Low light stress increases the chalkiness of rice; however, this effect has not been fully characterized. In this study, we demonstrated that low light resulted in markedly decreased activity of ADP-glucose pyrophosphorylase in the grains and those of sucrose synthase and soluble starch synthase in the early period of grain filling. Furthermore, low light also resulted in decreased activities of granule-bound starch synthase and starch branching enzyme in the late period of grain filling. Therefore, the maximum and mean grain filling rates were reduced but the time to reach the maximum grain filling rates and effective grain filling period were increased by low light. Thus, it significantly decreased the grain weight at the maximum grain filling rate and grain weight and retarded the endosperm growth and development, leading to a loose arrangement of the amyloplasts and an increase in the chalkiness of the rice grains. Compared to the grains at the top panicle part, low light led to a greater decrease in the grain weight at the maximum grain filling rate and time to reach the grain weight at the maximum grain filling rate at the bottom panicle part, which contributed to an increase in chalkiness by increasing the rates of different chalky types at the bottom panicle part. In conclusion, low light disturbed starch synthesis in grains, thereby impeding the grain filling progress and increasing chalkiness, particularly for grains at the bottom panicle part. Rice grain quality has attracted considerable attention in recent years ,2. A higChalk5 [OsPK2 [qPCG1 [qACE9 [starch synthase I (SSI) markedly increases amylose content and granule-bound starch synthase (GBSS) activity in rice grains, thereby significantly increasing the CGR and CD owing to the disturbance in the structure and arrangement of starch granules [starch branching enzyme IIb (SBEIIb) gene expression results in the loose arrangement of round-shaped starch granules and the production of grains with a higher level of chalkiness or opacity [Chalkiness is primarily determined by the structure and arrangement of amyloplasts. Specifically, when amyloplasts are loosely arranged due to insufficient grain filling and delayed grain development, the light transmittance of the grains decreases; thus, they show a greater degree of chalkiness ,8. ChalkChalk5 , OsPK2 [5 [OsPK2 , qPCG1 [2 [qPCG1 , and qAC1 [qACE9 . An imba1 [qACE9 . For exagranules . Further opacity .Additionally, rice chalkiness is not only determined by the genetic background of the rice species but is also influenced by environmental factors ,16,17, sLight, an essential environmental factor that affects plant morphogenesis, directly influences the photosynthetic rate of plant leaves and regulates the carbon metabolism of crops ,24,25. HTherefore, in this study, we conducted a field control light intensity study in Wenjiang, Sichuan, China from 2018 to 2021 with the following primary objectives: (a) to investigate starch synthesis and characteristics of the filling progress of grains under LL, (b) to investigate the impact of LL on the variations in grain chalkiness at different panicle parts, and (c) to evaluate the relationship of starch synthesis and grain filling with chalkiness in rice. Our results would provide insights for improving rice grain quality in low light intensity regions.The panicle part significantly influenced the CGR between 2018 and 2020 and the CD in 2020 . CompareThe rates of different chalkiness types at different panicle parts in 2018 and 2019 are shown in The activities of the enzymes associated with starch synthesis initially increased and then decreased during grain filling . In geneR2 > 0.992  and light treatment  significantly affected the grain filling characteristics in 2020, and light treatment significantly affected these parameters in 2021 . Moreove1), middle (t1–t2), and late (t2–t3) periods , and tillering (32.4 kg ha−1) fertilizers were applied. The initial fertilizer application rate at panicle initiation was 43.2 kg ha−1, and, at the booting stage, it was 28.8 kg ha−1. Further, at the basal stage, 90 kg ha−1 of P2O5 (superphosphate) and 90 kg ha−1 of K2O (potassium chloride) were applied, and 90 kg ha−1 of K2O was applied as a spikelet-promoting fertilizer. Chemical pesticides, such as tricyclazole, validamycin, avermectin, and penoxsulam, were used to prevent yield loss caused by diseases, insects, and weeds.An LL field experiment was conducted in the Huihe farm of Sichuan Agricultural University , Wenjiang, Sichuan, China from 2018 to 2021. The meteorological conditions (from sowing to harvest) of the experimental site were recorded from sowing to harvest . FurtherDuring flowering, 300 panicles with the same growth trend were labeled on the same day in each plot from 2018 to 2021. As previously described by Deng et al. , approxi−1; pH: 7.2–7.4) was added and mixed well, followed by centrifugation. The supernatant was collected, and enzyme-linked immunosorbent assay (ELISA) was performed using an ELISA kit , as per the manufacturer’s instructions, to determine the activities of AGPase, SuS, SSS, GBSS, and SBE.The marked grains of approximately 30 labeled panicles were sampled on days 3, 6, 9, 12, 18, 24, and 30 after LL treatment in 2021. Each sample (0.1 g) was ground into a powder using liquid nitrogen. Thereafter, phosphate buffer saline (0.01 mol LGW represents the dry weight of the grain (mg), A represents the maximum dry weight of the grain (mg), t represents the time after labeling (days), and B, C, and D represent equation parameters. The growth rate was derived from Equation (1) as follows: In 2020, 10 labeled panicles were sampled on days 5, 10, 15, 20, 25, 30, 35, and 40, whereas, in 2021, they were sampled on days 6, 12, 18, 24, 30, 36, and 40. In each case, approximately 30 marked grains were randomly selected for the determination of the grain filling characteristics of the rice grains. Six grains were removed from the glumes at each sampling time and observed using a stereomicroscope  in 2020. Furthermore, 20 grains from each panicle part in 2020 and from bottom part in 2021 were removed from the glumes and dried until a steady weight was obtained. Thereafter, Richards equation (Equation (1)) was used to measure the increase in the weight of grains at the top and bottom panicle parts, and relevant parameters were also calculated as previously described by Richards  and Wei The respective equations (Equations (3)–(10)) were used to describe the filling characteristics of the rice grains as follows:1 and t2 (Equations (11) and (12)). The grain filling process was also assumed to be completed when the grain weight reached 99% A, and this time point was designated t3, Equation (13).The filling process could be divided into the early, middle, and late periods of grain filling . FurtherThe grain filling stage was determined by three grain filling periods, calculated as: 1, t2, and t3 into Equation (1), the corresponding grain weights W1, W2, and W3 were obtained, respectively. Additionally, the mean of the grain filling and contribution rates of the three stages were calculated as follows, respectively:Substituting tIn 2020, mature rice seeds of different types of chalkiness were transversely cut using a knife and observed using a scanning electron microscope  at an accelerating voltage in the range of 10–20 kV.The CGR and CD of rice grains were measured using a rice appearance quality detector . In 2018 and 2019, chalkiness types were categorized as white-belly, white-core, white-back, and full-white chalkiness according to the location of the chalkiness, and grains with more than two types of chalkiness were described as having mixed-white chalkiness.p < 0.05. Further, figures were drawn using the GraphPad Prism software v8.0.1 . The data shown in all tables and figures represent the mean of three replicates.The data were analyzed using the SPSS software v19.0 . Significant differences between treatments were determined by performing Tukey’s tests, and statistical significance was set at 1, t2, contribution rate of the middle grain filling period, and contribution rate of the late grain filling period, as well as a greater decrease in I, grain weight at maximum grain filling rate, mean grain filling rate during the early period, and contribution rate of the early grain filling period at the bottom panicle part than at the top of the spikelet. Therefore, a more substantial increase in CGR and CD was observed for the grains at the bottom panicle part under LL. Future research using LL stress should focus on reducing chalkiness by coordinating starch synthesis and enhancing the progress of grain filling of rice, particularly for grains at the bottom panicle part.In this study, we observed that the CGR and CD were significantly negatively associated with the mean grain filling rates, maximum grain filling rates, grain weight at maximum grain filling rate, and mean grain filling rate of the rice grains but positively correlated with the time for reaching the maximum filling rate, effective grain filling period, and inflection point values. Furthermore, LL markedly decreased the activity of AGPP and those of SuS and SSS at the early grain filling stage and GBSS and SBE after 12 DAF, which led to insufficient starch synthesis in rice grains under LL. Therefore, LL significantly decreased the mean grain filling rates and maximum grain filling rates and increased the time for reaching the maximum filling rate and effective grain filling period, leading to slower grain filling and poorer grain fullness. Thus, both CGR and CD were significantly increased by LL owing to the increases in white-core, white-belly, white-back, mixed-white, and full-white chalkiness rates with more loosely arranged amyloplasts in grains. Furthermore, LL led to a greater increase in time for reaching the maximum filling rate, t


BackgroundDiabetes has increased the risk for various other ailments in various organs of the body. This can be contributing to periodontitis also as it is the sixth complication related to diabetes mellitus. There is a bidirectional relationship between both. Given the high global prevalence of type-2 diabetes mellitus (T2DM) with periodontitis, it is of great importance to determine the link between periodontitis and microalbuminuria in T2DM patients, which shows early renal disease.MethodologyIn the present study, a total of 500 patients having T2DM were assessed for periodontitis using Community Periodontal Index (CPI). Anthropometric and biochemical measurements were obtained. Blood samples were estimated for glycemic control tests such as fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and lipid profile. The subjects who participated in the study were categorized into three groups depending on the albuminuria level. The data were tabulated and analyzed using SPSS Statistics software .ResultsOut of 500 T2DM subjects, 342 subjects had periodontitis. A statistically significant difference was found in FPG, HbA1c, total cholesterol (TC), triglycerides, and low-density lipoprotein (LDL) between subjects with periodontitis and without periodontitis using a t-test (p = <0.001). The prevalence of normoalbuminuria, micro-, and macroalbuminuria among periodontitis patients was 24.6%, 72.8%, and 2.6% respectively, and the Chi-square analysis revealed that was highly significant. In terms of albuminuria, one-way analysis of variance (ANOVA) revealed statistically significant differences among the periodontitis subjects for the following variables: inputs such as the number of teeth, diabetes mellitus (DM) duration, the level of LDL, and also the depth of the pocket. Intergroup comparison of variables among subjects with albuminuria using the statistical test of Tukey Post Hoc found that there is a significant difference between normoalbuminuria and microalbuminuria. CPI score, tooth mobility, smoking, education level, family income, tooth brushing duration, along with the use of other dental hygiene aids was also found to be statistically significant among subjects with periodontitis.ConclusionThe study concluded that T2DM patients had a higher incidence of microalbuminuria among individuals with periodontitis. These subjects also had significantly higher HbA1c and FPG levels than subjects with normoalbuminuria. In addition, subjects with periodontitis exhibited a significant reduction in the total teeth numbers present in the case of albuminuria. The longitudinal correlation between DM, microalbuminuria, and periodontitis could be further investigated in detail to explore possible pathways. According