Greyhounds have been reported to have hyperhomocysteinemia (HHC), but the underlying mechanisms and clinical implications are unclear.Our primary aim was to assess serum concentrations of homocysteine (HCy) and related analytes in Greyhounds and to identify a likely metabolic pathway for HHC. A secondary aim was to determine whether HHC is associated with evidence of oxidative stress.Healthy pet Greyhounds (n = 31) and non‐sighthound control dogs (n = 15).Analysis of serum HCy, cobalamin, folate, and methionine, and plasma cysteine, glutathione, and total 8‐isoprostane concentrations.P < .0001). Cobalamin concentrations were lower in Greyhounds  compared to controls  and were inversely correlated with HCy . Serum concentrations of folate, which is regenerated when HCy is converted to methionine, also were inversely correlated with HCy . Serum methionine concentrations were more than 4‐fold lower in Greyhounds  compared to controls , but this difference was not significant (P = .3). Plasma cysteine, glutathione, and 8‐isoprostane concentrations did not differ significantly between groups.Homocysteine concentrations were higher in Greyhounds  compared to controls (13.9 μmol/L; Our findings suggest a primary defect in conversion of HCy to methionine in Greyhounds, with related impaired folate generation. Ineffective cycling by methionine synthase could lead to secondary cobalamin depletion. Notably, low serum folate and cobalamin concentrations can be observed in Greyhounds without signs of intestinal disease. HHChyperhomocysteinemiaHCyhomocysteine1Homocysteine (HCy) is a nonessential amino acid and precursor of both methionine and cysteine. Hyperhomocysteinemia (HHC) in people is strongly associated with some chronic disorders such as cardiovascular disease, stroke, macular degeneration, and cognitive impairment.In people, HHC can result from genetic defects in the enzymes catalyzing HCy interconversion or from acquired deficiencies in folate (vitamin B9) or cobalamin vitamin B12),2,1). WheGreyhounds have an apparent breed‐related syndrome of HHC.Our primary aim was to assess serum concentrations of HCy, folate, cobalamin, methionine, and cysteine in healthy Greyhound dogs to identify likely metabolic pathways associated with HHC. A secondary aim was to determine whether HHC in clinically healthy Greyhounds is associated with evidence of oxidative stress, as measured by total plasma concentrations of 8‐isoprostanes.22.1Clinically healthy pet Greyhounds, mostly retired racing dogs, were screened for inclusion in the study. Owners provided written informed consent before screening. Clinical histories, including current diet, medications, and supplements, were obtained from all dogs. Dogs were eligible if they were at least 1 year of age, were eating a balanced commercial dog food, and had no evidence of systemic illness on history, physical examination, CBC, or serum biochemical panel. Dogs were ineligible if they were eating a raw diet or grain‐free food, had undergone a diet change in the past month, were receiving antioxidants or dietary supplements of any kind, or were on any medications other than monthly heartworm and flea preventatives.Clinically healthy non‐Greyhound, non‐sighthound dogs, at least 1 year of age and of comparable sex, neuter status, and age (±1 year) as the Greyhounds, also were screened for inclusion in the study, using the same criteria used for the Greyhounds. All dogs were cared for under guidelines approved by the University of Wisconsin‐Madison Institutional Animal Care and Use Committee.2.2At the time of screening, an additional 16 mL of blood was collected (10 mL divided into 2 5‐mL additive‐free serum tubes and 6 mL divided into 3 2‐mL heparinized tubes) for testing associated with the study. Dogs were fasted overnight before blood collection. Serum was separated and frozen at −20°C for analysis of HCy, cobalamin, folate, and methionine. Heparinized blood was placed on ice and immediately treated by addition of bromobimane to 2 tubes (200 μL of 27 mM stock solution per 2 mL blood) to stabilize plasma cysteine and glutathione,Serum folate and cobalamin concentrations were measured using analytically validated chemiluminescent assays (Immulite 2000 platform).2.3U tests. Comparisons of proportions were performed using Fisher's exact tests. Serum HCy concentrations were correlated with age, plasma 8‐isoprostanes, and other biomarkers using Spearman rank correlation. All statistical