Although the relationship between serum uric acid (SUA) and nonalcoholic fatty liver disease has been widely reported, the relationship between SUA and liver enzymes has rarely been reported. The purpose of this study was to evaluate the association of SUA levels with alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in populations aged 20 years and older in the United States. We analyzed 7165 individuals aged 20 years and older from the National Health and Nutrition Examination Survey (NHANES) in the United States. Weighted multiple linear regression models were used to analyze the relationship between SUA and ALT and AST. A generalized additive model and a smooth curve fitting were used to observe the linear relationship. SUA was positively correlated with ALT and AST. In addition, the overall increasing trend of ALT and SUA was observed across the SUA quartile groups. In the stratified analysis by sex and race, the SUA levels in male, female, Mexican American, and Non-Hispanic White individuals, and those of another race, were positively correlated with ALT and AST. However, the SUA levels in Non-Hispanic Black individuals had a nonlinear relationship with ALT and AST. In individuals aged 20 years and older in the United States , SUA levels were positively associated with ALT and AST. Therefore, with a rise in SUA levels, liver function should be monitored or intervened with in people aged 20 years and older in the United States. Serum uric acid (SUA) is the main end product of purine metabolism, usually in the form of urate. It is well known that approximately two-thirds of urate is excreted by the kidneys and the remainder is excreted extra-renally, while a dysfunction in extrarenal excretion might increase the risk of hyperuricemia (HUA) ,2. In reThe liver has complex physiological functions, including metabolism, secretion, bile excretion, detoxification, and so on ,13. AlanIn recent years, a large number of studies have shown that the prevalence of NAFLD is closely related to levels of SUA . A crossWe believe that there might be a potential connection between SUA and liver enzymes. However, the relationship between SUA and liver enzymes has rarely been reported, and the underlying mechanism was not clear. A recent study in a Bangladeshi population found that SUA levels were positively correlated with ALT, while a significant correlation was not observed between SUA levels and AST . Therefohttps://www.cdc.gov/nchs/nhanes/, accessed on 29 July 2022), which contains representative health and nutrition data on the noninstitutionalized U.S. civilian population. The study used demographic data, dietary data, examination data, laboratory data, and questionnaire data. All studies in NHANES were approved by the Institutional Review Board of the National Center for Health Statistics .We used data from the National Health and Nutrition Examination Survey (NHANES)  were selected, and 40,790 participants were enrolled . After excluding participants who were younger than 20 years , who reported that they had diabetes (n = 2695), liver disease (n = 320), or cancer or malignancy (n = 1651), who had a positive blood test for the hepatitis B surface antigen (n = 81), who had used thiazide-like diuretics (n = 1338) or allopurinol (n = 99) within 1 month before the survey, and who lacked SUA (n = 1664), ALT (n = 54), AST (n = 4), or triglycerides , a total of 7165 eligible subjects were enrolled as our analytic sample .2), and waist circumference , and levels of serum total bilirubin , serum creatinine , total cholesterol , TG (mg/dL), high-density lipoprotein cholesterol , low-density lipoprotein cholesterol , glycated hemoglobin , platelets , and fasting blood glucose . It is worth noting that blood lipid levels were only investigated for participants who fasted for more than 8.5 h and less than 24 h. Details of all the variables are publicly available at https://www.cdc.gov/nchs/nhanes/ (accessed on 29 July 2022).For this study, the exposure variable was SUA (mg/dL), and the outcome variables were ALT (U/L) and AST (U/L). SUA, ALT, and AST were measured with a Beckman Synchron LX20 between 2005 and 2007 and a Beckman UniCel DxC800 from 2008 to 2012. Hyperuricemia was defined as an SUA level >7 mg/dL in men and >6 mg/dL in women . Serum A®, Vienna, Austria) and EmpowerStats  for the statistical analyses in this study. Continuous variables were displayed as a mean ± SD or median (IQR), and categorical variables were expressed as weighted percentages (%). A linear regression model was used for comparisons between continuous data, and the chi-square test was used for comparisons between categorical variables. First, the correlation of SUA with ALT and AST was analyzed in three different models using a weighted multiple linear regression model. Model 1 was an unadjusted variable model. Model 2 was adjusted for the recognized confounding factors . Model 3 was a model that was adjusted for all covariates, which were previously reported. SUA quartiles were grouped for analysis, and the median of the SUA quartiles was used as a continuous variable for the trend analysis, and SUA was grouped by hyperuricemia and normality. A stratified analysis by sex and race was also performed. Furthermore, to better display the relationship between SUA and ALT and AST, a generalized additive model and a smooth curve fitting plot were used to observe the linear or nonlinear relationship. Values were considered statistically significant if p-values were less than 0.05.We used R version , while HDD-C and PLT gradually decreased from Q1 to Q4 (p < 0.05) . The baseline characteristics of the subjects based on the SUA quartile are presented in  < 0.05) . In addip < 0.001). In addition, smooth curve fitting diagrams of the relationship between SUA and ALT and AST are shown  and in females  . SUA wasAfter stratification by race, SUA was positively correlated with ALT in Mexican American individuals , Non-Hispanic White individuals , and those of other races , except Non-Hispanic Black individuals  . In addiIn recent years, the association between SUA and NAFLD has been widely reported, while reports on SUA and liver enzymes are rare. Therefore, the purpose of our study was to investigate whether SUA was independently associated with ALT and AST in the U.S. population aged 20 years and older. There were two findings in this study. First, SUA was positively correlated with ALT and AST. SUA was also associated with the incidence of ALT elevation and AST elevation. The above associations were independent of all covariates. Second, the stratification analysis found that the SUA levels in Non-Hispanic Black individuals exhibited a nonlinear relationship with ALT and AST.Previous studies have shown that SUA levels are associated with the prevalence of NAFLD. A 5-year retrospective cohort study in Korea indicated that the risk of NAFLD increased with increasing SUA levels . In anotExisting studies show that there might be multiple mechanisms by which SUA caused liver dysfunction. Choi et al. suggested that uric acid-induced triglyceride accumulation could be mediated via a sterol regulatory element-binding protein 1 cleavage and nuclear translocation via induction of endoplasmic reticulum stress in hepatocytes . LanaspaIt was worth noting that we found that the relationship between SUA and ALT and AST showed a nonlinear relationship in Non-Hispanic Black individuals (an inverted U-shaped curve, as seen in Our study used a nationally representative sample from the United States, and the results were similar to the overall population. Furthermore, this is the first study to report the association between SUA and ALT and AST in Non-Hispanic Black individuals. However, there were some limitations of our study that deserve discussion. First, this study was a cross-sectional design, and there might be differences and biases in different covariates, which did not clarify their potential causality. Second, patients with cancer, diabetes, drug use behavior, and so on were excluded from this study. Therefore, we were not sure whether our findings were applicable to these special populations. In conclusion, further studies on the underlying mechanisms and prospective studies with large samples are needed to determine the exact mechanism of the association between SUA and ALT and AST.SUA was positively associated with ALT and AST in adults 20 years and older in the United States, independent of covariates. However, the SUA levels in Non-Hispanic Black individuals showed a non-linear relationship with both ALT and AST. When SUA reached a certain value, there was a negative correlation. Therefore, it is necessary to monitor or intervene in the liver function of people with elevated uric acid levels. However, this relationship may not apply to Non-Hispanic Black individuals. Therefore, it is necessary to improve screening, prevention, and intervention in patients with elevated uric acid levels in order to reduce the economic burden in the future.