to current estimates, 463 million individuals in 2019 to 537 million in 2022 were estimated to have the world’s most common chronic disease - diabetes mellitus (DM). By 2045, there will likely be 700 million individuals worldwide residing with diabetes, with the prevalence expected to rise by approximately 50% during the following years [Patients with diabetes are much more likely to experience other health problems, like diabetic retinopathy, diabetic nephropathy, cardiovascular disease, and diabetic neuropathy. In light of the fact that less than 25% of patients with diabetes would ultimately experience a revolutionary decline in kidney function, prevention of diabetes-related severe issues, particularly chronic kidney disease (CKD) and cardiovascular dysfunction, is crucial for the management of T2DM . AdditioThe dental-related disease periodontitis and diabetes are both complex and severe diseases that have a known two-way relationship. The sixth most frequent consequence of diabetes mellitus is periodontal disease ,2,4-6. PAlbuminuria is a significant indicator of subclinical atherosclerosis, widespread microvascular dysfunction, and kidney damage, and it is linked to a higher chance of later cardiovascular morbidity in people with diabetes or hypertension, including in the common populace. It is widely known that patients with micro- or macroalbuminuria have more advanced pathology than those with a normal range of albuminuria. Microalbuminuria and periodontitis seem to be associated with systemic inflammation ,9. The mStudies show that microalbuminuria is widespread in the general populace, with a generality of 6.6% even in hypertensive or non-diabetic patients and that it also serves as a standalone dangerous factor for other types of metabolic dysfunction ,12. GiveStudy sampleThe study comprised 500 T2DM patients who were treated in a south Kerala outpatient clinic from January 2021 to April 2022. There were 260 males and 240 females, all with similar age distribution. The samples were collected from PMS Dental College, Kerala, and permitted by the Institutional Human Ethical Committee with the reference number, Ref. No. PMS/IEC/2019-20/38. Type-2 DM diagnosed by a diabetologist within a month, having 12 or more teeth between the ages of 31 and 65 years, and being free of other clinical conditions involving proteins in urine were the inclusion criteria.Type-1 diabetic patients and individuals with a history of any other routine health issues like atherosclerosis, retinopathy, liver cirrhosis, obstructive sleep apnea, and immunologic or mental disorders were not included. Before being enrolled in the current study, informed consent was signed by all participants. The procedures and study design were evaluated and approved by a member of the Institutional Ethical Committee, who was also responsible for ensuring that the research was carried out in accordance with the Declaration of Helsinki.Socioeconomic factorsThe study participants were interviewed regarding their cigarette smoking habits, daily alcohol intake, routine exercise, education status, and monthly family income. Patients were categorized as ever smokers or non-smokers on the basis of their responses to the individual-reported valid questions. Participants who had smoked a minimum of five packets of cigarettes during their entire life were considered to be "ever-smokers". Based on the daily alcohol consumption during the last four weeks prior to the self-interview, patients were divided into non-drinkers, moderate drinkers (4 to 14 drinks per week), or strong drinkers (more than two drinks per day).According to the IPAQ  short form , patientAnthropometric, biochemical measurements and definitionsSkilled staff members obtained anthropometric and biochemical measurements. In a standing position, the waist circumference was gauged at the point where the iliac crest and the lower border of the rib cage meet. All study participants received a complete clinical examination that involved measuring their height, weight, and body mass index (Kg/m2). An individual was deemed obese with a BMI of 25 Kg/m2 . A BloodPatients with hypertension were those who were on antihypertensive drugs, who had systolic and/or diastolic blood pressure readings more than 140 mmHg, and 90 mmHg, respectively. For avoiding diurnal variation, a fasting blood sample (5 ml) was taken between 7:30 and 8:30 AM. Overnight fasting of 08-10 hours is recommended for performing the following laboratory tests: fasting plasma glucose, fasting lipid profile; test includes triglycerides (TGL), total cholesterol (TC), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL).Commercial kits were used to perform biochemical analysis on the Fully Automated Analyzer- Beckman Coulter (USA). All patients' FPG, TC, and TGL were measured. Using the Beckman Coulter AU480 fully automatic biochemistry analyzer, FPG is measured by the Hexokinase method, TC is measured by the cholesterol oxidase phenol 4-amino antipyrine peroxidase (CHOD-PAP) method, and TGL by the glycerol phosphate oxidase-presence of peroxidase (GPO-POD) method, respectively. Although it was directly tested using readily available commercially available kits , the level of LDL was computed using the Friedewald formula . By usinA spot urine sample of 25 ml was taken for the immunoturbidimetric method of estimating albuminuria in the Agappe Nepheleometer . Normoalbuminuria (<30 mg/g), microalbuminuria (30 to 300 mg/g), and macroalbuminuria (>300 mg/g) were used to categorize the study subjects with T2DM. They were also sorted up into groups based on whether they received insulin, hypoglycemic pills, or just diet alone for diabetic management. Additionally noted were previous records of coronary artery disorder. Information about the consumption of fats lowering and/or antihypertensive medications was retrieved from their medical records.Oral health habits and periodontal statusOral health activities included brushing teeth on a regular basis and using other dental hygiene materials such as dental floss, mouth-rinse, an interdental brush, and a powered toothbrush. Dentists, who were qualified and experienced, evaluated periodontal health. Periodontitis was assessed by measuring the periodontal pocket depth (PD) using a calibrated University of North Carolina (UNC) - 15 probe and the loss of attachment (LoA) using the Community Periodontal Index (CPI) developed by the World Health Organization (WHO). A CPI score of 3 and/or 4 for PD was used to determine the presence of periodontitis. Codes 3 and 4 indicate that there were one or more sites in the index teeth with PD larger than 4 mm and 6 mm, respectively. The entire dentition was divided into six sextants represented by the index teeth 11, 16/17, 26/27, 31, 36/37, and 46/47. Scores of the index teeth often showed the periodontal health of each sextant.The WHO recommends CPI as an epidemiological tool, and it has been widely employed for assessing PD and LoA. In each segment, the CPI score with the highest PD/LoA was recorded. In our study, periodontitis was described as having a CPI code of 3 to 4 for PD and a CPI score value of 1 to 4 for LoA. The standardized dental chart contained data on the number of teeth present, tooth mobility, and CPI code/score. The tooth mobility was scored from 0 to 3 and was classified as either present or absent (score 0).Statistical analysisThe data were analyzed by using the SPSS Statistics for Windows, Version 26.0 . The Shapiro-Wilk test was utilized to ascertain if the data were usually assigned. For continuous and categorical variables, the data were reported as mean±SD and percentages, respectively. Chi-square tests for categorical variables, the Student's t-test, and analysis of variance (ANOVA) for continuous variables were used to determine the significance of differences between groups. Tukey Post Hoc test was used for intergroup comparison among the three groups in terms of albuminuria. A p-value of ≥0.05 is considered statistically significant.Out of 500 individuals with T2DM, 342 participants  had periodontitis, while 158 subjects did not (80 men and 78 women). The overall mean age was 54.7±6.6 years. The age and gender distribution between patients with and without periodontitis was determined to be statistically insignificant. Table In the study sample, 68.4% of participants had periodontitis. The likelihood of ever-smokers and poorer educational attainment with lower family income was statistically more in patients with periodontitis (p<0.001). The Chi-square test disclosed an insignificant difference between patients with and without periodontitis in the proportion of various diabetic therapies, anti-hypertensive/lipid-lowering medications, and the prevalence of recently identified diabetes, or hypertension. The groups did not significantly differ in terms of the cardiometabolic indicators, which include BMI, waist circumference, HDL, and systolic and diastolic blood pressure (p>0.05). However, there was an appreciable difference in FPG, HbA1c, TC, triglycerides, and LDL between persons with and without periodontitis using the t-test (p<0.001).Patients with periodontitis had significantly lesser teeth and had DM for longer periods of time. The usage of additional oral hygiene products and the frequency with which people clean their teeth each day were revealed to be statistically different between the two groups based on their periodontal status. The mean microalbuminuria was 247.76±5.8 mg/l in patients with periodontitis, compared to 200.81±5.04 mg/l in individuals without periodontitis (p<0.001). The majority of the participants (32.7%) with periodontitis had PD ≥4 mm at one or more areas and tooth mobility (19.6%) which was statistically significant. The prevalence of microalbuminuria was statistically significant and more common in patients with periodontitis .In terms of albuminuria, Table Normoalbuminuria, microalbuminuria, and macroalbuminuria were found in 24.6%, 72.8%, and 2.6%, respectively, in the participants with periodontitis. Participants with micro- and macroalbuminuria, had mean PD of 5.5±4.22 and 6±5.21 mm, respectively. One-way ANOVA was used to determine the statistical significance of the differences between the three groups based on albuminuria. The following characteristics showed statistically significant differences among the periodontitis subjects: smoking, education, family income, the number of teeth present, the duration of DM, LDL, the frequency of brushing, the use of other oral hygiene aids, tooth mobility, CPI score, and periodontal PD. When compared to participants with normoalbuminuria, those with micro- and macroalbuminuria had significantly higher HbA1c and FPG levels.As indicated in Table Patients with micro- and macroalbuminuria had significantly longer DM duration (p<0.05) than patients with normoalbuminuria. Smoking and educational status also revealed an appreciable difference between the three groups in subjects without periodontitis. The three categories did not vary notably in any other periodontal markers, including LDL, triglycerides, TC, brushing frequency, or family income. Table Systemic inflammation, which causes impaired pancreatic beta-cell activity, apoptosis, and insulin resistance, precedes type 2 diabetes. With more and more data pointing to heightened systemic inflammation (acute-phase and oxidative stress indicators) brought on by the circulation of periodontal organisms and their virulence factors, the link between periodontitis and diabetes is becoming biologically plausible. In the direction of the relationship between diabetes and periodontitis, AGE (Advanced Glycation Endproducts)-RAGE (Receptor for AGEs) interactions and oxidative-stress-mediated pathways offer potential molecular linkages .In diabetic nephropathy condition, one of the earliest signs in patients with microalbuminuria, the bidirectional relationship is evident due to more amount of lipid accumulation leading to microvascular changes in the blood supply and thus leading to degenerative changes in the collagen of the connective tissue. This in turn is responsible for the spread of periodontal disease. It is documented that persistent microalbuminuria increases the risk of overt nephropathy by around five times over the course of 10 years in the Caucasian population with T2DM -19. The The albumin excretion rate normally rises steadily over several years as opposed to abruptly changing from normal to abnormal values, which occurs between 10% and 30% yearly until overt nephropathy manifests . It is eThe most widely used assay for chronic hyperglycemia