analyses were performed using commercially available software .Data were assessed for normality using Shapiro‐Wilk tests. Serum HCy, methionine, folate, and cobalamin and plasma cysteine, glutathione, and 8‐isoprostane concentrations were compared between healthy pet Greyhounds and non‐sighthounds using Mann‐Whitney P < .05. As few as 34 dogs total (Greyhound and controls) also would provide adequate power to detect a significant positive correlation of at least 0.47 between HCy and F2‐isoprostane concentrations as previously observed in human patients.http://biomath.info).Based on significant increases in plasma F2‐isoprostane concentrations observed in humans with HHC compared to controls,33.1The median age of both pet Greyhound dogs n = 31) and non‐sighthound controls (n = 15) was 3.5 years, and sex and neuter status were comparable between groups . This same relationship was found in the smaller non‐Greyhound control population, but did not reach significance .As expected, serum HCy concentrations were significantly higher in Greyhound dogs  compared to non‐sighthound controls  and median plasma glutathione concentrations were 3.0 μmol/L in Greyhounds and 2.6 μmol/L in controls .Plasma cysteine and glutathione concentrations did not differ significantly between breed groups. Median plasma cysteine concentrations were 6.7 μmol/L in Greyhounds and 7.9 μmol/L in controls Figure ; P = .36s Figure ; P = .113.3P = .004; Figure r = −0.40, P = .004; Figure Concentrations of serum cobalamin, which is a necessary cofactor for conversion of HCy to methionine, were significantly lower in Greyhounds  compared to control dogs . However, like cobalamin, serum folate concentrations were inversely correlated with serum HCy concentrations across all dogs  compared to controls , possibly because of heterogeneity in the control group .Serum methionine concentrations were observed to be more than 4‐fold lower in Greyhounds  compared to controls , but this difference was not significant  or across Greyhounds .Median plasma isoprostane concentrations were not significantly higher in Greyhound dogs  compared to controls  had cobalamin concentrations that generally are considered low enough to warrant supplementation based on current recommendations from the Gastrointestinal Laboratory at Texas A&M University. Serum cobalamin concentrations in Greyhounds also were significantly and inversely correlated with HCy concentrations in our study. This relationship was not found in the previous study,Serum folate concentrations were below the lower limit of the reference interval (7.7 μg/L) in approximately 55% 16 of 29) of the healthy Greyhounds in our study. Although not significantly different from controls, serum folate concentrations were inversely correlated with serum HCy concentrations. This relationship also was noted in the previous group of Greyhounds.6 of 29 oWe also measured serum methionine concentrations, which were 3‐fold lower in Greyhounds compared to non‐sighthound dogs. Although this difference was not significant because of heterogeneity within breed groups, this finding supports a Greyhound defect in the conversion of HCy to methionine, either by methionine synthase or its recycling enzyme, methionine synthase reductase. Cobalamin is an important cofactor for this pathway, and thus modest deficiencies in cobalamin could further exacerbate a genetic defect in either methionine synthase or methionine synthase reductase.The observation of subnormal serum cobalamin and folate concentrations in some healthy Greyhounds without gastrointestinal signs is important to consider when using these analytes as markers for small intestinal disease. Low serum cobalamin concentrations in Greyhounds could be a result of unrecognized intestinal malabsorption but also could be caused by depletion from an ineffective cycling of methionine synthase.No significant differences were found between groups in plasma cysteine or glutathione concentrations, which does not support impaired conversion of HCy to cysteine as a mechanism of HHC in Greyhounds. Also, no difference was found in plasma 8‐isoprostane concentrations between breed groups, which does not support the hypothesis that HHC leads to systemic oxidative stress in otherwise healthy Greyhounds. This finding differs from previous studies in people where HHC has been associated with increases in plasma 8‐isoprostane concentrations.Although our study has strengths in its prospective