Background. This work is a review of preclinical and clinical studies of the role of telomeres and telomerase in the development and progression of coronary heart disease (CHD). Materials and methods. A search for full-text publications  in English and Russian was carried out in the databases PubMed, Oxford University Press, Scopus, Web of Science, Springer, and E-library electronic library using keywords and their combinations. The search depth is 11 years (2010–2021). Results. The review suggests that the relative leukocyte telomere length (LTL) is associated with the development of socially significant and widespread cardiovascular diseases such as CHD and essential hypertension. At the same time, the interests of researchers are mainly focused on the study of the relative LTL in CHD. Conclusions. Despite the scientific and clinical significance of the analyzed studies of the relative length of human LTL as a biological marker of cardiovascular diseases, their implementation in real clinical practice is difficult due to differences in the design and methodology of the analyzed studies, as well as differences in the samples by gender, age, race, and ethnicity. The authors believe that clinical studies of the role of the relative length of leukocyte telomeres in adult patients with coronary heart disease are the most promising and require large multicenter studies with a unified design and methodology. Cardiovascular diseases (CVDs) are prevalent worldwide. In Europe, there were 19.9 million new cases of cardiovascular disease in 2017. There were 2.5 million new cases of CVD in Germany, 1.115 million in France, and 1.209 million new cases of CVD in the United Kingdom . CoronarGenetic factors have a significant impact on the risk of CVD. A history of CVD increases their future risk from 40% to 75% depending on the degree of the relationship  formulatDeoxyribonucleic acid (DNA) methylation and telomere shortening are considered potential molecular biomarkers of EVA . In a prIn recent years, blood leukocyte telomere length (LTL) has been considered a “mitotic clock” fixing human biological age  and as aAlso, as other early prognostic biochemical biomarkers of EVA, CVDs (atherosclerosis and CAD) are being actively studied: neutrophil gelatinase-associated lipocalin (NGAL) ; tissue In addition, biomarkers of the adverse outcomes of atherosclerosis and CAD  are being developed, among which LTL is of undoubted scientific and clinical interest ,20. ThisTelomeres (from the Greek telos “end” and meros “part”) are nucleoprotein structures located at the ends of chromosomes , consistTelomeres are bound to telomere-specific proteins that are part of the Shelterin complex. The Shelterin complex provides greater telomere stability and consists of six telomere-specific proteins: Telomeric Repeat Binding Factor 1 (TRF1); Telomeric Repeat Binding Factor 2 (TRF2); Telomeric Interacting Nuclear Factor 2 (TINF2 or TIN2), a complex consisting of TERF1 and Nuclear Factor 2; Protection of Telomeres 1 (POT1), a protein that provides telomere protection; Shelterin complex subunit and telomerase recruitment factor (TPP1), a subunit of Shelterin complex and telomerase recruitment factor; and TERF2 interacting protein (TERF2IP or RAP1), a protein that interacts with TERF2. All six proteins regulate telomere length .The interaction of the Shelterin protein complex with the telomere DNA sequence ensures the stabilization of the telomere structure and regulates the access of proteins involved in DNA elongation and repair. The TRF1 complex is involved in telomere length control by regulating telomerase access to the telomere sequence . The TRFTelomeres were first identified by Hermann Müller in 1938 and he and McClintock determined the protective role of telomeres in 1941 . The firTelomeres protect chromosome ends, maintaining genome integrity and stability ; telomerIn contrast to most somatic cells, hematopoietic stem cells, germ cells, keratinocytes in the basal layer of the epidermis, uterine endometrial cells, and cells from various tumors avoid telomere shortening by activating telomerase . TelomerTelomere shortening is associated with non-genetic  and genetic mechanisms of aging , as well as with social factors of aging  ,53. EVA The purpose of this systematic review is to find, analyze, and systematize studies on the relationship between LTL and CAD.Full-text publications were searched in the following databases: PubMed, Web of Science, Springer, Google Scholar, Oxford Press, Clinical Cases, Cochrane, and e-Library. We analyzed articles published between 10 January 2010 and 10 December 2021. Key words and their combinations were used to search for: “telomere length,” “stable coronary heart disease,” “humans,” “adults,” “coronary atherosclerosis,” “acute coronary syndrome,” “acute myocardial infarction,” “early vascular aging,” and “molecular predictors.”Publications were searched and selected using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A total of 278 articles were found using the keywords . We analFinally, we selected 14 suitable publications for our systematic review in which the authors used comparable methodological approaches to measure LTL using a T/S ratio and/or bp. This approach was important to be able to systematize the results of the analyzed studies. We analyzed but excluded from further processing publications with alternative methods of LTL calculation.We selected articles in which the relative LTL was measured by the method of Cawthon R. M. . This tep-value < 0.05.Statistical analysis of the obtained data was performed using the SPSS software package, version 23 . Since the size of compared samples was small (n ≤ 30), nonparametric statistics were used. Median (Me) and percentiles  were calculated for each of the three groups . The groups were compared using the Mann–Whitney test. Significance of differences was considered significant at a Our analysis of the studies demonstrates that the issue of LTL changing in patients with CAD has been extensively studied worldwide. The number of LTL studies on this disease is increasing in different age groups of patients and in different racial and ethnic groups compared with healthy controls . Thus, ip-value = 0.75).Hassler et al.  studied p-value = 0.850).In patients with stable CAD , the relp-value < 0.05).Mazidi et al.  found thp-value < 0.001). An interesting finding was that LTL was shorter in men than in women . The authors attributed this phenomenon to the higher estrogen levels in women. In addition, the study found that LTL was inversely correlated with age .Willeit et al.  in a prop-value < 0.001). This is indirect evidence of the decreased regenerative capacity of bone marrow cells and the decreased repair of blood vessel endothelium. A study by Wilson et al. [p-value < 0.001). Thus, LTL reflects vascular endotheliocyte telomere length, which allows us to use LTL assessment as a biomarker of vascular age, EVA, and human biological aging in various CVDs in adults.The possibility of using LTL as a molecular biomarker of human biological aging as it reflects the telomere length of endothelial cells has been confirmed by several studies. The study of Hammadah et al.  establisn et al.  revealedp-value < 0.001).Starnino et al.  found thp-value = 0.015). Thus, there was an association between LTL shortening and decreased plasma antioxidant capacity in patients with CAD.Tian et al.  analyzedp-value < 0.0001) but not with mortality from cerebrovascular disease and CVDs .Huang et al.  studied p-value = 0.058) [p-value = 0.026) [Yakhontov et al.  studied = 0.058) . Another= 0.058)  examined= 0.026) .Thus, in recent years, researchers and clinicians have been very interested in studying the relationship between LTL and stable CAD. The number of ongoing studies is increasing. However, the results obtained vary over a wide range, which may be due to differences in patient age, ethnicity and race, and region of residence. Nevertheless, there is no doubt that LTL is reduced in middle-aged and elderly adults developing stable CAD compared with healthy adult controls without CVD including CAD .p-value = 0.089).The number of LTL studies in patients with AMI is still significantly lower compared to LTL studies in patients with stable CAD. We found and analyzed five studies . In adulRusso et al.  found nop -value < 0.001).However, Gupta et al.  demonstrChan et al.  investigp-value < 0.001). However, after adjusting for age, smoking status, and type 2 diabetes mellitus, the differences between the groups were no longer significant . Thus, the authors concluded to the contrary that AMI was not associated with relative LTL in Czech women.Dlouha et al.  found thp-value = 0.008) and mortality from CVDs within the first year after AMI .A study by Margaritis et al.  determinThus, in patients with AMI, the relative LTL ranged from 0.115 CU  to 0.86 We found and analyzed a total of 17 publications including 5 studies conducted in Russia. However, three ,73,74 ofWe demonstrated that in studies of the mean relative LTL in young, middle-aged, and elderly adults, the value of this molecular biomarker decreases not only in relation to the physiological biological aging of the human body but also in relation to the premature development of stable CAD  and the Interestingly, the relative LTL in patients with AMI  is shortStudies of relative LTL in patients with AMI (predominantly) and with stable CAD (to a lesser extent) are in their infancy. Such studies are still in the minority, the sample sizes are small, and the results obtained in some studies are contradictory ,69,70,71p-value > 0.05). Nevertheless, this trend could be clarified by new, large, and multicenter studies with a similar design in the future.However, our systematic review of available publications demonstrated a trend toward shorter relative LTL in patients with AMI  compared with patients with stable CAD  and a healthy control group  . HoweverThus, CAD and arterial hypertension ,79,80,81The limitations of this systematic review include the analysis of publications in English and Russian only. It is possible that we missed some studies published in other languages that were not represented in the databases we analyzed.Another limitation of the review of published and available studies of relative LTL in adults with CVDs is the different methodological approaches of the investigators with regard to the study design, inclusion/exclusion criteria , and study duration . In addition, some authors used % rather than CU to estimate relative LTL.p-value < 0.005. However, the authors used an alternative method of measuring LTL—not in CU, but as a percentage compared to healthy controls. Due to the alternative LTL calculation methodology, the results of this study were also not included in our systematic review.Due to methodological problems , three Russian-language publications were excluded from the review. Thus, an interesting study is by Maximov et al. , in whicThe other main concern is that relative measured LTL cannot be compared between studies, but relative measured LTLs are comparable between groups inside one study. This is due to the fact that relative LTL measured as the T/S ratio measures the relative amount of telomeric DNA (T) to a single copy gene (S), calibrated to a plate reference genomic DNA sample. Therefore, and as this reference sample is unique for each study, the results on relative quantified LTLs are not directly comparable between studies.The association between LTL and EVA has had a limited focus in the present review and we therefore plan to include it in a future review of the relationship between EVA and LTL in young, middle-aged, and elderly patients.Despite the scientific and clinical significance of the analyzed studies on relative LTL as a molecular biomarker of CVDs, their translation into real clinical practice is difficult due to disparities in the design and methodology of the analyzed studies, including the studies on cell cultures and humans, as well as the differences in samples by gender, age, race, and ethnicity. The authors believe that clinical studies of the role of relative LTL in adult patients with CAD are the most promising and require large multicenter studies with a unified design and methodology.