is the HbA1c assay. Diabetes patients with HbA1c levels of 6.5% or below have acceptable glycemic control, while those with levels over 8% incur the risk of progressing disease-related problems, like diabetic nephropathy (DN) . GlycemiWith respect to normoalbuminuria, microalbuminuria, and macroalbuminuria in diabetic patients with periodontitis and/or without periodontitis, in the present study, the mean HbA1c values are demonstrated to have a significant difference in statistical analysis, which is consistent with findings noted in the prior studies ,22-24. AThe results of the present investigation and the observations of the other studies concur that the microalbuminuric group had considerably higher FPG concentrations than the normoalbuminuric patients ,20. The There was an appreciable variation in the number of teeth present among the individuals with and without periodontitis in the current study. The CPI, which is marked for its reproducibility and simplification, was used to identify periodontitis and evaluate its severity ,7-9,29. The key pathogenic mechanism connecting DM and periodontitis is a dysfunctional inflammatory response that involves immunological functioning, neutrophil activation, and cytokine biosynthesis. Prostaglandin E2, interleukin (IL)-1b, IL-6, and tumor necrosis factor (TNF)-a are among the pathways that become active in a hyperglycemic state and cause inflammation, which also has an effect on the periodontal tissues. However, prolonged subclinical systemic inflammation, a T2DM precursor, may contribute to poor glucose homeostasis. These results indicate a bidirectional interaction between hyperglycemia and periodontitis, with hyperglycemia raising the threat of periodontitis and periodontal pathology lowering glycemic status ,29.The limitations of this study are that the causal relationship between microalbuminuria and periodontitis could not be determined as it was a backward-looking cross-sectional study. The estimation of albuminuria was performed using a single urine spot sample. A multi-ethnic prospective study with a round-the-clock urine sample is necessary to control these constraints.The findings of the study suggest that T2DM patients had a greater prevalence of microalbuminuria than subjects with periodontitis and these subjects also had significantly higher HbA1c and fasting plasma glucose (FPG) levels than subjects with normoalbuminuria. In addition, subjects with periodontitis show a significant reduction in the teeth number present in terms of albuminuria. The longitudinal correlation between DM, microalbuminuria, and periodontitis could be further investigated in detail to explore possible pathways.


CW), carcass conformation (CC) and carcass fat (CF) in cattle. The data used comprised carcass data, along with imputed, high-density genotype data on 618,837 single nucleotide polymorphisms (SNPs) from 23,687 cattle; all animal genotypes were phased with respect to parent of origin. Based on the phased genotypes and a series of single-locus linear models, 24, 339, and 316 SNPs demonstrated imprinting associations with CW, CC, and CF, respectively. Regardless of the trait in question, no known imprinted gene was located within 0.5 Mb of the SNPs demonstrating imprinting associations in the present study. Since all imprinting associations detected herein were at novel loci, further investigation of these regions may be warranted. Nonetheless, knowledge of these associations might be useful for improving the accuracy of genomic evaluations for these traits, as well as mate allocations systems to exploit the effects of genomic imprinting.Genomic imprinting is an epigenetic phenomenon defined as the silencing of an allele, at least partially, at a given locus based on the sex of the transmitting parent. The objective of the present study was to detect the presence of SNP-phenotype imprinting associations for carcass weight ( Genetic selection has translated into performance gains in farmed livestock globally . The calOf interest to the present study is the epigenetic phenomenon known as genomic imprinting. Genomic imprinting is where the expression of an allele differs depending on the sex of the transmitting parent . While tCW), carcass conformation (CC) and carcass fat (CF)] using phased , high-density genotype data across the genome. Although SNP) data used herein. Results from the present study should provide further insight into the epigenetic components underlying the carcass merit of cattle. Furthermore, such information could potentially be used to improve the accuracy of genomic evaluations and to inform mate selection programs.For carcass traits in cattle , genomic imprinting has been reported to account for 8–39% of the total additive genetic variance ; while iPreviously imputed high-density genotypes, comprising 734,159 autosomal SNP genotypes from 638,662 cattle were available. An in-depth description of the pipeline used to impute the genotype data to high density is provided by The three carcass phenotypes of interest to the present study were CW, CC, and CF, all of which were measured in accordance with the EUROP grading system. Carcass weight is measured in kg, on average, one hour after slaughter, following the removal of the head, hide, legs, thoracic and abdominal organs, and internal fat. With regard to CC and CF, the former reflects the shape and development of the carcass, particularly on the round, back and shoulders, and the latter reflects the level of fat covering the carcass, as well as within the thoracic cavity of the carcass . Under tOnly genotyped young bulls, heifers and steers slaughtered between the ages of 12 and 36 months, inclusive, with recorded carcass phenotypes, of which there was 93,470 animals, were considered for the present study. Additionally, all young bulls, heifers and steers considered were born to dams with a parity number ≤10 and were not born from embryo transfer. Finally, any cattle with more than three inter-herd movements during their life, or a movement 100 days before slaughter were not considered further. Following all edits, the birth herd of all remaining genotyped animals were categorized as either beef or dairy based on parameters outlined by For each of the 23,687 animals of interest, the parental origin of each allele was inferred by phasing their genotypes using a combination of pedigree and genotype information in FImpute2 . The pedFollowing phasing, four unique genotypes were distinguishable at each locus . For the purpose of the association analyses, the four genotypes were coded to represent additive , dominance  and imprinting effects  .via a genomic relationship matrix. All phenotypes were adjusted in the GenABEL package in R  regions associated with CW, CC, and CF were defined based on the flanking linkage disequilibrium patterns around the SNPs with significant or suggestive associations. To estimate the start and end positions of the QTL regions, all SNPs within a 0.5 Mb window that were in linkage disequilibrium (r2 of ≥0.5) with significantly or suggestively associated SNPs were considered part of a single QTL region. In the case where QTL regions overlapped, these regions were merged together and considered a single region. Additionally, the presence of candidate genes within a 0.5 Mb window of the QTL regions, as well as genes located within the QTL regions were investigated using ENSEMBL (https://www.ensembl.org/) on the ARS-UCD 1.2 genome build, alongside the biomaRt package in R  were inspected to identify known imprinted genes within a 0.5 Mb window, either upstream or downstream, of the SNPs of interest.Quantitative trait loci (age in R . FurtherBos taurus (BTA) chromosome 2, demonstrated imprinting associations with CW. In addition, a further five SNPs located on BTA 2 (three SNPs), BTA 19 (one SNP) and BTA 23 (one SNP) demonstrated suggestive imprinting associations (0.01 < q ≤ 0.05) with CW. Based on the 24 SNPs demonstrating an imprinting association with CW, two distinct QTL regions were identified. These QTL regions stretched from 2.60 to 2.65 Mb on BTA 2 and from 3.43 to 3.71 Mb on BTA 2. Both lead SNPs  in the QTL regions were intergenic variants, with no currently known imprinted gene residing within a 0.5 Mb window of the QTL regions.The associations between CW and the additive, dominance and imprinting genotype codes of each SNP are shown in Manhattan plots with the additive, dominance, and imprinting associations between each of the 618,837 SNPs of interest and CC are presented in The additive, dominance and imprinting associations of each SNP of interest and CF are shown in The term epigenetics or, in other words, the manifestation of divergent phenotypes from the same genotype, can be attributed to Conrad Waddington . An examBos taurus genome (Mus musculus genome is as high as 600 (www.geneimprint.com), novel loci demonstrating imprinting associations were detected in the present study. Nonetheless, the imprinting effects  associated with the novel loci detected in the present study were biologically small. For example, the largest imprinting effect estimated for the different lead SNPs associated with CW, CC, and CF in the present study were equivalent to 5.0%, 7.1%, and 8.9% of the respective genetic standard deviations estimated for the traits of interest by The presence of imprinting genes in cattle has been previously documented, with 20–30 imprinted genes currently validated in the s genome . Furthers genome , althougs genome , although as 600 . Wolf etAs per Bos taurus genome; these included BTA 3, 4, 6, 13, 18, 21, and 25. Of the SNPs demonstrating imprinting associations located on these chromosomes, the nearest SNP demonstrating an imprinting association to a known imprinted gene  was 2.7 Mb downstream from ZNF597 on BTA 25.The presence of imprinting associations with the carcass traits of interest were detected on 19 different chromosomes in the present study. Of these, the vast majority of the SNPs detected to have imprinting associations were located on BTA 2; this is despite the fact that no imprinted genes have, to the best of our knowledge, yet been validated on BTA 2. Nonetheless, the presence of novel imprinting regions for carcass traits, namely CW and kidney, pelvic and heart fat, on BTA 2 was previously documented in cattle by p values ≥0.628), ≥0.56 for CC , and ≥0.59 for CF ; extending the window to 0.5 Mb, the q values associated with the imprinting effects estimated for SNPs within the larger windows were all ≥0.86 for CW , ≥0.56 for CC , and ≥0.16 for CF . This signifies that, based on the analysis conducted herein, even if a less conservative genome-wide significance threshold was used, no currently known imprinted genes demonstrated imprinting associations with the carcass traits evaluated. The relatively large dataset of animals employed for this analysis should ensure that the analysis conducted had the necessary power to detect any imprinting associations for the carcass traits, should they exist. Similarly, While not all known imprinted cattle genes had intronic SNPs included in the present study , all known imprinted genes did have at least one SNP within a 50 Kb window of their location included in the analyses. Of the SNPs located within these 50 Kb windows, the average and standard deviation of their minor allele frequencies were 0.30 and 0.13, respectively. All q values associated with the imprinting effects estimated for SNPs within a 50 Kb window of a known imprinted gene were ≥0.99 for CW , with Of the 618,837 SNPs included in the association analyses, 24 SNPs, 339 SNPs, and 316 SNPs, spread across 19 different chromosomes, demonstrated some form of imprinting association  with CW, CC, and CF, respectively. The fact that all imprinting associations detected for the carcass traits of interest were at novel loci warrants further investigation in these regions, particularly, BTA 2 where the vast majority of the imprinting associations were detected. Nonetheless, the data used to detect these imprinting associations comprised high-density genotype data from a relatively large group of cattle, which should ensure the analyses conducted had the power to detect imprinting associations, should they exist. Knowledge of loci at which imprinting associations are present for the carcass traits of interest could be incorporated into genomic evaluations in an attempt to improve the accuracy of such evaluations for these traits. Furthermore, this knowledge could be incorporated into mate allocation programs to exploit (or avoid) the effects of genomic imprinting in potential offspring.