screening and use of non‐sighthound dogs as controls, it had some limitations. First, measurement of methylmalonic acid was not included in our study, and thus we were unable to assess cobalamin deficiency on a cellular level.In addition, although each dog in the study ate a consistent diet, the diets varied among individual dogs. The population size was small, and we may have lacked power to detect significant differences in serum methionine concentrations between breed groups. Finally, although HHC is associated with a prothrombotic state in people,MTR) and methionine synthase reductase (MTRR) genes should be performed in Greyhounds to determine whether coding variants are related to inter‐ and intrabreed variability in serum HCy concentrations. Supplementation with B vitamins can improve HCC even in human patients with genetic defects in the conversion of HCy to methionine,Overall, our findings suggest a primary defect in conversion of HCy to methionine in otherwise healthy Greyhounds. We did not find evidence of oxidative stress associated with HHC in this breed using plasma 8‐isoprostane concentrations, but additional measures of oxidative stress should be evaluated. Because HHC can lead to prothrombotic states in people, an assessment of coagulation status is needed in relation to HCy concentrations in Greyhounds. In addition, resequencing of the methionine synthase (Joerg M. Steiner is the Director of the Gastroenterology Laboratory at Texas A&M University, which provides fee‐for‐service assays for some of the analyses included in this study. Lauren A. Trepanier serves as Associate Editor for the Journal of Veterinary Internal Medicine. She was not involved in review of this manuscript. No other authors declare a conflict of interest.Authors declare no off‐label use of antimicrobials.Approved by the University of Wisconsin‐Madison IACUC, protocol V006303‐A01.Authors declare human ethics approval was not needed for this study.


Chenopodium quinoa Willd.) is a pseudocereal with rich nutritional composition, gluten free, and organoleptic. The primary aim of this study was to elucidate the possible protective roles of quinoa in glucose homeostasis in a model of cafeteria diet‐induced obesity. Male Wistar rats (3 weeks of age) were randomly allocated to be fed by; control chow , quinoa , cafeteria , or quinoa and cafeteria  for 15 weeks. CAFQ resulted in decreased saturated fat, sugar, and sodium intake in comparison with CAF. Compared to CON, CAF increased body weight gain, plasma insulin, plasma glucose, decreased liver IRS‐1, AMPK mRNA expressions, and pancreatic β‐cell insulin immunoreactivity, and developed hepatocyte degeneration and microvesicular steatosis. Compared to CAF, QUI lowered body weight, plasma glucose, and plasma insulin, increased liver IRS‐1 and AMPK mRNA expressions, and pancreatic β‐cell insulin immunoreactivity. Compared to CAF, CAFQ lowered plasma glucose, increased liver IRS‐1 mRNA expressions, increased pancreatic β‐cell insulin immunoreactivity, and lowered hepatocyte degeneration and microvesicular steatosis. Dietary treatments did not influence IRS‐2, AKT2, and INSR mRNA expressions. HOMA‐IR, HOMA‐β, and QUICKI were also similar between groups. Restoration of insulin in CAFQ islets was as well as that of CON and QUI groups. In conclusion, as a functional food, quinoa may be useful in the prevention of obesity and associated metabolic outcomes such as glucose intolerance, disrupted pancreatic β‐cell function, hepatic insulin resistance, and lipid accumulation.Quinoa ( Chenopodium quinoa Willd.) diet decreased plasma glucose and insulin levels and increased insulin sensitivity in the liver. The cafeteria diet resulted in increased body weight, glucose intolerance, impaired hepatic insulin signaling, microvesicular steatosis, and reduced β‐cell insulin immunoreactivity. Quinoa added to the cafeteria diet reduced body weight and improved glucose intolerance, hepatic insulin signaling, and microvesicular steatosis.The pseudocereal quinoa ( Rates of obesity have nearly tripled since 1975 according to World Health Organization's global obesity data WHO, . The neeQuinoa is an Andean origin pseudocereal, is known as the “mother of all grains”, and considered as a “golden grain” by civilizations in ancient times , quinoa diet , cafeteria diet , or quinoa and cafeteria diet  for 15 weeks.All experiments were performed in accordance with Directive 2010/63/EU under the license from