Diabetes foot ulcers (DFUs) are a type of foot infection, ulcer, and/or deep tissue destruction caused by neuropathy and vascular disease in the distal extremities of diabetic patients. Its pathogenesis and its microenvironment are not entirely understood.Initially, the GSE165816 data set from the GEO database was utilized for single cell analysis to reveal the microenvironment and functional status of DFUs. The GSE199939 RNA-seq data set was utilized for external validation. On the basis of the logistic regression machine learning algorithm (OCLR), pseudo time series analysis, dryness index analysis, and drug target gene analysis were then performed. By constructing drug-gene and gene-gene networks, we can locate the most recent DFUs treatments. Finally, immunofluorescence technology was used to detect the cell-related markers of the DFUs microenvironment, and qPCR was used to detect the expression of drug targets in DFUs.Firstly, we used the Cell Maker database to obtain information about human cells and related gene markers, and manually reviewed a total of 45 kinds of cells and maker information that may appear in the DFUs microenvironment, which were divided into 17 cell clusters after annotation. Subsequently, we counted the proportions of DM and DFUs in different types of cells, and the results showed that the proportions of macrophages, white blood cells, and monocytes were higher in patients with DFUs, while the proportions of pluripotent stem cells and stromal cells were higher in patients with DM. The Pseudo-time series analysis of cells in DFUs showed that the differentiation pathways of immune cells, mesenchymal cells and stem cells were similar in the three states, while the other cells were distributed in different stages. At the level of a single cell, the scores of both multipotential stem cells and hematopoietic stem cells were significantly lower in DFU healing and non-healing than in DM. Additionally, the highly expressed genes in DFU were chosen as drug targets. We identified seven potential target genes and discovered twenty drugs with high significance. Finally, the colocalization relationship between CD19, ITGAM, and HLA-DR expression in monocytes and macrophages of DFU skin tissue and healthy subjects was analyzed by laser confocal microscopy with the immunofluorescence triple labeling method. The results showed that the expressions of CD19, ITGAM, and HLA-DR in the skin of DFUs were significantly higher than those in the skin of healthy subjects, and the co-localization relationship was significant in DFUs.This study can serve as a resource for the treatment of DFUs. Diabetes foot ulcers (DFUs) are one of the most severe diabetic complications . Its etiCurrently, traditional intervention methods and DFU efficacy are unable to meet expectations . Stem ceThis article retrieves the GSE165816 DFUs patient dataset from the geo database . GSE1658Data on single-cell RNA sequencing (GSE165816 dataset) was acquired from the group of Georgios Theocharidis. The sequencing of 94,325 single cells from 33 DFUs samples resulted in the retention of 94,325 single cells after data processing, including quality control, data filtering, and normalization. In this study, only processed transcripts from foot skin samples of 11 healthy subjects (including 8 diabetics), 9 DFU healing, and 5 DFU non-healing were used. Cells were sequenced using the Illumina HiSeq 4000 platform .For downstream principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis, Seurat (Version 4.0.2) was configured with partial threshold settings. Cells with fewer than 200 genes were eliminated from consideration. Gene expression was scaled after being normalized with the LogNormalize method. Following data normalization, 2000 highly variable genes (HVGs) were identified for each sample using the “VST” method. Subsequently, PCA was used to identify significant principal components (PCs), and the JackStraw and ScoreJackStraw functions were used to visualize the P-value distribution. The “IntegrateData” function was used to correct batches in order to avoid the batch effect of sample identity, which could disrupt subsequent analysis. In the end, 30 PCs were chosen for t-SNE analysis. With a resolution of 0.8, the FindClusters function was used to classify the cells into eight distinct clusters. To identify differentially expressed genes (DEGs) for each cluster, the FindAllMarkers function was used with logfc.threshold = 1 and p-value <= 0.01.http://xteam.xbio.top/CellMarker/ or http://bio-bigdata.hrbmu.edu.cn/CellMarker/) for cell and maker information. Cells that might be in the microenvironment of the DFUs were examined by hand and put together with cells of the same type. Using Fisher’s exact test and Jacquard’s coefficient, the characteristic genes and cytomaker genes of each cluster were used to annotate cells. The cluster was annotated as the cell type with the lowest P value (P <= 0.05) and the highest Jacquard coefficient. If there is no cell type with a p-value P <= 0.05, it is labeled as unknown.Cellular annotation of DM and DFUs data We utilize the cellMaker database (The package Monocle (Version 3.0) was used to figure out the path of the cells, get count data from the samples, and figure out the negbinomial. The size method was utilized to normalize the data. The genes were constructed using the differential genes in each cluster as the locus, with QVAL < 0.01 serving as the selection criterion for differential genes. The dimension of the data was then reduced using the reverse graph embedding (DDRTree) algorithm, and the quasi-timing analysis was performed using the orderCells function. Using pseudotime and cell type, the plot cell trajectory function allows for the visualization of cell trajectory inference.via GO enrichment. During enrichment, each enrichment term has a GO ID number. The unique GO ID number can be obtained through the enrichment of differential genes, followed by the enrichment of those genes into various pathways. KEGG is mostly about signaling pathways, and its database can add different genes to different pathways.For GO\KEGG enrichment analysis of DFUs and healthy subject-specific genes, clusterProfiler packages were utilized to identify significantly enriched pathways with a p <= 0.05 cutoff, and the top 20 pathways were chosen for display.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG) are gene function and structure enrichment databases, respectively. In sequencing the genome or transcriptome, it is common to find different genes in various individuals or populations. The analysis of differential genes may reveal the causes of individual or group differences. Differential genes can be enriched in biological processes, cell distribution, structure, and function The GEO database’s TPM data for GSE199939 was extracted using the GEOquery package. Using the limma package, DEGs were determined. Significantly dysregulated genes were determined to have a P value < 0.05 and an absolute log2(FC) > 1.https://www.synapse.org) were used as training data. Following training, the dryness of hematopoietic stem cells and pluripotent stem cells in ulcer microenvironments of DFUs and DM patients was evaluated, as well as the dryness of bulk-level samples.All expression data of a specific cell type were first extracted for dry evaluation at the level of a single cell, and then all expression values of the same cell in the same patient were averaged to form the gene expression data of the cell in the patient.The OCLR algorithm is a logistic regression machine learning algorithm  published in Cell in 2018 that measures the level of moisture in tumor samples. In this paper, the microenvironment and relative humidity of DFUs are evaluated. We characterized sample dryness at the level of gene expression using mRNAsi scores. Human stem cell datasets provided by the Progenitor Cell Biology Consortium (PCBC) (https://www.dgidb.org/) was utilized to obtain drugs associated with potential drug target genes, as well as other genes associated with this drug. Using bulk data, the Spearman correlation coefficient between drug-related genes was calculated, and significant co-expressed gene pairs were identified using the criteria p <= 0.05 and COR > 0.70. Thus, drug-gene and gene-gene pairs were generated to construct the drug-gene network, which was visualized using cytoscape 3.8.2. For the drug-gene network, potential drug targets were used as seed nodes to evaluate the significance of drugs using the WGCNA algorithm. The chance of starting over is 0.1, and the iteration keeps going until the difference between this iteration’s results and the results of the previous iteration is 10-10. This is done to figure out how much each drug weighs.The DGIdb database . In addition, 12 healthy individuals who underwent physical examination in our hospital during the same time period were recruited as the healthy control (HC) group. This group consisted of nine males and three females, with an average age of 58.23 ± 15.48 years. In terms of gender ratio and age, there was no significant difference among the three groups . In the morning, 10 ml of fasting blood was drawn from each subject’s cubital vein into a heparin anticoagulant tube, centrifuged for 20 minutes at 3500 rpm/min, and the serum was separated and stored at -80°C. Six cases of foot skin tissue from diabetic foot ulcers and six cases of healthy people were chosen and fixed with formalin. Immunofluorescence detection was then used to find the disease.The paraffin sections were put into water and placed in a repair box filled with citric acid (PH6.0) antigen repair solution in a microwave oven for antigen repair. After the sections were slightly dried, a tissue chemical pen was used to draw a circle around the tissue, and the primary antibody and secondary antibody were added and incubated for 50 minutes at room temperature in the dark. The slides were placed in PBS (PH7.4) and washed on a decolorization shaker for 3 times, 5 minutes each time. The auto fluorescence quencher was added to the ring for 5 minutes and rinsed with running water for 20 minutes. DAPI counter stained nuclei were slightly dried and then sealed with anti-fluorescence quenched tablets. Then the sections were observed under a fluorescence microscope and images were collected.Using the TRIzol reagent, total RNAs from the plasma were extracted and reverse-transcribed into cDNA. The PCR reaction was comprised of 40 cycles of denaturation at 95°C for 10 minutes, annealing at 60°C for 1 minute, and extension at 95°C for 15 seconds. As the internal standard, Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was utilized. The levels of related factors’ expression were determined using a PCR reaction with 40 cycles of denaturation at 94°C for 15 minutes, annealing at 55°C for 30 seconds, and extension at 70°C for 1 minute. GAPDH was used as an internal reference. Each experiment was conducted a minimum of three times. Using the 2-Ct (cycle threshold (CT)) formula, the relative concentrations of ANPEP, BID, CYBA, CYBB, FCER1G, ITGA1, and PLAUR were calculated.Our workflow diagram is depicted in To integrate different samples, we first analyzed the single-cell sequencing dataset GSE165816 from DUF. Using the k-nearest neighbor (KNN) clustering algorithm, 94,325 cells were grouped into 29 clusters  > 1 as the threshold and then intersected them with characteristic genes corresponding to specific clusters. In the skin of normal people’s feet, 64 characteristic genes and 77 DFU characteristic genes were identified. A GO functional enrichment analysis was performed . As a measure of the gene’s overall expression in the DFU microenvironment, the average expression of a gene in a patient’s pluripotent stem cells or hematopoietic stem cells was used. The OCLR algorithm was then utilized to assess the hematopoietic and pluripotent stem cells of each patient Table S4Based on the aforementioned analysis, we discovered that monocytes, hematopoietic stem cells, and pluripotent stem cells are the primary distinct cell populations in the ulcer microenvironment of DM and DFU patients. In light of these three cell types, we were able to identify possible drug targets. Then, utilizing bulk data, we assessed the differences between the drug target genes that had been screened initially in DFUs and in healthy patients Table S5Plasma tissues from 22 DFUs patients and 12 healthy subjects were clinically collected to further support the hypothesis that the genes screened above are related to the immune microenvironment of DFUs. ANPEP, BID, CYBA, CYBB, FCER1G, ITGA1, and PLAUR mRNA expression levels were first discovered in the blood by qRT-PCR. We noticed that the blood of DFUs patients had significantly higher expression levels of ANPEP, BID, CYBA, CYBB, FCER1G, ITGA1, and PLAUR Table S6Diabetes patients frequently develop diabetic foot ulcers, also referred to as diabetic acrogangrene. Local tissue ischemia, neuropathy, and infection work in concert to almost completely predict its occurrence . DiabeteSingle-cell sequencing of tissues produced 94,325 cells’ worth of sequencing information. The age of diabetic and diabetic foot cells in various cell types was calculated. Leukocytes and monocytes were the most common types of cells in the DFUs cell population. In the diabetic cell population, pluripotent stem cells and stromal cells were the most common types of cells, showing that cells come from many different places. In the original paper about data mining, the author used 54 samples from 17 patients to conduct 21 cell clustering. In this study, smooth muscle cells, SMCs, fibroblasts, Fibro, vascular endothelial cells, VasEndo, T-lymphocytes, T-lympho, CD14+ monocytes, CD14-mono, differentiated keratinocytes, DiffKera, and basal keratinocytes, BasalK were analyzed. This is basically consistent with the study of DFUs microenvironment clustering cells in this paper. But the data we used was not completely consistent, and we only extracted 33 samples for analysis. In the process of cell annotation, annotation results are affected by annotation methods and maker sets. The dimensionality reduction clustering methods, annotation methods, and maker sets of our original text are all different, so the results may be different to some