Gastric cancer (GC) is one of the most serious gastrointestinal malignancies with bad prognosis. The association between GC and cuprotosis-related genes has not been reported.  The clinical and RNA expression of patients with GC were downloaded from TCGA database. The CIBERSORT package was used to quantify the abundance of specific cell types. Using the Cox regression analysis, we conducted a prognostic nomogram model based on cuprotosis-related differential genes in GC. We evaluated the prognostic power of this model using the Kaplan-Meier (K-M) survival curve analysis, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve analysis. p < 0.05), while T cell CD4 memory activated macrophage M0, macrophage M1, and macrophages in GC tissue. The number of M2 was significantly more than that in the adjacent tissue (p < 0.05). Additionally, GC patients in the test group, the training group, and all the sample groups had shorter survival time with the increase of the risk factor (p < 0.05). The nomogram of GC based on cuprotosis prognosis-related genes was conducted. The AUC of the nomogram to predict 1-, 3-, and 5-year survival rate was 0.618, 0.618, and 0.625, respectively.  The plasma cells, monocytes, and mast cells in GC tissue were significantly less than those in adjacent tissue ( A novel cuprotosis-related gene signature impacts on the prognosis of GC. Our research provides new insights and potential targets for studying the link between GC and cuprotosis point, thereby providing new insights into understanding the molecular mechanism of GC. Gastric cancer (GC) is the main cancer of the gastrointestinal tract. According to relevant statistics, GC has become the fifth most common cancer in the world and the third leading cause of cancer-related death and has become one of the major global health problems –3. GC acCopper is an indispensable trace element involved in various biological processes. Recent studies have shown that copper levels in serum and tumor tissue are significantly elevated in cancer patients compared to healthy individuals , 7. The The tumor microenvironment (TME) has been confirmed to be closely related to the occurrence, growth, and metastasis of GC , and theHowever, a comprehensive analysis of associated prognosis, tumor immune microenvironment, and immunotherapy based on cuprotosis has not yet been performed. In our study, based on the TCGA database and CIBERSORT, we performed immune infiltration correlation analysis in GC, screened cuprotosis-related differentially expressed genes, and constructed a cuprotosis prognostic model and its risk factor analysis. Prognostic features can effectively predict the prognosis of GC patients. At the same time, relevant functional analysis, immune microenvironment and immune-related function analysis, immune escape, immunotherapy, and screening of potential drugs were carried out. Our research provides new insights and potential targets for studying the link between GC and cuprotosis point, thereby providing new insights into understanding the molecular mechanism of GC.https://portal.gdc.cancer.gov/) website was used to download clinical and transcriptomic expression data related to GC, and R software was used to sort, summarize and summarize the clinical data, and further obtain its expression matrix. And we used the Perl script to screen out the expression matrix of mRNA and remove the expression data of noncoding RNA.The TCGA (https://www.ncbi.nlm.nih.gov/geo/) to download the gene chip data related to GC, and the screening conditions are (1) GC, (2) human, and (3) GC tissue and adjacent tissue. Background correction, normalization, and expression value calculations were performed on the microarray data using the limma R package in R, and the CIBERSORT package was used to estimate the cellular composition of GC and adjacent tissue. The composition of immune cells in each sample was further analyzed using the CIBERSORT package, and histograms were drawn. A heatmap of immune cell distribution was drawn using the pheatmap package. Then, the corrplot package was used to analyze the interaction between immune cell populations in GC and to plot the coexpression of immune cell infiltration in GC. Finally, the vioplot package was used to analyze the expression of each immune cell in GC tissue and adjacent tissue and further draw the violin diagram of immune cell expression.Using the CIBERSORT package to deconvolute the STAD expression matrix data obtained above, the cellular composition of complex tissues can be estimated based on normalized gene expression data, which can quantify the abundance of specific cell types. And get the STAD-related infiltrating immune cell expression matrix, and use the immune sorting Perl script to sort immune cells, in the GEO (gene expression omnibus) database  is the criterion for screening differential genes, where log2FC ≥ 0.58 means mRNA expression is upregulated and log2FC ≤ −0.58 means mRNA expression is downregulated. Finally, the differentially expressed mRNAs related to cuprotosis between the STAD group and the control group were obtained, that is, the STAD differentially expressed genes (DEGs). The heatmap package was used to draw heatmaps and cluster analysis of the filtered DEGs, and the p value in the differentiated data was converted to -log10, and the -log10  was grouped according to log2FC  and imported the processed data into R to draw a volcano plot.The STAD mRNA expression matrix obtained in the previous stage was combined with the expression matrix of the currently known 19 cuprotosis genes, and the correlation heatmap was drawn using the limma package, and the differential expression between the two groups was calculated according to and using the limma package. In mRNAs, set The standardized STAD cuprotosis-related expression data was merged with the clinical data of GC, and R language packages such as survivor, caret, glmnet, survminer, and survivorROC were used to perform univariate and multivariate Cox prognostic survival analysis of GC differential genes, dig out the key cuprotosis genes closely related to the prognosis of GC, and draw its survival curve. In addition, 443 cases were randomly divided into a test group (Test) and a training group (Train), and the survival package was called to perform risk-survival analysis on the combined data in the early stage, and the risk-survival curve and ROC curve were drawn, the training group (Train), and the survival state graph of all samples. The survival package was called again to carry out clinical statistical analysis and risk prognosis analysis on the general clinical data of GC. The univariate and multivariate independent prognostic analysis was used to mine the risk factors related to GC, and the univariate and multivariate independent prognostic analysis forest diagram was drawn, C-index curve, nomogram, and further survival, survminer package for model validation of clinical grouping.https://www.r-project.org/) software were used to analyze GC. The cuprotosis-related differential genes of cancer were subjected to GO analysis, respectively. GO analysis is mainly used to describe the function of gene products, including Cellular Component (CC), Molecular Function (MF), and Biological Process (BP). The clusterProfilerKEGG.R package was used for KEGG pathway enrichment analysis, and the enrichment degree of core pathways was analyzed according to the enrichment factor value, and the potential biological function and signaling pathway mechanism of GC were explored.The scatterplot3d package was used to carry out principal component analysis of GC cuproptosis-related genes and GC-related risk genes, and the clusterProfilerGO.R package and Perl language in R language , and use the ggpubr package to analyze the relative expression of the core targets in the STAD expression data based on the core targets screened in the previous stage, and plot the relative expression box plots of core targets.http://org.Hs.eg.db), clusterProfiler, and enrichplot packages to carry out GO and KEGG enrichment analyses of core genes, respectively, download the GO/KEGG annotation files of whole transcriptome genes from GSEA official website, and analyze the cellular components , molecular function , and biological process  and KEGG pathway enrichment analysis. The enrichment degree of core pathways was analyzed according to the enrichment factor values, and the potential biological functions and signaling pathway mechanisms of core genes in GC were explored.Using limma  or GraphPad Prism (version 8.3.0). A p < 0.05), while T cell CD4 memory activated macrophage M0, macrophage M1, and macrophages in GC tissue. The number of M2 was significantly more than that in the adjacent tissue (p < 0.05), while the number of other immune cells had no significant difference between the two groups (p > 0.05).The obtained STAD expression matrix data was used for background correction, normalization, and expression value calculation of the chip data using the limma R package in R, and the CIBERSORT package was used to calculate the immune cell composition of GC and adjacent tissue. And further use the CIBERSORT package to analyze the composition of immune cells in each sample, and draw a histogram, as shown in https://portal.gdc.cancer.gov/) website to download the clinical and transcriptome expression data related to GC and obtain 407 transcriptome-related data sets and 443 clinically related data sets according to the preset screening conditions data set, use R software to organize and summarize clinical data, and further obtain its cuprotosis-related expression matrix. According to the p value < 0.05, the expression change range ≥ 1.5 times (|log2 FC| ≥ 0.58) was the criterion for screening differentially expressed genes, and 7 differentially expressed mRNAs were screened in the data set, including 2 upregulated mRNAs and 5 downregulated mRNAs, including DBT, PDHB, CDKN2A, GLS, MTF1, NFE2L2, DLST, and draw STAD cuproptosis-related gene expression matrix heatmap in p value after the difference analysis was converted to -log10, and the -log10  was grouped according to log2 FC  and imported the processed data into R plot the volcano in Use the TCGA (p > 0.05); the two groups of data are comparable in p < 0.05), as shown in Figures p < 0.05), as shown in p < 0.05), as shown in 443 clinical cases were randomly divided into a test group (Test) and a training group (Train), and the clinical statistical analysis of the general clinical data of the two groups found that there was no significant difference in age, gender, and tumor stage between the two groups , as shown in p < 0.05) in Import the STAD expression data and TMB file into R, and use the function to calculate the correlation between GC cuprotosis-related risk genes and STAF tumor mutation load, and draw waterfall charts for high- and low-risk groups according to the correlation results, as shown in Figures p < 0.001), while SLC31A1 and GCSH genes were highly expressed in STAD tumor tissue (p < 0.01), and there was no significant difference in the expression of NLRP3 between the two groups (p > 0.05).The core cuprotosis risk genes NFE2L2, NLRP3, SLC31A1, and GCSH were obtained through differential expression analysis and survival prognosis analysis in the early stage. We further studied the relative expression of core cuprotosis risk genes NFE2L2, NLRP3, SLC31A1, and GCSH in GC STAD. Download the relevant expression data