraying was 85.68 and that for prevention chemotherapy coverage of zoonoses was 43.81 in terms of capacity of vector and reservoir interventions , followed by those of echinococcosis 42.20), rabies (19.19), and tuberculosis (17.31). However, the capacity of sub-Sahara African countries in responding to and preventing COVID-19 scored an average vaccination coverage estimated at 47.69 and that of infectious number at 34.56 . In addition, five countries exceeded 60 in scores, and 12 countries were lower than 50 in scores, while the scores of all the countries were normally distributed on the whole (Fig. Results from this study provided OH performance for zoonoses and promoted awareness of OH by providing a reference in OH practice, research gaps and international assistance for sub-Sahara African countries. In addition, this study revealed an important finding where the governments of the 11 countries that were excluded are encouraged to direct more resources in the holistic application of the One Health approach for zoonoses so that their performance can be assessed in future. However, this work based on the OHIZ framework and official databases from authoritative organizations, which might be restrictive for the selection of the indicators within the scope of the framework.In the last two decades, human beings have suffered from zoonoses. Zoonoses prevention and control had issues such as cross-border transmission and multidisciplinary integration. The OH approach provides an opportunity to overcome these challenges. In addition, the development of OH between countries needs to be synchronized. The OH concept has been raised at the beginning of the twenty-first century , 39 and Indicators to assess OH performance related to zoonoses are manifold, yet they are still not seemingly being embraced in developing countries, especially in sub-Saharan Africa, where zoonoses have the greatest impact. Findings from this study provide preliminary research information in advancing knowledge of the evidenced risks to strengthen OH strategies for effective control of zoonoses and to support prevention of a next zoonotic event.Additional file 1. Sources of data for the indicator sets used for zoonoses OHi.