extent. But there is no gold standard for judging the accuracy of annotation, and the results of our cell annotation are based on the results of calculations and manual review, so it is reasonable to think that it has some accuracy.In addition, we discovered that in the three ulcer microenvironments of diabetes mellitus, DFUs non-union stage, and healing stage, macrophages, leukocytes, and monocytes appeared earlier, stromal cells and pluripotent stem cells appeared later, and other cells were distributed at all stages. The majority of macrophages, according to the most recent research, are derived from blood monocytes, with the remainder coming from fetal liver monocytes and hematopoietic stem cells in the original hematopoietic tissue. From directional stem cells in bone marrow, monocytes gradually develop and mature into peripheral blood, enter the tissue through the vascular wall, and eventually develop into macrophages . The abiStem cell transplantation has emerged as a novel method of treating diabetic feet in recent years. According to research by Han Y et al., MSCS act in a paracrine manner to promote the development of new blood vessels and granulation tissues by secreting stromal cell-derived factor-1 (SDF-1), vascular epidermal growth factor (VEGF), basic fibroblast growth factor (bFGF), and hepatocyte growth factor (HGF) . EncouraFurther investigation revealed that the main distinct cell populations in the ulcer microenvironment of DM and DFU patients were monocytes, hematopoietic stem cells, and pluripotent stem cells. ANPEP, BID, CYBA, CYBB, FCER1G, ITGA1, and PLAUR were found to be seven drug target genes. To find potential drugs for DFUs treatment, drug-gene and gene-gene drug-gene network maps were created. In one study , diabetiAt the cellular and molecular levels, this study demonstrates similarities and differences in tissues from various clusters that could serve as potential targets for novel treatments for the advancement of DFUs. Despite the fact that 33 single-cell samples were obtained from data mining, this study was fully validated in 22 DFUs patients and 12 healthy subjects, as well as at the bulk level. Since each cell is a sample, the size of the sample is good enough for the analysis that will come next.Significant heterogeneity in the cell clusters was discovered through cluster analysis of cell subsets isolated from normal subjects, diabetic patients, and diabetic foot skin. A higher level of inflammation in DFUs tissues may be predicted by the high expression of macrophages, leukocytes, and monocytes in tissues, whereas a higher level of dryness in diabetes may be predicted by the high proportion of pluripotent stem cells and stromal cells. In addition, stromal cells and pluripotent stem cells showed up later, while other cells were dispersed at all stages in the ulcer microenvironment of diabetes mellitus and DFUs healing and non-healing. Leukocytes, macrophages, and monocytes also showed up earlier. Differences in the number and activity of particular cells are predictive of changes in the DFU microenvironment, rather than the timing of the emergence of particular cells. Between cell ages percentage, DFUs patients had significantly more macrophages than DM patients with pluripotent stem cells did. This suggests even more strongly that dryness and inflammation are key elements influencing DFUs. The results of the overall expression values of hematopoietic or pluripotent stem cells suggest that DFU patients may have a certain number of stem cells, or even more than normal people (possibly related to the body’s self-protection), but that their activity is lower than that of normal people due to the restrictions of their own conditions. DFUs have a poor prognosis in comparison to healthy individuals because it is challenging to heal. ANPEP, BID, CYBA, CYBB, FCER1G, ITGA1, PLAUR, and other genes were significantly overexpressed as drug targets in the DFUs microenvironment. The Drug Gene Network identified CYCLOSPORINE, SIMVASTATIN, CURCUMIN, LUTEOLIN, APIGENIN, and CHRYSIN drugs with potential DFUs.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The studies involving human participants were reviewed and approved by Medical Ethics Committee of Jinshan Hospital affiliated to Fudan University ( JIEC 2021-S44 and IEC-JIEC 2021). The patients/participants provided their written informed consent to participate in this study.In this study, all authors participated in the conception and design; YL conceived and wrote the paper; SJ, XL, and WL processed the data; SZ, GW, and YC drew the figures. All authors contributed to the article and approved the submitted version.


This study aimed to explore the effects of different types of social participation on the components of well-being, as well as the differences according to sex in the relationship between social participation and well-being. This was a cross-sectional community study. Well-being was measured using the positive emotion, engagement, relationships, meaning, and accomplishment (PERMA) profile. Social participation included activities of daily life, sports and entertainment activities, and social service activities. The independent association between each type of social participation and the components of well-being was examined by using a network analysis in both males and females. Of all 1276 participants surveyed, 60% were females. The results of the network analysis showed that positive emotion–housework (0.263), positive emotion–games (0.102), engagement–housework (0.107), engagement–work (0.054), and meaning–socializing (0.085) had unique connections in males; the average predictability in the network was 0.417. For females, positive emotion–physical activity (0.102), engagement–associations or societies (0.071), relationships–physical (0.090), relationships–socializing (0.092), and relationships–volunteering activities (0.133) had significant connections; the average predictability in the network was 0.358. Different types of social participation may have different effects on the components of well-being. Furthermore, differences according to sex in the relationship between social participation and well-being should be considered when formulating interventions to improve well-being. With the development of positive psychology, many researchers have considered well-being as their central research topic. Well-being is a measure of how well life goes for the person who lives it , which iSocial participation is fundamental to human involvement in life situations and is an important modifiable health determinant . It was Studies have found that males and females have different levels of well-being and social participation. It is widely acknowledged that there are differences according to sex in social construction ,17. The In addition, studies indicated that well-being was more significantly related to activities at home for females compared to males; for males, performing activities with others  may contribute to higher levels of well-being ,25. A stGiven the importance of social participation to well-being, this study probed the link between different types of social participation and the components of well-being in healthy adults, as well as examined whether there was a difference between them based on sex. From a theoretical perspective, we proposed the following hypotheses: (1) Social participation has a positive impact on an individual’s well-being; (2) different types of social participation have different effects on well-being and its components; and (3) there are differences according to sex between social participation and well-being.This was a cross-sectional community study. A convenient sample of participants was recruited using posters on community websites in Shandong Province, China, from October 2021 to January 2022. Brief information on the study, the participant criteria, and the contact information for the study investigator were provided on the study posters. Participants were included if they: (a) were between the ages of 18 and 65 years; (b) could read and understand Chinese; and (c) were willing to participate in the study. Those with any somatic disease condition that affected physical activity were excluded . This study was approved by the authors’ institutional ethics committee (2021-R-048) and all participants provided informed consent.Potential participants obtained questionnaires by scanning a QR code on the poster. A survey note accompanying the questionnaire informed participants of their anonymity, ensured voluntary participation in the study, and provided instructions on how to complete the questionnaire. We also stated the length of time it would take to complete the survey (5~10 min). The survey could only be submitted when participants completed all questions; therefore, there were no missing data. Participants completed the questionnaire via an online link and submitted it directly to the network questionnaire platform. To ensure the quality of the survey, only one questionnaire per IP address was accepted. A final total of 1276 participants were included in the analysis.Participants provided sociodemographic information such as age, sex, marital status, education, and economic condition. Marital status ), education , and economic condition  were the categorical variables.Participation in social activities was assessed using a researcher-designed questionnaire according to Levasseur’s framework  that maiThe PERMA Profiler was used to evaluate individuals’ well-being levels . The PERp < 0.05 was considered statistically significant.All analyses were performed using IBM SPSS , R 4.0.2 , and a variety of R packages. The continuous variables were presented as the mean (M) and standard deviation (SD). The categorical variables were reported as frequencies and percentages. The test level was 2-sided; k = 2) and extended Bayesian information criterion (EBIC) to select the LASSO regularization parameter, which was applied and set at 0.5 to estimate the network structure. The thickness of each edge in the visualized network indicated the strength of the connection, with thicker edges indicating a stronger relationship [A mixed graphical model (MGM) was used to estimate network structure  among sotionship .Given that our primary objective was to assess the associations between variables, predictability was selected as an index to evaluate the significance of nodes in the generated network structure. For this reason, we only discussed predictability in this study and did not consider other parameters. Predictability measurements, which indicate the amount of variance explained by all other nodes in the network, quantify the extent to which a node is related by determining how well it can be predicted by all the other nodes in a network structure . We compIn addition, the NetworkComparisonTest (NCT) package was used to evaluate network structure differences between male and female networks. A network structure invariance test was run to examine whether the global network structure differed between the two networks by comparing the distributions of edge weights. The global strength invariance test was used to compare the weighted absolute sum of edge weights of two networks ,33.p = 0.053). There was no difference in accomplishment and meaning between male and female groups.The five components of well-being  scored 20.18, 20.06, 20.75, 20.93, and 21.56, respectively, for the overall sample. Females were more likely to report better positive emotions and relationships than males. Engagement was reported to be marginally statistically significant . Games, donation and volunteering activities had the least attendance (participation rate < 40%). Regarding sex differences in social participation, the participation rates in housework and physical activities were higher for females than males. Nevertheless, males had a higher participation rate in sports and games activities than females. There were no sex differences in the other types of social participation .Among social participation and well-being, the edge between positive emotion–housework (0.263), positive emotion–games (0.102), engagement–housework (0.107), engagement–work (0.054), and meaning–socializing (0.085) had significant weights that showed a unique connection.The predictability values of well-being were in the following order: meaning (variance = 0.814), accomplishment (variance = 0.805), positive emotion (variance = 0.765), relationships (variance = 0.600), and engagement (variance = 0.595), indicating that they were well predicted by other nodes in the network. In addition, the average predictability of all the nodes in the network was 0.417.Among social participation and well-being, the edges between positive emotion–physical activity (0.102), engagement–associations or societies (0.071), relationships–physical activity (0.090), relationships–socializing (0.092) and relationships–volunteering activities (0.133) had significant connections based on their weights.The predictability values of well-being were in the following order: meaning (variance = 0.848), accomplishment (variance = 0.817), positive emotion (variance = 0.806), relationships (variance = 0.697), and engagement (variance = 0.659), indicating that they were well predicted by the other nodes in the network. The average predictability of all nodes in the network was 0.358.p = 0.194) and global strength invariance (p = 0.879). It followed that the overall structure of the two networks was similar but the internal associations were different.The NCT analysis that compared the network between males and females showed no significant differences in network structure invariance  and there were differences according to sex between the two in the community population. Therefore, all three hypotheses of the study were confirmed. We first investigated the level of well-being and compared the differences based on sex. The scores for the five components of well-being in the overall sample were similar to the findings of a previous study among healthy adults . CompareIn addition, we found differences according to sex in the types of participation in social activities. Compared with males, females have a higher proportion of participation in housework and physical activities and males were more