of STAD from TCGA, and analyze the relative expression levels of NFE2L2, NLRP3, SLC31A1, and GCSH genes through the ggpubr package, and draw a box expression map, as shown in Figures The GO/KEGG annotation files and STAD tumor data files downloaded from the GSEA official website were read into R, and the enrichment analysis operation was performed to obtain the following: the GO of gene NFE2L2 in STAD is enriched in chromatin remodeling, DNA packaging, and protein DNA complex subunit organization function in According to the preliminary screening of GC cuprotosis-related risk genes, for the therapeutic effect of these genes, the CPG2016 drug database was used for screening, and the limma, ggpubr, pRRophetic, and ggplot2 packages were run to evaluate effective drugs for GC cuprotosis-related risk gene therapy. Discover AR-42, axitinib, belinostat, BEZ235, BMS345541, bortezomib, CAY10603, CP466722, CUDC-101, cytarabine, elesclomol, GSK429286A, HG-6-64-1, JW-7-24-1, MG-132, and MLN4924. Such drugs have good potential clinical efficacy on GC cuprotosis-related risk genes, as shown in Figures In this study, we obtained 407 transcriptome-related data sets and 443 clinically-related data sets through TCGA, explored the expression characteristics of 7 cuprotosis-related genes in GC, and constructed a prognostic model and its risk factors by constructing a prognostic model. Analysis, functional enrichment analysis, immune-related function analysis, and tumor mutational burden (TMB) analysis have confirmed for the first time that cuprotosis-related genes are related to the occurrence, development, and prognosis of GC.Immunoregulatory factors and immune cells play important roles in the pathogenesis of GC , 12. We p value < 0.05, the expression change range is ≥1.5 times (|log2 FC| ≥ 0.58), and a total of 7 cuprotosis-related differentially expressed genes  were screened. Previous studies have found that PDHB is known to be closely related to colorectal cancer, renal cancer, and other malignant diseases [R software was used to organize and summarize the clinical data set of GC obtained by TCGA and further obtain its cuprotosis-related expression matrix. According to diseases , 18. Thediseases , while Tdiseases . In detediseases . Previoudiseases –24, whildiseases , 26, andWe also randomly divided 443 clinical cases into a test group (Test) and a training group (Train) to construct a GC cuprotosis prognosis model and analyze its risk factors.The results confirmed that both cuprotosis risk genes and tumor stage are important indicators for evaluating the prognosis of GC. At the same time, the related functional analysis of cuprotosis differential genes was carried out, and it was found that their pathways were mainly enriched in the TCA cycle and carbon metabolism in cancer. Gong et al. also found that the TCA cycle may be related to the pathogenesis of GC through GSEA enrichment analysis . In addiThe core cuprotosis risk genes NFE2L2, NLRP3, SLC31A1, and GCSH were obtained through differential expression analysis and survival prognosis analysis in the early stage. We further studied the relative expression of core cuprotosis risk genes NFE2L2, NLRP3, SLC31A1, and GCSH in GC STAD and confirmed that NFE2L2 has low expression in STAD tumor tissue, while SLC31A1 and GCSH genes were highly expressed in STAD tumor tissue. There was no significant difference in the expression of NLRP3 between the two groups. At the same time, single-gene GSEA enrichment analysis was used to study the core cuprotosis risk genes in STAD tumor tissue. We performed gene enrichment analysis on STAD samples. SLC31A1 has been confirmed to be associated with various diseases such as lung cancer, ovarian cancer, and pancreatic cancer –30, but Our study still has limitations. First, although the expression of differentially expressed genes of cuprotosis in GC screened by TCGA proved that these genes are associated with the prognosis of the disease, a data set with a sufficiently large sample size and more complete clinical prognostic information is still needed for future research. Second, given that the predictions were established and validated by leveraging data from public databases, further biological evidence is required for validation in addition to the statistical evidence we provided. Finally, the specific mechanism of GC-related cuprotosis differential genes in the tumor immune process is still unclear, and further research is needed.


This study applied an ecological-based analysis aimed to evaluate on a global scale the association between greenness exposure and suicide mortality.Suicide mortality data provided by the Institute for Health Metrics and Evaluation and the Normalized Difference Vegetation Index (NDVI) were employed. The generalized additive mixed model was applied to evaluate with an adjustment of covariates the association between greenness and suicide mortality. Sensitivity tests and positive-negative controls also were used to examine less overt insights. Subgroup analyses were then conducted to investigate the effects of greenness on suicide mortality among various conditions.The main finding of this study indicates a negative association between greenness exposure and suicide mortality, as greenness significantly decreases the risk of suicide mortality per interquartile unit increment of NDVI . Further, sensitivity analyses confirmed the robustness of the findings. Subgroup analyses also showed a significant negative association between greenness and suicide mortality for various stratified factors, such as sex, various income levels, urbanization levels, etc.Greenness exposure may contribute to a reduction in suicide mortality. It is recommended that policymakers and communities increase environmental greenness in order to mitigate the global health burden of suicide. Suicide has become a common occurrence in a modern society. Approximately 2.5% of death in the global population has been attributed to suicide . AnotherIn addition to the influence of gender on suicide mortality, previous studies have suggested that several risk factors trigger psychosocial stress and, thus, inspire suicide attempts, and these factors include mental disorders, socioeconomic and sociocultural problems, physical conditions, and lifestyle , 5. In aA recent study revealed that exposure to greenness is negatively associated with suicide mortality . AlthougAlthough previous studies have marked the beneficial effects of greenness on human health, very few studies have investigated on a global scale the linkage between greenness and suicide mortality. Some studies have only utilized a few years of data and/or unequal timeframes of study data , 18. Furhttp://ghdx.healthdata.org/gbd-results-tool). In this database suicide was defined using the revision codes for intentional injuries  from the 10th edition of the International Classification of Diseases. Suicide rate mortality was reported by the number of deaths per 100,000 population, which is consistent with the WHO's Indicator and Measurement Registry. Mortality rates were age-adjusted, which is necessary because death rates per 100,000 population are significantly different by age group. Annual estimation data used in this study were available for the seventeen consecutive follow-up years ranging from 2000 to 2016. There were 183 countries across five continents with available data for suicide mortality and related factors. The data of suicide mortality at the country level in this study was provided by the Institute for Health Metrics and Evaluation (IHME) from Global Burden of Disease Collaborative Network—Global Burden of Disease (GBD) study 2017  is a satellite-image-based vegetation index provided by the National Aeronautics and Space Administration (NASA) for estimating plant growth, vegetation cover, and biomass production . This es2 spatial resolution, as measured by a Terra Moderate Resolution Imaging Spectroradiometer (Terra-MODIS) sensor, were used to estimate greenness exposure in each country . The NDVI product used in this study was MOD13A3 version 6. It has been noted the issue of contiguity with water being detected in negative grids of NDVI. Because of this, pixels with negative values were excluded so as to avoid this misclassification bias resulting from the effects of water. Satellite-image NDVI data with acquisition dates closer to the middle of a season were collected for use in this study. In other words, to address seasonal variations, data were retrieved in January, April, July, and October. The month settings in the data collection did account for countries with two and/or four seasons. After that adjustment, a monthly global greenness map was generated by combining 292 images. Moreover, a similar process was performed to estimate the greenness values for each of the four selected months. Finally, monthly greenness estimates were calculated in order to capture the annual average values of greenness at the country level. In total, the number of NDVI images used to generate global greenness maps was 19,856 images (292 x 4 selected months x 17 follow-up years from 2000 to 2016). The spatial distribution of exposure to greenness at the country level based on the interquartile of NDVI (IQR = 0.311) is displayed in In this study, NDVI data provided by NASA with 1 x 1 kmdemographic factors: density of population, age, and sex ; (2) socioeconomic variables: income level, health expenditure rate, attainment of education rate, urbanization rate, divorce rate, unemployment rate, and population without religious affiliation .The country-level variables included in this study are listed in iliation –23; (3) sumption , 25; (4)er—PM2.5 , and temer—PM2.5 ; (5) comThe descriptive statistics of all country-level variables used in this study are presented, and a bivariate test using Spearman's rank algorithm was performed to identify the correlation between suicide mortality and all potential covariates . The maiModel 1 included greenness, density of population, age, sex, healthcare expenditure rate, PM2.5, temperature, burden due to depressive disorders, and spatial-temporal autocorrelation; Model 2 added unemployment rate to model 1; Model 3 added divorce rate to model 2; Model 4 added economic status and educational rate to model 3; Model 5 added urbanization rate to model 4; Model 6 added the lifestyle behaviors smoking rate and alcohol consumption to model 5; and Model 7, we adjusted for all covariates and considering population-weighted greenness as the main exposure. Population-weighted greenness was evaluated considering that exposure to greenness and population density varied spatially in each region , sex , DALY loss due to depressive disorders [< or ≥ median (5.38)], economic status , urbanization level , unemployment rate [< or ≥ median (6.28%)], and divorce rate [< or ≥ median (0.80%)], as well as for level of alcohol consumption [< or ≥ median (2.00 liters/population)] and smoking rate [< or ≥ median (19.10%)].Each of the statistical analyses were performed using R version 3.6.3  and the spatial analyses were performed using ArcGIS 10.7.1 .2 (SD = 152.72). Nearly half of the total population were aged 25–49 and nearly half were male. Among all of the countries, 80 countries had low-income levels (43.71%). The healthcare expenditure rate, education rate, urbanization rate, divorce rate, unemployment rate, and population without religion were 6.22% (SD = 2.39), 