the Ethics Committee of Erciyes University, Kayseri, Turkey, number: 18/007 and checks ARRIVE guidelines. All animals were housed individually in plastic cages and subjected to a 12‐h light–dark cycle (08.00 and 20.00) at a temperature of 23 ± 3°C and 45% humidity. The animals had ad libitum access to food and water at all times. After 1 week of habituation (standard chow and drinking water), male Wistar rats (3 weeks of age) were randomly allocated to be fed by one of the following four diets; control chow diet   from the samples obtained at 0, 30, and 60 min  index, the quantitative insulin sensitivity check index (QUICKI), and homeostatic model assessment of β‐cell function (HOMA‐β). The equations were as follows:HOMA‐IR = fasting insulin (μU/mL) × fasting glucose (mg/L)/405 )]/[fasting glucose (mmol/mL‐3.5)]  was taken by cardiac puncture. Further, commercially available ELISA kits  were used to measure plasma levels of insulin‐like growth factor‐1 (IGF‐1) and glucagon‐like peptide‐1 (GLP‐1).2.3‐ΔΔCt method as previously described and normalized using housekeeping gene  according to the manufacturer's protocol. The quantity and quality of isolated RNA were measured using NanoDrop 2000 Spectrophotometer (Thermo Scientific). Following isolation, RNA samples were stored at –80°C for further use in expression studies. The total RNA was converted to first‐strand complementary DNA using the RT2 First Strand Kit (QIAGEN), and incubated at 42°C for 15 min, with a next step of 5 min at 95°C. Quantitative real‐time PCR was used to measure mRNA expression levels of IRS1, IRS2, AKT2, AMPK, and INSR genes using SYBR Green I Master Kit . PCR amplification was carried out using LightCycler® 480 II Real‐Time PCR System . Cycling conditions were 95°C for 10 min, followed by 45 cycles of 95°C for 15 s, and 60°C for 1 min. All samples were studied in duplicate. ACTB (β‐actin) was used as the housekeeping gene. The relative expression of each mRNA was determined by the 22.4At the end of the experiment, the liver and pancreatic tissues of rats were removed and detected in 4% formaldehyde solution. Standard histopathological techniques were applied to the liver and pancreatic tissues waiting in fixation solutions. Then tissue sections from the organs were taken and embedded in paraffin following dehydration  and clearing (xylene). Five‐micrometer‐thick paraffin‐embedded liver sections of all rats were stained with hematoxylin–eosin (H&E) and periodic acid–Schiff (PAS) for a histological assessment as previously described. Digital photomicrographs of stained tissues were captured at 200× magnification using a light microscope (Olympus BX51) . The pancreatic sections kept at 60°C overnight were washed in phosphate‐buffered saline (PBS) by passing through a series of xylene and then graded alcohol. It was then treated with a 5% citrate buffer for antigen recovery. Hydrogen peroxide (3%) was applied to the sections washed in PBS. For the next steps, staining kit  was used. After treatment with diaminobenzidine  to make immune reactivities visible, they were washed with deionized H₂O. Counterstained sections with Gill hematoxylin were washed. Finally, the sections passed through xylene by removing the water with increasing alcohol series were covered with a sealing medium  and examined under a light microscope (Olympus BX51). Morphometric measurements of immunoreactivity intensity of insulin in ß‐cells from the digitalized images of sections were carried out using the ImageJ program. Data were obtained from one pancreas section from each animal , and a total of 45 islets were analyzed per group  was examined using repeated‐measures analysis. Values are expressed as mean with their standard errors. p < .05 was considered statistically significant. Post‐hoc testing (Tukey's test) was applied to define the main effects of the diets  , treatment time (p < .001), and interaction between diet and treatment time (p = .028) were statistically significant , a significant interaction between diet and treatment time indicated that body weight changes were different over weeks  Figure . When avt Figure . The fint Figure . The bodt Figure .p < .05). While rats fed the CAF had similar energy intake to CON, rats fed the CAFQ had lower energy intake than CON. Carbohydrate intake was significantly lower in QUI, CAF, and CAFQ than in CON. CAF and CAFQ had significantly lower protein intakes in comparison with CON and QUI. The impact of diet