likely to engage in sports and game activities than females. Intuitively, differences according to sex in social participation might nonetheless be expected given the existence of sex-differentiated physical fitness and social roles. In addition, interests and life experiences usually differ along certain lines for males and females . These fFurthermore, this study explored the effects of different types of social participation on well-being  and examined the differences between them according to sex. Given that the complex associations among socio-demographic strata and different types of social participation might contribute to the various components of well-being, we adopted the MGM to understand the pairwise associations among them in both male and female samples. Although the overall structures of the two networks were not different, the internal associations between them were different. For males, after controlling for potential confounding factors such as age, marital status, education, and economic condition, housework was related to positive emotions and engagement. A plausible explanation for the results is that most of these activities are performed by females due to societal views and expectations . Under sWith respect to females, well-being was associated with physical, socializing, and volunteering activities. Research has documented that social activities are beneficial to well-being ,43, but This study had several limitations and the results should be interpreted with caution. First, the cross-sectional study design was limited in identifying the dynamic relationship between social participation and well-being. Second, the community samples were obtained from only one region of China that did not represent all Chinese individuals. In addition, according to the results, the average predictability of the network structure was 0.417 and 0.358 for the male and female groups, respectively. Therefore, some unmeasured confounders  should be considered in future research. Third, although we considered various types of social participation, this range remained difficult to cover. In addition, we failed to consider the degree of social participation, willingness, and initiative to participate. Fourth, the data in this study were collected during the COVID-19 pandemic, which potentially affected people’s social activities and levels of well-being. This may have limited the representativeness of the results. Finally, the self-reported nature of the data might have led to bias to some extent.In summary, males and females had different levels/types of well-being and social participation. There were also differences according to sex between social participation and well-being. Housework, games, and work activities were more strongly linked to well-being in males; for females, physical, socializing, and volunteering activities and memberships in associations or societies were related to greater levels of well-being. When considered from a public health perspective, this study offers a foundation for examining how specific activities are related to well-being in a community population and presents a more realistic description of the types of social activities in which they engage, which would most likely provide support to enhance public well-being. The government and media could actively publicize and encourage males and females to engage in different types of social activities. Therefore, it is important to identify the heterogeneity in the types of social activities according to sex. More studies in the future are required to identify the underlying mechanisms of sex in the relationship between social participation and well-being. Given the various types of social participation and components of well-being, the network analysis is a promising approach to exploring the complex associations between multiple variables.


Spermatogenesis is a complicated course of several rigorous restrained steps that spermatogonial stem cells undergo to develop into highly specialized spermatozoa; however, specific genes and signal pathways, which regulate the amplification, differentiation and maturation of these cells, remain unclear. We performed bioinformatics analyses to investigate the dynamic changes of the gene expression patterns at three time points in the course of the first wave of rat spermatogenesis. Differently expressed genes (DEGs) were identified, and the features of DEGs were further analyzed with GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) and Short Time-series Expression Miner (STEM). A total of 2954 differentially expressed genes were identified. By using STEM, the top 10 key genes were selected in the profile according to the enrichment results, and the distinguishable biological functions encoded by these DEGs were automatically divided into three parts. Genes from 6, 8 and 10 days were related to biosynthesis, immune response and cell junction, and genes from 14, 15 and 16 days were related to energy metabolic pathways. The results also suggest that genes from 29, 31 and 35 days may shift metabolic to sperm motility, sperm flagellum and cilium movement. Male germ cells are a highly specialized type of cells, and they undergo significant morphological, biochemical and molecular changes during their development. Those cells start from the first germline cells in the embryo, Primordial germ cells (PGCs), and end with the production of haploid matured sperm . In maleThe rat testis contains hundreds of seminiferous tubules, which include germ cells at different developmental periods during spermatogenesis. In order to characterize the changes during spermatogenesis, we should determine all the time points when those changes are occurring. Timing is critical for tissue development in transcriptomic studies, and luckily, the timeline for the first wave of spermatogenesis in rats has been established . ThroughThe mRNA population specifies a cell’s identity and helps to govern its present and future activities . RNA seqHere, the differences in gene expression during the first wave of spermatogenesis in rats were analyzed. Total testicular tissue samples were collected at three critical time points: at PND 6, 8 and 10, PND 14, 15 and 16, and at PND 29, 31 and 35. Currently, almost all the studies about testicular development and spermatogenesis are concentrated on mice or humans. The complicated physiology of the rat reflects many human traits, which could provide the ability to delve into the potential pathways and regulatory mechanisms of polygenic diseases. This study provides a very valuable basis for studying the genetic genes of male fertility and their regulatory and influencing pathways.Wistar-Imamichi rats were placed in 12 h of light/12 h of darkness and allowed autonomous intake of water and food. Male and female rats naturally mate. Day 1 means the date of the rat’s birth. Rat pups were separately killed by cervical dislocation method on PND 6, 8, 10, 14, 15, 16, 29, 31 and 35, and testes were collected. At least three testes from different litters were collected at each time point. All procedures were performed in accordance with the NIH Guide for the Care and Use of Laboratory Animals.Whole testes from rats of each time point were collected and snap-frozen in liquid nitrogen and stored at −80 °C prior to RNA extraction. The three phases of the measured microarrays were based on each stage of spermatogenesis in rats. The samples were sequenced by KangChen Bio-technology Co, Shanghai, China. A total of 27 samples of testes were used in the study.Samples were collected at different time points in the course of the first wave of rat spermatogenesis. Each time point represents a different stage of development in the testis. PNDs 6, 8 and 10 are the first time points when most SSCs are present in the seminiferous tubules, and S was used to represent this time point. The second time point was selected at PNDs 14, 15 and 16 when meiosis began, and M was used to represent this time point. The last time point was at PNDs 29, 31 and 35, at which time the testis contained round and elongating spermatids, and R was used to represent this time point.Microarray experiments were conducted by KangChen Bio-technology Co.  according to the standard procedure . Brieflyp-value, and the normalized gene intensity values were calculated as follows: FoldChange = ABS((average M/average SSCs) [p-value < 0.05. For R vs. M using the limma package, we required a p-value < 0.05 and |log2 FoldChange| > 3.For three periods, we identified the genes that are differentially expressed (DEGs) between two periods using the formula and limma package for the R language. For M vs. SSCs and R vs. SSCs, firstly, the gene intensity value was standardized, where xi is the gene intensity value, xj is the average gene intensity value of each sample, and stdxj is the standard deviation of the gene intensity value of each sample. There were 12,215 genes shared by SSCs and M, and 12,122 genes shared by SSCs and R. Secondly, FDR was calculated to correct the ge SSCs) ,14. Finap-value < 0.01 were considered significantly enriched.The DEGs functional enrichment analyses were conducted using the Metascape . Three mhttps://www.cs.cmu.edu/~jernst/st/; accessed on 10 December 2020). The union of DEGs in M vs. SSCs, R vs. SSCs and R vs. M testes was categorized into five profiles. Subsequently, the Pearson correlation coefficient between genes in each profile was calculated to screen out R > 0.85 and p-value < 0.01, and the top ten key genes in the profile were selected according to the enrichment results, which may play a crucial role in gene interaction and regulation of spermatogenesis.Series cluster analysis was performed to determine DEG expression profiles in the STEM program , chromosome organization (GO: 0051276), intracellular protein-containing complex (GO: 0140535), transferase complex (GO: 1990234), cell division (GO: 0051301) and response to oxidative stress (GO: 0006979) in both the S vs. M and S vs. R stages. However, DEGs between M and S were enriched in the regulation of the protein catabolic process (G0: 0042176) and Alzheimer’s disease (rno: 05010). Furthermore, GO analysis between R vs. M revealed genes related to spermiogenesis and cytoskeleton, such as epithelial cilium movement involved in the extracellular fluid movement (GO: 0003351), microtubule organizing center (GO: 0005815), sperm principal piece (GO: 0097228), axonemal dynein complex assembly (GO: 0070286), acrosome assembly (GO: 0001675), sperm connecting piece (GO: 0097224), microtubule-associated complex (GO: 0005875), manchette (GO: 0002177), regulation of cilium movement (GO: 0003352), cilium (GO: 0005929), spermatogenesis (GO: 0007283) and acrosomal vesicle (GO: 0001669) A.p-values < 0.01. The heat map is complemented by an enrichment network in which each network node is represented by a pie chart, where the sector size is proportional to the number of genes originating from each gene list. This representation is designed as a visual illustration of the biology of selective or shared pathway clusters (Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed on these differentially expressed genes with a cut-off criterion of corrected clusters B.p-value < 0.01. The top 10 key genes in the profile were selected according to the enrichment results, and these genes may play a key role in gene interaction and regulation. Short-time sequence expression analysis of DEGs was performed to understand the change of gene expression trend in the range of dynamic time series. STEM analysis of the 2954 DEGs showed that there were five expression patterns in three stages of spermatogenesis, among which 953 DEGs in module 49 showed an increased expression trend in SSCs, M and R, while 894 DEGs in module 0 showed a decreasing expression trend. In module 1, 326 DEGs showed a trend of first rising and then downloading expressions. The S-stage cells are enriched in certain pathways on an extracellular exosome, and RNA and cadherin binding are involved in cell–cell adhesion, DNA-directed RNA polymerase activity, and so on . In series cluster analysis, we categorized the 2954 DEGs that were differentially expressed in three stages into five profiles . The numSpermatogenesis takes place in the wall of the seminiferous tubules and involves a multitude of sequential cell types. First, there are undifferentiated spermatogonia, among which lies a population of SSCs. SSCs can both self-renew and give rise to large numbers of spermatogonia . Second,Recently, there have been some studies on transcriptome profiling of the testis, but most of them are performed in mice. Up to now, almost every new drug has been tested on rats, and they have made great contributions to the pharmaceutical industry for decades. If we could understand the biology of the rat much better, then we could build perfect models of human disease which can be used to develop new drugs. Laiho A et al. showed that genes involved in gametogenesis, germ cell development, fertilization and sperm motility were up-regulated during the first wave of mouse spermatogenesis . This maThe study by Guo et al. provided valuable information regarding gene expression dynamics during human spermatogenesis . Their sThe first wave of spermatogenesis, bypassing the SSC step, was likely selected over evolutionary time because it permits the rapid generation of sperm, thereby bestowing fertility to young males . Based oOur data elucidate the diversity of expressed genes and signal pathways during the first wave of rat spermatogenesis and lays the ground for further studies of specific factors contributing to male fertility. The number of probes detected in the S, M and R stages was 19,683, 25,795 and 26,177, and the corresponding number of unique genes was 17,492, 17,269 and 17,359, respectively. The number of specifically expressed genes in the S, M and R stages was 4912, 744 and 926, respectively. Most genes have functions within biological process categories and are known to participate in spermatogenesis and testis development. These findings will help us to understand further how gene expression is regulated during spermatogenesis. In future studies, it will be critical to perform decisive experiments to investigate those transcription factors.