83.7% (SD = 19.68), 54.93% (SD = 22.89), 1.02 (SD = 1.11), 8.23 (SD = 6.61), 8.23 (SD = 6.61), and 0.04 (SD = 0.1), respectively. In terms of behavioral factors, the average smoking rate was 18.6% (SD = 13.79) and the average annual alcohol consumption was 3.26 liters (SD = 3.61). As for meteorological factors, the mean PM2.5 exposure was 19.45 μg/m3 (SD = 16.10) and the mean temperature was 19.5 °C (SD = 8.16). Lastly, DALY loss due to depressive disorders was 5.62 years (SD = 1.37). The temporal trends of greenness assessment per IQR of NDVI and suicide rates at the country level are illustrated in The statistical summaries of all variables analyzed in this study are displayed in p-value < 0.001). This result indicates that there is a reduction in the risk of suicide mortality by up to 31% per each unit IQR increment of NDVI (IQR of NDVI = 0.311). Furthermore, the results of the other sensitivity test models demonstrate that greenness exposure is negatively associated with suicide mortality. The results of the analyses demonstrate a robust approximation, which is indicated by the stable estimation of coefficients and corresponding risk ratios. Detailed estimations for all covariates of the main model are presented in 2, a negative exposure control, was found to have no significance.p-values < 0.01), respectively. In contrast, no significant association was exhibited between NDVI and suicide mortality in countries with low greenness exposure levels. In terms of sex, significant negative associations were observed for both males and females , indicating there is no difference according to sex in relation to greenness in reducing suicide mortality. Additionally, significant negative associations between greenness and suicide mortality were also identified in depressive disorder prevalence  and income level . Significant negative associations between greenness and suicide mortality were observed in countries with the highest unemployment rate  and divorce rate , as well as in countries with high amounts of alcohol consumption  and high smoking rate .Results of subgroup analyses by different levels of greenness exposure, sex, DALY loss due to depressive disorders, economic status, urbanization rate, unemployment rate, and divorce rate, smoking prevalence, and alcohol consumption are displayed in This study demonstrated the negative relationship on a global scale between greenness exposure and suicide mortality. This result indicates that exposure to greenness may serve a role in reducing suicide risk. The results of a series of sensitivity analyses were consistent, which bolsters the robustness of the findings, even after adjustment for demographic factors, healthcare status, social environment, and behavioral variables. To our knowledge, this is one of the few ecological studies to have investigated the linkage globally between greenness and suicide mortality. Because they contain analysis of long-term data sets (17 years of data) with comprehensive variables, the study findings provide a global overview of the relationship between greenness and suicide mortality and can be used as a reference in regional planning supporting human health and well-being.After adjusting for all covariates, this study confirmed the protective effects of greenness on suicide mortality, with a 31% decrease in risk of perceived suicide mortality per IQR increment in greenness. The finding of this large-scale study is consistent with the conclusions drawn in previous studies that have focused on a similar topic but at a smaller geographic level , 18. ForOur stratified analyses revealed the linkage in various conditions between greenness and suicide mortality. In terms of levels of greenness, countries with medium or high greenness exposure levels have a lower suicide mortality rate. These findings corroborate those of previous studies exploring either suicide risk reduction  and alsoRegarding prevalence of depressive disorders, our findings support the theory that countries with higher burden from depressive disorders benefit more from greenness exposure's influence on suicide mortality than do countries with lower burden from depressive disorders. It is well known that depression is closely associated with suicidal thoughts and suicide attempts . ObservaFirst, due to a lack of available vegetation data for each country, this study assumed that all types of greenery have a positive impact on health, and the biodiversity of green plants was not considered in the model adjustment. Further investigation is appropriate if detailed information is made available. Second, in its analytical models this study controlled for many pertinent factors, but several confounding covariates may not have been considered, such as individual health information, genetics, family history, hereditary diseases, race/ethnicity, and cultural tolerance. Because of this, possible unmeasured confounding effects remain unknown. Third, a country-level database may not be the best scale for variable assessments, and it may introduce statistical bias. However, due to the limited availability of city-level data for all selected variables, we chose to use country-level data to examine the global association between greenness and reduced risk of suicide mortality. Fourth, MODIS-NDVI with 1 x 1 km2 resolution was used for the greenness assessment. We recognize that 1 x 1 km2 is not the optimal spatial resolution of MODIS-NDVI for estimating greenness and could not distinguish the type of green spaces. Thus, the use of MODIS-NDVI with the best spatial resolution of 250 x 250 m2 for future studies is suggested. In addition, we also understand that this study lacks land use or land cover data that may be more reliable to assess exposure to urban green spaces including public and private green spaces. Fifth, although global suicide data has gone through a process of standardization and evaluation of data quality using sophisticated modeling frameworks, however, data quality gaps may exist in each country. This may be due to under-reporting of suicide as a social, cultural, religious, and political or legal consequence, especially in lower-middle-income countries. Finally, we recognize that global analysis using country-level data have shortcomings in terms of data accuracy and result interpretation. Therefore, to support better scientific evidence, use of accurate data and comprehensive analysis is recommended for future studies.This study has some limitations. Notwithstanding the shortcomings of this study, our findings could serve to help better understand at a macro level the relationship between greenness exposure and suicide mortality. A series of sensitivity tests were performed in order to confirm the robustness of the findings. More detailed information was obtained from the ensuing subgroup analyses. Based on this information, the study proposed suggestions to and offered encouragement to decision-makers, key stakeholders, and community members to heed calls for a spatial planning that supports place-based suicide prevention programs.This study serves a pivotal role in a better understanding of how exposure to greenness can be linked to a reduced risk of suicide mortality globally. The observed reduced effect of suicide mortality was related to greenness exposure under various conditions. Confessing interventions from exposure to greenness can affect general health outcomes in the extensive population, this study also proposed suggestion and encouragement to the entire community and stakeholders to pay attention to spatial planning that supports place-based suicide prevention programs.ghdx.healthdata.org/gbd-results-tool, Accessed in November 2020); the National Aeronautics and Space Administration - NASA, which provided global greenness NDVI data ; the Atmospheric Composition Analysis Group, which provided global PM2.5 data ; the United Nations Agency, which provided demographic data (esa.un.org/unpd/wpp/); and the World Bank Group, which provided data for socioeconomic status, smoking prevalence, alcohol consumption, and pertinent covariates at the country level .The data set from this study is publicly available. Data used in this study was acquired from the Institute for Health Metrics and Evaluation - IHME, which provided the metrics of disability-adjusted life years (DALY) database .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


After the rapid spread of the novel SARS-CoV-2, the short-term and long-term mental health impacts of the pandemic on the public, in particular on susceptible individuals, have been reported worldwide. Although digital mental health services expand accessibility while removing many barriers to in-person therapy, their usability, feasibility, acceptability, and efficacy require continued monitoring during the initial phase of the pandemic and its aftermath.In this study, we aimed to understand what mental health services are offered, whether they are practical or acceptable, and to what extent digital mental health services are effective in response to the COVID-19 pandemic across high-income and low- and middle-income countries.This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline. We implemented searches in PubMed (MEDLINE), Embase, PsycINFO, and Cochrane databases for studies that were published between December 2019 and November 2021 and that involved the use of digital mental health services. Two review authors screened, assessed, and extracted studies independently. The protocol was registered on the International Prospective Register of Systematic Reviews.P<.001) and a moderate reduction in anxiety symptoms  significantly.This review identified 7506 articles through database searching. In total, 65 (0.9%) studies from 18 countries with 67,884 participants were eligible for the scoping review. Of the 65 studies, 16 (24.6%) were included in the meta-analysis. A total of 15 (23.1%) studies measured the usability; 31 (47.7%) studies evaluated the feasibility; 29 (44.6%) studies assessed the acceptability; and 51 (78.5%) studies assessed the efficacy. Web-based programs , videoconferencing platforms , smartphone apps , and SMS text messaging  were the main techniques. Psychotherapy  followed by psychoeducation  and psychological support  were commonly used. The results of the meta-analysis showed that digital mental health interventions were associated with a small reduction in depressive symptoms (standardized mean difference=−0.49; 95% CI −0.74 to −0.24; The findings suggest that digital mental health interventions may be practical and helpful for the general population, at-risk individuals, and patients with preexisting mental disorders across high-income and middle-income countries. An expanded research agenda is needed to apply different strategies for addressing diverse psychological needs and develop integrated mental health services in the post–COVID-19 era.PROSPERO CRD42022307695; https://tinyurl.com/2jcuwjym As of October 5, 2022, there were 624.4 million confirmed cases of COVID-19 spread over 228 countries and territories, and COVID-19 has claimed the lives of 6.6 million individuals . In a crAlthough most evidence has been on the negative mental health impacts of COVID-19, a parallel area of research interest has explored how mental health services change when exposed to such stressors . Web-basAgainst this background, the objective of this scoping review and systematic review was to qualify and quantify the usability, feasibility, acceptability, and efficacy of digital mental health interventions applied for infectious disease outbreaks in the initial phase of the pandemic. We focused on the assessment of whether each of the applied techniques was usable, feasible, acceptable, and effective. We also separately synthesized data from high-income countries and low- and middle-income countries (LMICs). As there is no standard definition of usability, feasibility, acceptability, and efficacy, we considered comprehensive and broad definitions of these terms. We defined usability as program use, user engagement, and the ease of use of the services being tested, as followed in prior research ,11. We mThis report includes a scoping review of studies on digital mental health interventions applied for infectious disease outbreaks and a systematic review of studies assessing commonly reported mental distresses identified in the scoping review. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline when appropriate .We sought to include original studies focusing on digital mental health services applied during or in response to COVID-19. We implemented searches in PubMed (MEDLINE), Embase, PsycINFO, and Cochrane between December 2019 and November 2021 using a combination of search terms relating to both digital mental health services and COVID-19. The complete search strategy is provided in We removed duplicate citations across electronic databases before the screening. Initially, pairs of 2 review authors  independently screened the titles and abstracts for eligibility. We referred to full texts if titles and abstracts did not provide information for eligibility based on the inclusion and exclusion criteria. The full texts of the potentially included studies were screened by 1 review author and checked by another author for agreement. In case of disagreements, the opinion of a third reviewer was sought, and a consensus was reached through discussion.We included qualitative, quantitative, and mixed methods studies that involved the use of digital mental health services. Eligible interventions included health education, evaluation, consulting, helplines, psychological interventions, and telemedicine. The intervention was delivered by any means of digital technology, including SMS text messaging, smartphones, websites, social media, videoconferencing, wearable devices, or mobile apps. We excluded comments, protocol papers, systematic reviews, preprints, conference papers, and studies that did not provide any qualitative or quantitative data for defined outcomes. We excluded studies that were conducted before December 2019. There was no exclusion for age, gender, ethnicity, socioeconomic status, professions , or any type of mental disorder . For the meta-analysis, we included parallel RCTs and crossover RCTs that provided adequate data for analyses, using the same aforementioned criteria.We developed a data extraction form that could be used by all review authors, as recommended by the Joanna Briggs Institute Scoping Review methodological guidance . The datTwo reviewers (XY and ZP) independently assessed the risk of bias using the Cochrane Risk of Bias (RoB 2) tool for all included RCTs. Disagreements were resolved by discussions. In case of uncertainties, a third reviewer (SZ) was consulted. The 5 domains included bias owing to the assignment of intervention, adherence to the intervention, missing outcome data, outcome measurement, and selection of reported outcome that were measured. Studies were rated as “low” risk, “some concerns,” or “high” risk.Owing to the nature of the research question and the heterogeneity of the studies, we synthesized qualitative and quantitative results separately. For the scoping review, we descriptively summarized the included studies with a narrative synthesis of individual studies. We summarized the overall number of included studies, the total number of study populations and their basic characteristics, countries, study design, type of digital mental health services, and the objectives and findings of the included studies. We clustered the studies by the type of techniques used and location (high-income countries vs LMICs). For each type of technique, the findings on usability, feasibility, acceptability, and effectiveness data were narratively synthesized by a textual approach.Q and the I2 statistic were used to assess heterogeneity. An I2 value of ≥60% can be considered a substantial level of inconsistency across studies [For meta-analyses, we synthesized findings on similar efficacy outcomes that were measured by >3 RCTs. Outcomes, such as loneliness, burnout, or psychological well-being, that were measured by 1 or 2 RCTs were not synthesized. We pooled continuous outcomes as standardized mean differences (SMD) with 95% of CIs using a random-effects meta-analysis. The values of 0.2, 0.5, and 0.8 in SMDs denote minor, medium, and large effects, respectively . Cochran studies . The ana studies .The PRISMA flowchart shows the study selection process . This reOf the 65 studies, a total of 15 (23.1%) studies measured usability; 31 (47.7%) evaluated feasibility; 29 (44.6%) assessed acceptability; and 51 (78.5%) assessed efficacy.Web-based programs , videoconferencing platforms , smartphone apps , and SMS text messaging  were the main techniques applied. There were other studies that used social media , hotlines , a chatbot , virtual reality , and robotic telemedicine . Most studies provided psychotherapy , followed by psychoeducation , psychological support , psychological assessments , and psychiatric clinical services .This section summarizes the findings from 65 studies that reported the feasibility, acceptability, and effectiveness of digital mental health services during the COVID-19 pandemic. The synthesis was organized according to the type of digital technique used. Overall, 21  out of the 65 studies included in this scoping review used web-based programs. In 17 studies that were conducted in high-income countries, a significant increase in registered users (n=2) and a high rating in usability (n=1) were reported. The completion rate ranged from 30.5% to 85% (n=5); the retention rate ranged from 30.5% to 85% (n=3); and the attrition rate was 13% (n=1). Quality checks of feasibility reported strong attendance (n=1), strong retentions (n=2), and high ratings of feasibility (n=2). Studies presented preliminary support for the feasibility of web-based programs yet with possible technical difficulty (n=1). In terms of acceptability, there was high satisfaction (n=5); the interventions were perceived to be acceptable, helpful, appropriate, and positive (n=3); and the acceptability scores were significantly better than average (n=1). Most studies, either when no control group is involved or when compared with the control group, reported improvements in anxiety symptoms and anxiety-related social impairment (n=8), while no effects on reducing anxiety were reported as well (n=2). The same patterns were found in outcomes measuring depression. Most studies reported improvements in depressive symptoms and depression severity (n=5), and there was no difference in depressive symptoms when the intervention group was compared with onsite groups (n=1). Improvements in stress-related symptoms (n=3), COVID-19–related worry (n=2), and insomnia (n=1) were identified.In 4 studies conducted in LMICs, the mean time spent was 35.6 (SD 25.4) minutes (n=1) and the completion rate was 87.4% (n=1). High attendance and high retention rates (91.2%) were reported (n=1). With regard to acceptability, high ratings of acceptability and a high level of satisfaction (n=2) were reported. Studies, either when no control group is involved or when compared with the waitlist group, reported improvements in anxiety symptoms (n=4); some studies reported improvements in depressive symptoms (n=2), and 1 study reported reduction in stress and burnout.Among the 65 studies, 16  used teleconferencing platforms, including Zoom ,72,73,81Of the 65 studies, 14  developed smartphone apps to deliver mental health services. In 11 studies conducted in high-income countries, studies reported high usability scores (n=2), and user engagement time ranged from 36.7 minutes over 12 weeks to 1424 minutes over 14 weeks (n=2). Feasibility was reported in terms of the average number of days retained , and the retention rate ranged from 28.3% to 85.7% (n=3). In terms of acceptability, the interventions were rated as “acceptable” (n=2), “satisfied” (n=2), “good” (n=1), and “helpful” (n=1). Studies reported a reduction in depressive symptoms compared with the preintervention and waitlist group (n=4). Similar improvements were reported in anxiety symptoms compared with preintervention, waitlist group, and a control app with limited access to psychoeducational contents (n=5). In 4 studies in LMICs, no evidence was found for usability and feasibility. Acceptability was reported as high satisfaction (n=1) and helpful and enjoyable (n=1). There were improvements in depressive symptoms, insomnia, psychological flexibility, and self-compassion, either when no control group is involved or when compared with the waitlist group (n=2).Of the 65 studies, 5  used the SMS text messaging technique. All studies were conducted in high-income countries. Studies reported high usability of ecological momentary intervention (n=1), and the completion rate ranged from 16% to 78%. An overall high satisfaction was reported (n=1). Studies suggested that an improved mood rating was observed at posttreatment assessments either with or without the control group (n=4). No evidence was found of studies conducted in LMICs for the technique of SMS text messaging.The use of social media as a technique to deliver mental health services was described in 3  out of 65 studies ,54,79. IOf the 65 studies, 3  reported using hotlines and telephone calls to deliver mental health services during the COVID-19 pandemic ,47,65. IOf the 65 studies, 3  used robotic telemedicine and VR. Two studies conducted in high-income countries reported an average use of 78 (SD 24.8) times (n=1) and a completion rate of 58% (n=1). High satisfaction was reported (n=1). Evidence suggested a decrease in anxiety symptoms and stress symptoms for all participants after the intervention (n=1). In 1 study conducted in LMICs, an overall positive impression of the multimodal robotic system was reported (n=1), yet the need to adjust some features was suggested (n=1). No evidence for acceptability or efficacy was found by studies conducted in LMICs.P<.001; I2=87%, 95% CI 80%-91%; Q=107.57; P<.001).Of the 65 studies, 15 (23.1%) that reported depressive symptoms were included in the meta-analysis. Digital mental health interventions were associated with a small significant reduction in depressive symptoms .The effectiveness of digital mental health interventions on anxiety symptoms was reported in 15 RCTs. The pooled SMD showed a moderate and significant effect of these interventions in reducing anxiety symptoms . Reduced anxiety symptoms were not associated with sample size, location, measurement of anxiety, duration of follow-up, or the duration of intervention.We examined the sources of heterogeneity by studying covariates across studies  and 4. SMeta-regression analyses are reported in P=.57 and P=.50, respectively; For the main analyses of depression and anxiety, we observed evidence of funnel plot