on fat intake of the animals was apparent as rats fed the CAF and CAFQ had significantly increased fat intake in comparison with those fed the CON and QUI. At this point, fat intake of CAF and CAFQ groups was similar. The different nutritional composition of QUI diet was reflected in nutritional intakes of animals in this group as their fat and protein intakes were significantly higher than CON. CAF group had the highest intake of saturated fatty acids, sugar, and sodium, whereas these nutrient intakes decreased in rats fed CAFQ diet. Fiber intake of CON and CAFQ was similar, whereas CAF had lower, and QUI had higher fiber intakes . Post‐hoc analysis showed that plasma glucose levels were significantly lower in QUI and CAFQ compared to CAF at 30 min postinjection (p < .05). A similar pattern was also observed at 60 min postinjection (p < .05). At 90 min postinjection, plasma glucose levels were significantly lower in QUI compared to CAF (p < .05) and all groups displayed comparable levels at 120 min postinjection . In addition, the AUC of glucose was significantly higher in CAFQ than in QUI (p < .05)  Figure .p < .05) and the groups CON, CAF, and CAFQ did not exhibit a further difference. At 60 min, CAFQ group had significantly higher insulin levels than CAF. Despite the differential effects of dietary treatment on glucose and insulin levels of the study groups, other parameters in plasma related to glucose homeostasis such as HOMA‐IR, HOMA‐β, and QUICKI were similar between groups. Further, plasma levels of GLP‐1 were found to be similar, whereas plasma IGF‐1 levels showed significantly different among the diet groups. CAFQ exhibited significantly higher IGF‐1 levels than QUI and CAF , and insulin receptor (INSR) were unaffected. The IRS‐1 expression was significantly upregulated in QUI (p < .001) and downregulated in CAF (p < .05) when compared to CON. The addition of quinoa in cafeteria diet exerted a normalization in the expression of IRS‐1 since CAFQ had similar expression level of IRS‐1 in comparison with CON (p > .05). Among the rats exposed to QUI diet, the expression of AMPK was significantly higher than CON (p < .001). Although CAFQ exhibited a similar expression of AMPK in comparison with CAF (p > .05), the levels were also like CON, whereas CAF displayed significantly lower expression of AMPK than CON (p < .05)  and AMP‐activated protein kinase (AMPK), whereas IRS‐2, RAC‐beta serine/threonine‐) Figure .The CON group exhibited normal liver architecture with regular hepatocyte cell cords organized radially from the vena centralis. Moreover, regularly distributed sinusoids were observed between the cell cords, whereas the portal areas had also a regular arrangement. The nuclei of the hepatocytes were clearly observed. Hepatocyte cell cords, sinusoid localization, and portal areas appeared to be normal. Similar results were obtained from histological analysis of liver sections of QUI group. As compared to CON group, exposure to CAF diet induced microvesicular steatosis, which was observed in hepatocytes close to some portal areas. In CAF group, partial degeneration in hepatocyte cell nuclei and more acidophilia staining in some hepatocytes was remarkable. In addition, dispersion of some cell cords radially extending from the vena centralis in some areas of the hepatic tissues and narrowing of the sinusoids was observed. Supplementation with quinoa in CAF diet‐fed rats substantially alleviated microvesicular steatosis. In the CAFQ group, hepatocyte degeneration was slighter than that in CAF group Figure . No appr3.4The CON group showed strong immunoreactivity of insulin in ß‐cells in the form of dark brown granules which occupy most of the islet. Immunostained ß‐cells from CON group appeared to be similar to that of QUI group. As compared with CON and QUI groups, a noteworthy reduction in the immunohistochemical expression of insulin in ß‐cells was observed in pancreatic section of a CAF group. Insulin immunoreactivity was also observed in the cytoplasm of beta cells in pancreatic islets belonging to the CAFQ group Figure .Morphometric analysis revealed that insulin expression in QUI group was similar to that of CON group as evidenced by photomicrographs of insulin immunohistochemical staining of pancreatic islets. Furthermore, immunoreactivity density in CAF group significantly decreased in comparison with CON and QUI groups. Immunoreactivity density tended to increase in CAFQ group compared to the