Background: This study aimed to verify the association between Sedentary Behavior (SB) and performance on cognitive function tests in middle-aged and elderly adults. Methods: This cross-sectional study included 6505 participants (55.2% women) of ELSA-Brasil, with a median age of 61 years. The different types of SB considered were sitting time and screen time. The scores obtained in the memory, language, and executive function tests were used to assess cognitive performance (CP). The association between SB and CP was assessed using linear regression. Results: For men, sitting time was associated with better performance in memory, language, and executive function tests. Screen time on the weekend, showed a favorable association with performance in the executive function test. Occupational screen time on weekdays was positively associated with language test performance. For women, sitting time and occupational screen time were positively associated with performance on memory tests. SB was favorably associated with performance in language tests and executive function tests. Conclusions: SB seems to favor CP in this population without evident dementia and with a high level of education. The type of SB  and the schooling seem to be of particular interest for cognitive performance. Neurological disorders are among the main causes of disability worldwide . DementiPrevious studies on a Brazilian cohort of adult and elderly workers identified several factors associated with performance on cognitive tests in this population, which were used as a proxy for cognitive function. Early exposure to adverse social conditions , the heaAmong the modifiable risk factors associated with dementia, the role of lifestyle is well recognized and is considered a relevant starting point for the prevention, delay, or reduction in cognitive decline . RegularTherefore, further studies are needed, especially in low- and middle-income countries where evidence of this association has not been identified and where the prevalence of dementia and the rate of population aging are increasing rapidly . In addiThus, this study aimed to verify the association between different types of sedentary behavior and performance on cognitive function tests in middle-aged and elderly adults. The elucidation of this association could help develop strategies to reduce the prevalence of dementia.This is a cross-sectional study with data from the first follow-up wave 2:2012–2014) of the ELSA-Brasil. The ELSA-Brasil was a multicenter cohort study launched in the year 2008 in six Brazilian capitals; the participants were 15,105 retired and active civil servants aged between 35 and 74 years. More details regarding the study design and cohort profile can be found in previous publications 12–2014 o. ELSA-BrAmong the 14,014 participants in the first follow-up (wave 2:2012–2014) of the ELSA-Brasil, 7248 individuals aged >55 years were eligible for this analysis because they had performed cognitive function tests. Of these, we excluded: (1) those with incomplete information for outcomes (n = 533), (2) those who reported having had a stroke (n = 113), (3) and those with incomplete data on the questionnaire on sedentary behavior (n = 97). The stroke patients were excluded due to possible impact on performance in cognitive tests. The final sample consisted of 6505 participants . After eThe response variables were total cognitive test scores that assessed memory, language, and executive function. The tests applied are part of the battery of neuropsychological tests Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) ,23 and aMemory: In assessing memory, tests were used to assess immediate and delayed memory, in addition to the ability to remember and distinguish correct words from a set of distractors. To examine immediate memory, the word list memory test was used ,23. In tLanguage: Tests of semantic verbal fluency (flora category) and phonemic fluency (letter A) were used to assess declarative and semantic memory and language ,23. In tExecutive function: The track B test assesses attention, concentration, psychomotor speed, and mental flexibility (executive function) . In thisThe higher the scores on the memory and language tests, the better the cognitive performance in these domains. On the other hand, the longer the time taken to complete Track B, the worse the participant’s performance. All tests were adapted and validated for the Brazilian population . PreviouSitting time: Participants were asked to report the average daily number of cumulative hours spent sitting on weekdays (Monday to Friday) and weekends (Saturday-Sunday) with the following questions: (a) How much time per day, on average, do you spend sitting during weekdays? (b) How much time per day, on average, do you spend sitting during the weekend?Screen Time: Participants were asked to report the average daily number of accumulated hours spent sitting in front of a screen .Thus, for the purposes of analysis, the following dimensions of sedentary behavior were considered: (1) time sitting during weekdays, (2) weekend sitting time, (3) leisure screen time during weekdays, (4) leisure screen time on the weekend, (5) weekday occupational screen time, and (6) weekend occupational screen time.Covariates in this study were self-reported using standardized questionnaires, or obtained through clinical procedures or standardized laboratory test measurements. Details of the procedures can be found in the literature ,28.Sociodemographic characteristics: Sex, race/skin color, marital status, and education were included in the study. Schooling was divided into four subgroups: <8 years (incomplete elementary school), 8 years (complete elementary school), 9–11 years (high school), and ≥12 years (higher education). Participants’ perception of the characteristics of the neighborhood   was alsoSocioeconomic position: It was evaluated according to the participant’s current socio-occupational class based on three aspects: (1) occupation, (2) expected income considering the educational level , and (3) reported income. The scores were summarized into three categories: high, medium, and low .Occupation: Occupations were organized into three categories: academic, administrative, and operational activities, as proposed by Machado et al. . ActivitHealth behaviors: Health behaviors included smoking , excessive alcohol consumption (≥210 g/week for men and ≥140 g/week for women), sleep (self-reported daily hours), and leisure-time physical activity. The practice of physical activity (PA) was measured using the International Physical Activity Questionnaire (IPAQ)  in the l2), diagnosis of diabetes , and hypertension (defined as systolic pressure >140 mmHg and/or diastolic pressure >90 mmHg and/or confirmed drug treatment for hypertension). Biochemical tests and weight check were performed under fasting conditions. The presence of depressive symptoms (at least two symptoms from Section G of the CIS-R) [Health indicators: Anthropometric nutritional status was evaluated by body mass index (kg/me CIS-R)  and selft-tests were used to verify the difference between the numerical variables, according to their normality. For variables with observed and expected frequencies less than five and minimum expected frequencies greater than or equal to 1, the likelihood ratio was used. For the variable referring to executive function, logarithmic transformation was applied to base 10 to make it approximately normal. As SB and performance on cognitive tests differed significantly between men and women, the analyses were stratified by sex. Single and multiple linear regressions were used to obtain associations between sedentary behavior domains  and test performance. Cognitive . Model 1 had simple associations between exposures and outcomes of interest; Model 2 had age-adjusted associations; and Model 3 had associations adjusted for variables associated with some of the outcomes (p < 0.05), in addition to those considered a priori as potential confounding factors . Multicollinearity was verified in Model 3 by determining the variance inflation factors (VIF), considering values of VIF >10 as multicollinearity problems. It is noteworthy that the variables “occupation” and “socioeconomic position” presented multicollinearity with each other. The first was prioritized to the detriment of the second because the latter comprises aspects related to occupation and income, which could cause other subsequent multicollinearity problems. Tests to evaluate assumptions of normality, linearity, and homoscedasticity confirmed the adequacy of the final model (Model 3). Statistical analyses were performed using Stata software  version 14. Statistical significance was set at p < 0.05.Data were expressed as absolute and relative frequencies and measures of central tendency (mean or median) and dispersion (standard deviation or interquartile range). Data normality was tested using histograms and the Kolmogorov–Smirnov test. Categorical variables were compared using Pearson’s chi-square test. Mann–Whitney and Student’s 2; IIQ:24.33–30.21 kg/m2). Nonetheless, most participants had a good or very good self-perception of health (80%). Regarding health behaviors, most participants did not report excessive alcohol intake (91.6%), were non-smokers (79.4%), were physically active (50.2%), and had a median of 6 h of sleep per day. Regarding performance on cognitive tests, the median score on the memory tests was 38 (IIQ 33–42), with a mean score of 28.8 (SD = 8.28) on the language tests, and a median time of 109 s (IIQ 81–157) in performing trial test part B. In the various aspects of sedentary behavior evaluated, it was observed that most of the sedentary time occurred during weekend which included time spent sitting  and leisure screen time .Significant differences were observed according to sex for almost all investigated variables. It is noteworthy that women had a higher level of education (55.7% with complete higher education), were more active (52.7%), performed better in cognitive tests, and spent less sitting and screen time than men .For both sexes, the higher the level of education and the higher the socioeconomic position, the higher the average score in the memory and language domains, and the lower the average time on the Part B trial. At all levels of education and socioeconomic position, women performed better on cognitive tests than men, except for the execution time of the trial test, where men of a higher socioeconomic position performed slightly better than women in the same position. It was also observed that active individuals performed better on the cognitive tests .p value 0.007 for men), and for occupational screen time during weekdays . Thus, after adjusting for potentially confounding variables, for every one-hour increase in sitting time during weekdays, there was a 0.12 increase in memory test scores for both men and women.Likewise, there was a statistically significant positive association between sedentary behavior and performance in language tests in both sexes. After adjusting for confounders (Model 3), in men, this association remained significant for weekdays  and weekends . In women, these associations