asymmetry, which could suggest no publication bias . Individuals with mild to moderate mental health symptoms, which may be addressed by psychosocial support and psychological interventions based on a stepped-care approach, are the target populations for the expanded use of smartphone apps to improve the delivery of mental health services. The technology with broad reach could also be used for psychoeducation , which iThe use of digital mental health services was reported across high-income countries and middle-income countries, but there were no studies from low-income countries. Digital mental health services have great potential in LMICs because of the limited availability of mental health services to cover the population needs  along wiThe finding that digital mental health services are associated with the amelioration of anxiety and depressive symptoms is consistent with previous evidence examining their effects ,87. SubgOur review sheds light on future research. First, further efforts should be focused on how digital mental health services can be integrated with existing traditional treatment modalities to form a complementary and integrated service model. In particular, the integration of medication and digital services remains to be further validated for safety and feasibility. Second, most studies included in our review were digital psychotherapy interventions, suggesting that digital technologies may have facilitated the accessibility of psychotherapy during the pandemic. We found evidence supporting the efficacious delivery of psychotherapies, either guided ,77 or seOur study has implications for policy development in health care. During a pandemic, digital mental health technology can be used as a backup to address psychological demands and broaden service coverage. We urge policy makers to create future industry regulatory laws so that the digital health sector can grow in a way that provides security and effectiveness testing. The development of digital health infrastructure, including information transmission facilities and technical testing methods for data security issues, is also a crucial prerequisite for the future development of digital mental health. If digital mental health services are to continue, there is a need to specify the minimum level of privacy and security that is acceptable. For example, in the United States, digital mental health services have rapidly made changes in response to policies and regulations concerning confidentiality and privacy to promote telehealth delivery of care .Our study has several limitations that should be noted. First, owing to the nature of our research question, the scoping review demonstrated substantial heterogeneity. In the pool of included studies, there was a high heterogeneity in terms of study design, type of techniques, type of mental health services, intervention components, target conditions, populations, and outcomes. Most studies did not have comparisons, and their effectiveness remains to be examined in future studies. For meta-analyses, we found only a few factors that contribute to heterogeneity between studies. The subgroup analyses were based on outcomes and limited by the variations in the type of techniques and type of mental health services. As a result, the findings should be interpreted with caution and read in terms of implications for future research.Second, most participants in our scoping review were from high-income nations, primarily the United States and European countries. There is an urgent need for more independent research that examines the viability, acceptability, and efficacy of digital mental health as a response to pandemics in LMICs, particularly in low-income countries.Third, although the current evidence supports the short-term effectiveness of most digital mental health services, only 2 studies have evaluated the long-term outcomes. A practical evaluation of the long-term benefits of digital mental health services should be undertaken, particularly in urban contexts.Fourth, this study did not include preprint servers in the search, which may lead to the overestimation of our findings. However, a methodological research study of systematic reviews and meta-analyses revealed that including unpublished data (such as preprints) may add new sources of bias, although it does not change the results of reviews . In addiFinally, the target of this study was to evaluate the usability, feasibility, acceptability, and initial efficacy of digital mental health services in the initial phase of the pandemic. Therefore, we limited the data search to the first 2 years of the pandemic. We recommend that future studies should assess whether these services will remain the same or be further refined during other phases of the pandemic.In summary, we have reported a range of digital mental health services delivered during the initial phase of the COVID-19 pandemic. We found that digital mental health services were usable, feasible, acceptable, and effective in response to mental health needs in the initial phase of pandemic across high-income countries and middle-income countries. Our findings also highlight the amelioration of depressive and anxiety symptoms based on the pooled results of the RCTs. To date, the strategies to lessen the COVID-19 pandemic’s negative impacts on mental health remain a subject of much debate. We suggest that policy makers develop, implement, and assess different strategies for addressing the long-term mental health needs of the pandemic and its aftermath. Digital mental health services as novel strategies for promoting psychological well-being can purposively address physical barriers and provide a promising element for future integrated mental health service models in the post–COVID-19 era.


Globally, large-scale COVID-19 vaccination programs are in progress to control the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic , which hHerein we present a misdiagnosed case of remote lymphadenopathy after receiving the CoronaVac vaccine from Sinovac. We highlight its prolonged course, discuss the clinical findings and imaging features, and analyze our misdiagnosis in combination with a relevant literature review.A 34-year-old woman presented with left axillary pain for a week and transient fever (38.6°C) for a day. She denied a medical history of allergic disease, tuberculosis, past malignant tumors, recent infection, trauma, specific medication history, and travel or social history. She received the first and second doses of CoronaVac 5 and 4 months ago, respectively, with both doses delivered to the left deltoid muscle. The possibility of side effects was neglected, as the detection exceeded the expected time interval for an adverse reaction to the vaccine. Physical examination revealed left axillary swelling and tenderness with no localized skin or soft tissue lesions, particularly on the head, neck, chest, or left arm.9/L), the computed tomography (CT) of the head, neck, and chest was normal, and the US of the thyroid, breast, and lymph nodes in other parts of the body and abdomen was also normal (Ultrasonography (US) revealed multiple abnormal left axillary lymph nodes with “alarming” signs 2A–C. Th9/L), lymphocyte count (0.59 × 109/L), hemoglobin (113 g/L), and hematocrit value (33.8%); the peripheral smear showed normal erythrocyte and leucocyte morphology; the coagulation function showed an increase in D-dimer concentration (1.55 mg/L), fibrinogen (3.92 g/L), and prothrombin time (14.6 s); the liver function test showed an increase in lactic dehydrogenase (762 U/L); the inflammatory biomarkers of procalcitonin , serum ferritin , and erythrocyte sedimentation rate  were increased, whereas C-reactive protein and the rheumatoid factors were normal. Immunological tests exhibited negative values for specific infections, including serum IgM antibody titers against influenza virus A/B, parainfluenza virus, respiratory syncytial virus, Epstein–Barr virus, adenovirus, legionella pneumophila, Mycoplasma pneumoniae, Chlamydia pneumoniae, Rickettsia, IgG against hepatitis virus C, syphilis, and HIV antibodies. The quantifications of serum hepatitis B surface antigen (0.00 IU/ml), blood cytomegalovirus DNA (<1.0 × 103), blood Epstein–Barr virus DNA (<1.0 × 103), and serum fungus  again. The US features of the abnormal lymph nodes remained nearly the same, whereas CEUS revealed a noticeable reduction in the hypoperfusion area  uptake in ipsilateral lymph nodes, ranging from intense to gradually regressed after administration  (Few of the cases were detected ng (MRI) , 32, CT ng (MRI) , and mamng (MRI) . These tng (MRI) . Additiong (MRI) .The US has a high diagnostic value in the screening, evaluation, and follow-up of lymphadenopathy ; it presIn this case, the patient underwent 4 successive US examinations that demonstrated dynamic changes during progression and regression. Initially, the US showed increases in the number and size of abnormal lymph nodes, with notably thickened lymphatic cortex 2A–C. Reα–γ). In hindsight, we noted that the initial hypoperfusion area overlapped with the most thickened cortex; moreover, it regressed even earlier than the cortex attenuation. A decrease of hypoperfusion may be an even earlier sign of improvement. We speculated that the COVID-19 vaccine might stimulate immune cells in the nodal cortex, which leads to excessive pressure on tissue microcirculation. The insufficiency of perfusion was represented as filling insufficiency on CEUS. However, this was merely a conjecture regarding pathogenesis without the support of systematic research, and further work is required to elucidate this mechanism.To our knowledge, this case was the first to report the CEUS findings of reactive lymphadenopathy after COVID-19 vaccination. The patient underwent 3 successive CEUS scans that also demonstrated dynamic changes. Initially, CEUS demonstrated hypoperfusion in the deviated center of the largest lymph node. It was markedly narrowed in the second CEUS and became nearly invisible in the third exam , and abnormal coagulation function. A previous study reported a decrease in lymphocytes after COVID-19 vaccination , and eleConcerning the type of COVID-19 vaccine that causes reactive lymphadenopathy, there have been more than 2,000 reported cases after mRNA vaccines and 14 reported cases after adenoviral vectored vaccines , 22, yetRadiologists and clinicians should recognize that reactive lymphadenopathy has become frequently observed in association with the general administration of COVID-19 vaccines. It should be considered a frequent and important differential diagnosis. Rational judgment should be made in the context of vaccination information and subtle imaging interpretations. Herein we propose the existence of a prolonged course of this side effect, the value of US as a diagnostic workup and evaluation, and the first introduction of CEUS through the presented case.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.Written informed consent was obtained from the individual for the publication of any potentially identifiable images or data included in this article.QY and JL were major contributors in preparation of the manuscript. LJ interpreted the patient data and drafted the paper. QY did the literature review. WJ drafted the paper. NC and ML performed the US and CEUS. JL, XW, and DW interpreted the patient data. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.