CAF group, but the difference was not statistically significant. Moreover, restoration of insulin in CAFQ islets was as well as that of CON and QUI groups Figure .4Cafeteria diet induces a phenotype of obesity with glucose intolerance and inflammation as a model of human metabolic syndrome ; investigation (lead); resources (lead). Derya Karabulut: Formal analysis ; methodology ; resources . Gonza Kamaci Ozocak: Formal analysis ; methodology ; resources . Ecmel Mehmetbeyoglu: Formal analysis ; methodology ; resources . Emin Kaymak: Formal analysis ; methodology ; resources . Betul Kisioglu: Data curation ; visualization ; writing – original draft . Betul Cicek: Funding acquisition (lead); project administration (lead). Asli Akyol: Conceptualization (lead); methodology (lead); supervision (lead); writing – review and editing (lead).This work was supported by the Scientific Research Projects Coordination Unit of Erciyes University (No. TDK‐2018‐8222).The authors declare that they have no competing interests.This study was approved by the Erciyes University Local Ethics Committee for Animal Experiments (HADYEK), Kayseri, Turkey under the license from the number: 18/007.


To analyse the characteristics and mortality of hypertrophic cardiomyopathy (HCM) patients with different body compositions.In this study, 530 consecutive patients with HCM at West China Hospital were studied from November 2008 to May 2016. An equation based on body mass index (BMI) was used to obtain the Percent body fat (BF) and lean mass index (LMI). Patients were divided into five sex-specific BMI, BF and LMI quintiles.2, 28.1 ± 7.3% and 16.5 ± 2.2 kg/m2, respectively. Patients with higher BMI or BF were older and had more symptoms and adverse cardiovascular conditions; those with higher LMI were younger and had less coronary artery disease and lower serum NT-proBNP and creatine. BF correlated positively with resting left ventricular (LV) outflow tract gradient, mitral regurgitation (MR) degree and left atrial diameter but was inversely associated with septal wall thickness (SWT), posterior wall thickness (PWT), LV mass, and E/A ratio; LMI was positively correlated with SWT, LV end diastolic volume and LV mass but was negatively associated with MR degree.48 all-cause deaths occurred during a median follow-up of 33.8 months. Reversed J-shape associations of BMI and LMI with mortality were observed. A lower BMI or LMI was significantly associated with high mortality, especially for low-moderate BMI and LMI. No significant difference in mortality was found across BF quintiles.The average BMI, BF and LMI were 23.1 ± 3.2 kg/mThe associations of BMI, BF and LMI with baseline characteristics and cardiac remodelling are different in HCM patients. In Chinese HCM patients, low BMI and LMI predicted mortality but not BF. Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disorder with heterogeneity in its natural history. Although HCM-causing mutations are believed to be the main prognostic factor of HCM patients, a gene-based model is still unable to predict outcomes . In factObesity has become a major health concern as a result of the change in modern lifestyles. The population with obesity is more vulnerable to cardiovascular disease. However, in the context of chronic diseases, including chronic heart failure , chronicBMI, an index universally applied to measure obesity, has been questioned under the background of the obesity paradox in cardiovascular disease . Fat masThe data of this study were obtained from the hypertrophic cardiomyopathy database of West China Hospital. The database includes data from consecutive patients diagnosed with HCM at West China Hospital of Sichuan University from November 2008 to May 2016, and the collected data includes demographic, clinical, laboratory and treatment data. Patients with the following conditions will be excluded: (1) patients with malignant tumors, (2) patients with severe aortic valve disease and (3) patients with end-stage renal failure. All patients have been informed consent, so that their medical records for research purposes. The study got the West China Hospital of Sichuan University Ethics Committee approval.3 − (LVEDD)3]} + 0.6 g.All patients were assessed by echocardiography as recommended by the American Society of Echocardiography . Two-dim2). The Clínica Universidad de Navarr—Body Adiposity Estimator (CUN-BAE) equation was applied to estimate percentage BF: BF = −44.988 + (0.503 × age) + (10.689 × sex) + (3.172 × BMI) − (0.026 × BMI2) + (0.181 × BMI × sex) − (0.02 × BMI × age) − (0.005 × BMI2 × sex) + (0.00021 × BMI2 ×age), where sex is replaced by 0 for males and 1 for females  by the square of the height , symptoms of HCM, smoking history, and family history of sudden cardiac death were obtained from hospital records and collected by trained research investigators. Cardiologists assess the risk of sudden cardiac death (SCD) according to the HCM Risk-SCD tool . Venous During follow-up, the primary event recorded was all-cause mortality and the secondary event was cardiovascular mortality. Patients themselves and/or their family members were contacted by telephone or through outpatient visits for follow-up information. Most of the patients visited outpatient appointments every 1–6 months. All the data were consistent with the hospital records.It was inappropriate or impossible to involve patients or the public in the design, or implementation, or reporting, or dissemination plans of our study.χ2 test or Fisher's exact test was applied to compare categorical variables. Data were compared using one-way analysis of variance if they followed a normal distribution; or else, the data were compared using the Kruskal-Wallis test. Single correlations between body composition and echocardiographic characteristics were evaluated using Pearson's correlation test when the values were normally distributed; otherwise, they were analysed using Spearman's rank correlation test. To determine the association between body composition and outcomes, survival across body composition categories was plotted in Kaplan-Meier curves and compared using the log-rank test. Then, multivariate Cox proportional hazard analyses were applied to identify the independent effects of baseline body composition characteristics on time until death. Possible confounding factors of age, sex and medical history  were adjusted; septal wall thickness (SWT); LVOT obstruction; LV wall thickness > 30 mm; LV ejection fraction (LVEF); treatment with β blockers, non-dihydropyridine calcium channel blockers, angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers; and alcohol septal ablation. The method described by Grambsch and Therneau was used to assess the assumption of proportional hazards . Categorical variables are represented as counts (percentages). The  hazards . Restric2, 28.1 ± 7.3% and 16.5 ± 2.2 kg/m2, respectively. The distributions of the patients' baseline data across BMI, LMI and BF quintiles are showed in 530 patients with complete BMI data from the West China Hospital Hypertrophic Cardiomyopathy database were included in the present study. The average age of these patients was 54.5 ± 16.4 years, and 54.2% of the enrolled patients were male. The average BMI, BF and LMI were 23.1 ± 3.2 kg/mWe further explored the potential correlations between body composition and various echocardiographic data . BMI wasP for all-cause mortality < 0.001 and P for cardiovascular mortality = 0.012, P for all-cause mortality = 0.545 and P for cardiovascular mortality = 0.097, Over a median follow-up of 33.8 months , a total of 48  deaths occurred, and of those deaths, 31  were ascribed to cardiovascular causes. Kaplan-Meier plots suggested that the risk of all-cause and cardiovascular mortality was higher in the low BMI group . SimilarThe univariate and multivariate HRs for all-cause and cardiovascular mortality by body composition variables are displayed in 2, such that a higher BMI was independently correlated with a lower risk of death  HCM patients. The inverse relationship of LMI with mortality seemed to be stronger until approximately 18 kg/m2 of LMI. However, BF was not significantly associated with mortality in HCM patients.In this cohort study of 530 Chinese HCM patients, we used a validated anthropometric prediction equation to examine the association of BF and LMI with all-cause and cardiovascular mortality. We found that mortality was inversely related to BMI, especially among normal weight  and Chinese (23.1 kg/m2) studies, our data may reflect the exclusive relationship between BMI and outcomes in the Chinese HCM population who have relatively low BMI levels.Obesity is emerging as a public health problem and a well-known risk factor for cardiovascular disease. Recently, a Sweden nationwide registry-based prospective cohort study showed that obesity in adolescence resulted in an increased risk of HCM in midlife . MoreoveThe