remained significant for sitting time during weekdays , on the weekend , leisure screen time on the weekend , occupational screen time during weekdays  and on the weekend . Thus, for each one-hour increase in sitting time during weekdays, for example, there was an increase of 0.22 and 0.23 in the language test scores for men and women, respectively, after adjusting for factors of confusion.Regarding executive function, there was a significant inverse association with most sedentary behaviors. Thus, sitting time and screen time were associated with a shorter time to perform the Part B trial test. In men, sitting time during weekdays , on the weekend , leisure screen time on the weekend , occupational screen time during weekdays , and on the weekend  were associated with better performance on executive function tests, even after adjusting for confounding factors (Model 3). In women, there was also a significant inverse association between executive function and all sedentary behaviors analyzed (Model 3): sitting time during weekdays  and weekends , leisure screen time during weekdays  and on weekends , and occupational screen time during weekdays  and on the weekend .The results of the present study, based on a sample composed of adults and the elderly, from a middle-income country, without diagnosed dementia or previous stroke history, and with a high level of education, show a positive association between sedentary behavior and performance in cognitive tests measuring memory, language, and executive function. This is the first study to investigate this relationship in a population of adults and older adults in a middle-income country in South America.For men, sitting time (during weekdays and weekend) was associated with better performance on memory, language, and executive function tests. Weekday occupational screen time was favorably associated with performance on memory and executive function tests. Weekend screen time  was associated with better performance on the executive function test. For women, sitting time and occupational screen time, both during weekdays, were positively associated with performance in memory tests. In terms of performance on language tests, all types of sedentary behavior analyzed were favorably associated with it, except screen time during leisure time in the week. Likewise, a positive association was observed between executive function tests and all types of sedentary behavior.The association between sedentary behavior and cognitive function remains inconclusive. Some studies have identified unfavorable associations , others Our hypothesis is that the divergences identified in the literature can be explained by the different types of sedentary behavior and cognitive performance evaluated and by the characteristics of study participants.Different types of sedentary behavior seem to have different impacts on each cognitive skill assessed ,40. A laAdditionally, a recent study has suggested a classification of sedentary behavior . AccordiA cross-sectional study examined the association between sitting cognitive activity (CAS) and cognitive impairment in 5300 community-dwelling Japanese elderly individuals  without dementia, disability, and severe illness . The autAnother reason that may explain the conflicting results in the literature is the characteristics of the study samples. Cognitive performance can be strongly influenced by socio-demographic characteristics such as age and education ,45. The It is noteworthy that performance on all cognitive tests was worse among men than among women. These sex differences are not always identified and seem to depend on the assessed cognitive domain . In addiSome limitations of the present study must be considered. First, due to its cross-sectional nature, inferences about causality are not possible. In addition, the association between SB and cognitive decline could not be investigated since the ELSA-Brasil baseline does not include data on sedentary behavior, which makes it impossible to perform a longitudinal analysis of this association and, consequently, to assess the chronic effects of SB on cognitive function. We cannot rule out errors and bias in self-reported information on sitting time and screen time, which may have been underestimated. However, although objective data on SB  are more robust, they do not provide information about the context of sedentary behavior performed . It is aDespite these limitations, this study has several strengths. The ELSA is the largest epidemiological study in South America , with soFinally, there are some recommendations for future studies on this topic. To date, most studies have separately investigated the effect of each physical behavior  on health outcomes, disregarding the co-dependent nature of these data . ComposiThe current study adds new evidence to the emerging body of research on sedentary behavior, physical activity, and cognitive performance. We identified that different types of sedentary behavior showed a favorable relationship with performance on cognitive tests assessing memory, language, and executive function in a sample of adults and elderly people without evident dementia and with high schooling. Our findings underscore the need to examine, in addition to the amount of sitting and screen time, the type of sedentary behavior and the context in which it is performed.It is plausible that mentally active sedentary behaviors  may stimulate and favor cognitive performance. However, before promoting the benefits of sedentary behavior on cognitive performance, more studies are needed, especially prospective studies, considering more aspects of cognition and sedentary behavior, employing objective methods such as accelerometers and brain imaging, and more data analysis approaches. In this way, one can gain a better understanding of the nature and magnitude of these associations. Given that this area of research is still under development and that results in middle-income countries are scarce, our study provides information that may contribute to a better understanding of the association between sedentary behavior and performance on cognitive tests.We reiterate the importance of practicing physical activity and reducing the amount of time spent in sedentary behavior in accordance with current public health recommendations to promote the general health and well-being of the population.


Cyclamen graecum is native to the eastern Mediterranean. Its beautiful flowers with upswept pink petals appear during early autumn, after the summer drought period and before leaf expansion in late autumn. The floral and leaf development alternates with their cessation in early winter and late spring, respectively. Ecophysiological parameters and processes underlining the life-cycle of C. graecum have not previously been published. Seasonal fluctuations of sugars, starch, and free proline have been investigated in tubers, leaves, pedicels, and petals, as well as petal and leaf water status. At the whole plant level, the seasonal co-existence of leaves and flowers is marked by an elevated soluble sugar content, which was gradually reduced as the above-ground plant parts shed. The sugar content of petals and pedicels was lower than that of leaves and tubers. Leaf starch content increased from late autumn to spring and was comparable to that of tubers. The starch content in petals and pedicels was substantially lower than that of tubers and leaves. In tubers, monthly proline accumulation was sustained at relatively constant values. Although the partitioning of proline in various organs did not show a considerable seasonal variation, resulting in an unchanged profile of the trends between tubers, leaves, and flowers, the seasonal differences in proline accumulation were remarkable at the whole plant level. The pronounced petal proline content during the flowering period seems to be associated with the maintenance of floral turgor. Leaf proline content increased with the advance of the growth season. The values of leaf relative water content were sustained fairly constant before the senescence stage, but lower than the typical values of turgid and transpiring leaves. Relationships of the studied parameters with rainfall indicate the responsiveness of C. graecum to water availability in its habitat in the Mediterranean ecosystem.The geophyte  Cyclamen L. (Primulaceae) is commercially important and a very popular horticultural genus native to the area around the Mediterranean Basin [Cyclamen was mentioned as kyklaminos (κυκλάμινος) in Theophrastus’ writings (4th century BC) [Cyclamen species. The cultivated cyclamens are usually hybrids of the spring flowering species Cyclamen persicum.The geophytes exhibit a life-cycle associated with temporal separation of the vegetative phase from the flowering phase and possess perennial tubers, which support their annual growth ,2,3. Cycan Basin ,5,6. Wiltury BC) . The Cyctury BC)  recognizCyclamen graecum Link grows in the wild; it is a perennial, tuberous geophyte, naturally distributed in bushy, stony, and sunlit ground in southern parts of the mainland of Greece and Aegean islands, as well as in coastal areas of Turkey and Cyprus, sometimes being confined into crevices in rocks. Environmental conditions, especially temperature, control annual development and florogenesis in geophytes [C.graecum is an autumn flowering geophyte. Floral pedicels and leaf petioles arise from the upper part and/or the crown of the over summering, large, perennial tubers that have nodes marked by small buds [Cyclamen species with more than 30 chromosomes, e.g., C. persicum (2n = 48) and C. graecum (2n = 84), can develop very large tubers [C. graecum, thick anchor roots are developed between fibrous roots, from the center of the base of the tuber [C. graecum appear in November. The leaves are slightly angular with variegated green spots on the adaxial surface; parts of the adaxial leaf surface are light green and other parts are dark green, while the abaxial leaf surface is violet-mauve.eophytes . C.graeall buds ,11. It he tubers ,13. Actue tubers ,15. In Cum 2n = 4 and C. gpanis porcinus), a common name for the genus Cyclamen, is a reference to tubers supposedly being a favorable food for pigs [Partitioning of total sugars between plant parts is directly linked to developmental flux of carbon molecules, osmolytes, and energy . Moreovefor pigs ,20.Proline has proven to be a multi-functional tool in plant metabolism during the last two decades. Beyond its well-established roles as an osmoticum and generally a protectant against abiotic stresses , its invThe objective of this study was to identify and compare the partitioning of soluble sugars, starch, and proline among above- and below-ground plant parts of Cyclamen graecum, which are exposed to fluctuating environmental conditions, as well as the water status of petals and leaves, which according to the best of our knowledge has not hitherto been published, in order to evaluate ecophysiological traits of tissues exposed to ambient conditions.C. graecum is characterized by two phenological stages in the course of a year: the active phase (from flower emergence in September to leaf senescence in April) and the dormant phase spanning the prolonged drought period (from May to August) in the eastern Mediterranean, when the aboveground plant parts are not visible. Concerning the active phenological stage, the flowers splay open in September  and pedicels , while leaf sugar content was negatively related with that of tubers . In addition, the seasonal rainfall was negatively correlated with the sugar content of petals  and positively correlated with the sugar content of leaves .Tubers accumulated large quantities of soluble sugars throughout the year . A graduC. graecum was observed in April (256 mg g−1) when the climatic conditions were favorable for photosynthesis in the Mediterranean ecosystems, and before the cessation of foliar growth of C. graecum. Thereafter, from May to October, starch content declined (−1) were measured from June to October; actually, this period coincides the three-month summer drought (June to August), the cessation of foliar growth, and the early stage of flower formation in September, before the development of new expanding leaves in November (p < 0.05). The starch content in petals and pedicels was substantially lower than that of tubers and leaves during the flowering stage (from September to December) (−1 d.w.). Negative relationships were detected between petal starch content with the corresponding tuber starch content  and the precipitation in the study site .The highest starch content in tubers of declined . The lowNovember . IntermeNovember ; in factecember) . The relecember) , coincidThe partitioning of free proline in tubers, leaves, pedicels, and petals are presented in s) and turgor (Ψp) values were increased (less negative)  were found among sampling dates  were detected in September , after tegative) , and thees of Ψp , most prng dates .2 = 0.954, p < 0.05) and Ψs ; also, negative relations were detected between soluble sugars and Ψ , and Ψs , as well as between starch and Ψ  and Ψs , while a positive relationship between Ψp and proline content was found , as well as Ψp and soluble sugars .In petals, significant positive correlations were detected between Ψ and rainfall .The relative water content (RWC) of leaves was sustained fairly constant until March and declined in April . AdditioC. graecum confirms to their role in storing photoassimilates and providing a supply of energy to drive new growth [p < 0.05); starch partitioning may be linked to source-sink relationships; the photosynthetically active leaves (the source) provide assimilated carbon (available for transport) to a storage organ (sink), which will utilize it to support metabolic requirements. Furthermore, the elevated values of starch from February to April in both tubers and leaves coincide with the leaf photosynthetic efficiency, and the mild winter temperatures in the Mediterranean area that favor photosynthetic rates. It seems likely that in C. graecum, starch may represent a commitment of resources that are acquired by the above-ground tissues simultaneously with the growth of those drawn from stored reserves. This finding is in contrast to data published elsewhere for the summer flowering geophyte Pancratium maritimum, where starch was mainly stored in underground bulbs [The seasonal accumulation of starch and soluble sugars in the tubers of w growth ,25. The nd bulbs .2 = 0.881, p < 0.05). Floral growth during the early autumn takes precedence over allocation. A further decrease of soluble sugars in tubers at the period of leaf emergence indicates a translocation of stored sugars to sustain leaf development and floral exhibition, when winter lies ahead, via a transition from sink to source. The leaf sugar content during winter and spring denotes an active photosynthetic machinery for this species grown under ambient, environmental conditions, coinciding with the values of leaf RWC before wilting; leaf RWC may also be considered as a measure of the relative cellular volume, affecting interactions among macromolecules. Usually, levels of RWC below 70% imply a water potential at the order of −1.5 MPa or less, and this would cause changes in the metabolism with ceasing of photosynthesis [2 = 0.834, p < 0.05), presumably contributing to turgor maintenance, expansion and water status of these tissues [C. graecum, flower and leaf development are concomitantly exhibited only during a two-month period, i.e., November and December.At the phenological stage of flowering, when the ambient temperatures begin to fall, the concentration of soluble sugars in the tubers rapidly decreased to support the metabolically demanding reproductive growth with carbon source and energy ,28; thisynthesis , concomiynthesis . Concernynthesis . In peta tissues ,33,34. A tissues ,36,37,38C. graecum showed a small but statistically significant increase from November to March, compared to the rest of the year. This accumulation may be driven by the low temperatures of the corresponding months and may be considered a stress-related response. An analogous profile was followed by its leaves, resulting in unchanged partitioning of proline between leaves and tubers, when leaves are coming through during the life-cycle of C. graecum; nevertheless, the greatest variation was found between petal and leaf concentrations. It has been published that C. graecum is a cold-tolerant species [Proline content in tubers of  species ,39. The  species . Concern species , while i species . Additio species ,27,42. P species ,44,45,46C. graecum survives the hot summer in a state of dormancy. C. graecum blooms in autumn, before leaf emergence. Thereafter, leaves grow and accumulate metabolic reserves throughout the wet and cool season, until the dormancy period, which begins in late spring. In geophytes, long days can initiate the transition to bud dormancy [C. graecum is released from dormancy when the ambient temperatures decrease; hence, shifts from the vegetative to reproductive stage, and floral initiation and differentiation occur in the mature tubers [Ecophysiological traits of plant organs that are seasonally either renewed or shed may be a suitable criterion of plant’s adaptation to environmental conditions. dormancy ,48. The e tubers .P. maritimum and was attributed to a requirement for osmotic adjustment, because this geophyte is exposed to dry and saline ambient environmental conditions [C. graecum, has been highlighted during floral developmental processes that include dehydration, as spontaneously occurring during pollen formation or embryogenesis [Free proline accumulation in petals was remarkable and significantly increased compared to the other plant organs. Flowers exhibited a 2.5- to 5-fold enhanced proline content in comparison to tubers and 2- to 3-fold compared to leaves. The transportation of proline into the reproductive organs, even under non-stress conditions, has been repeatedly reported . Corrobonditions ,46. Multnditions . Low valogenesis ,52. Furtogenesis ,53.Cyclamen graecum Link distributed in the campus of the National and Kapodistrian University of Athens in Greece , at the foothills of Hymettus Mountain, where travertine limestone appears along discontinuities of strongly fractured gray dolomite limestone; also, father soil characteristics, texture, and composition have been previously published [C. graecum [C. graecum were sampled from a single stand of C. graecum surrounded by uniform Mediterranean phryganic vegetation [C. graecum [The study was conducted in naturally occurring patches of ublished ,55. Conc graecum , on a mogetation , at mont graecum  appear i graecum . Values v/v), in a shaker, and the extracts were filtered using Whatman # 2 filter paper. Soluble sugar concentration was investigated colorimetrically, according to a modified phenol-sulphuric acid method [+ Spectrophotometer, Biochrom, Cambridge, UK). The determination of starch was made in the residue after the extraction of sugars, using the anthrone method [−1 d.w.Soluble sugars were extracted from dry, finely powdered samples  that were placed in 10 mL 80% ethanol , and the homogenate filtered through Whatman # 2 filter paper; 2 mL of the filtrate reacted with acid-ninhydrin solution (2 mL) and glacial acetic acid (2 mL) in test tubes, which were placed in a water bath at 100 °C for 1 h, and the reaction terminated in an ice bath. After cooling, the reaction mixture was extracted with 4 mL toluene and homogenized in a vortex. The chromophore containing the toluene was aspirated from the aqueous phase and the absorbance was read at 520 nm; immediately after, the terminated reaction in glass tubes placed in an ice bath, using toluene as a blank sample and the spectrophotometer mentioned in paragraph 5.2. The proline concentration was estimated using a standard curve of relevant L-proline solutions  and calculated on a dry weight basis.Free proline content was determined colorimetrically on 4 mL samples of the condensed fluid extracted from the plant material ,64. The s) was measured using the same leaf discs after freezing and thawing [p) was calculated as the algebraic difference between Ψ and Ψs. The relative water content (RWC) of fully expanded leaves was determined according to the disc method [Petal water potential (Ψ) was measured psychometrically on 6 mm diameter fresh discs (five replicates) from fully expanded petals, which were placed in five C-52 psychrometric chambers  attached to a dew point psychrometer  using the psychrometer switchbox ; the time required for equilibration between the water vapor pressure of leaf sample and that of the psychrometer chamber was 2 h. The osmotic potential  was performed on the studied parameters at p < 0.05 and the Duncan’s multiple range test was applied for comparing the means. All statistical tests were performed using the SPSS statistical v. 23.0 . Regression analysis was used to determine relationships among results obtained by plant tissues of C. graecum and precipitation.The results are presented as mean ± Standard Error (SE). In order to determine differences in the studied parameters of plant parts of C. graecum is characterized by two phenological stages in the course of a year, the active phase (from flower emergence in September to leaf senescence in April), and the dormant phase spanning the prolonged drought period, when above-ground plant parts are not exposed to the severity of summer in the eastern Mediterranean. Partitioning patterns of soluble sugars, starch, and free proline in above- and below-ground parts of C. graecum contribute to the maintenance of its annual rhythm and phenophases in fluctuating environmental conditions. The remarkable concentration of proline in petals, in comparison to other plant parts during autumn, seems to be associated with the maintenance of their turgor; without turgor, the exposed petals to ambient environmental conditions of the sharply reflexed corolla of C. graecum could not be standing so firm and erect. The leaf relative water content was found lower than the typical values of turgid and transpiring leaves; this may indicate that leaves of C. graecum subjected to ambient conditions are not susceptible to low temperatures. However, further work will be required to fully test this hypothesis.The life form of