obesity paradox has been documented in patients with coronary artery disease, chronic heart failure and several chronic vascular diseases, but it remains controversial. One of the arguments against the obesity paradox focused on the defect of BMI in measuring body composition (lean mass and fat mass). In fact, Oreoponlous et al. showed that BMI, as a surrogate for obesity, had a better relationship with lean mass than BF. BMI-measured obesity is sometimes associated with excess muscle rather than fat . Higher Obesity has been shown to result in abnormal cardiac remodelling and function mediated by fat-derived inflammatory cytokines. Olivotto et al. demonstrated that obesity indexed by BMI was associated with increased LV mass and LA diameter, LVEDD and greater LVOT obstruction . When co2 could be attributed to the low risk of death associated with high lean mass. The stabilized association between BMI and mortality in the higher BMI range (>24 kg/m2) was likely due to the counteracting of the opposite influence of BF and LMI on mortality. In fact, the prognostic value of LMI has been documented in a broader population. In a prospective study of an Asian population, Han et al. suggested that higher LMI was associated with better survival; whereas, BF was not associated with mortality (As far as we know, this is the first study to investigate the relationship between body composition and the mortality of HCM patients. Our data added a new insight that the reversed J-shaped relationship between BMI and morality in HCM patients can be explained by a combination of the association of LMI and BF with mortality. The decreased mortality associated with high BMI within the range of less than 23 kg/mI range > kg/m2 wavia the CUN-BAE equation can be easier to accept by clinicians. Secondly, this is a retrospective observational study that was conducted in a single tertiary referral centre, with inherent biases compared to real-world studies. Third, the study recruited only Chinese HCM patients with a mean BMI of 23.1 kg/m2. Therefore, the extrapolation of these results to other race/ethnicities, especially Caucasians who have much higher BMIs, must be performed cautiously.There are some limitations in our research that should be noted. Firstly, although this study looked at the association between body composition and mortality, BF and lean mass were obtained from formulas and not directly measured. Therefore, direct measurement of lean mass and BF using methods such as dual-energy x-ray absorption and bioelectrical impedance requires further investigation. However, in terms of clinical application, the direct measurement of BF and lean mass is unpractical due to its cost. The CUN-BAE equation was obtained by analyzing a large population and subsequently validated in several other studies. In a sense, the assessment of lean mass derived from BMI In a cohort of the Chinese population with HCM, we provided evidence showing that when BMI is divided into fat and lean mass components, the associations of LMI or BF with baseline cardiovascular factors and cardiac remodelling are entirely different. Patients with higher LMI had a benign cardiovascular profile, lower MR degree and increased LV mass and LVEDV, while patients with higher BF had more concomitant clustered cardiovascular conditions and an increased LVOT gradient, MR degree and diastolic dysfunction. With respect to outcomes, reversed J-shape relationships of BMI and LMI with mortality were observed. Patients with higher BMI or LMI were related to a lower risk of mortality, especially in the low range of BMI and LMI. BF was not significantly associated with mortality in HCM patients.


IRF4 rearrangement  has been recently recognized as a specific entity that is frequently associated with young age and favorable prognosis. However, whether the good outcome of the disease is due to IRF4+ or other factors remains obscure. We thus analyzed 100 young patients with primary head and neck LBCL to see the clinicopathologic correlates of IRF4+.Large B‐cell lymphoma with IRF4 status of the tumors, and clinical data were reviewed.The histopathology, immunophenotype, IRF4+, which were more frequently associated with a follicular growth pattern, medium‐sized blastoid cytology, germinal center B‐cell‐like, and CD5+ phenotype, compared with IRF4− ones. While most of the patients received chemotherapy with or without radiation, eight IRF4+ patients received mere surgical resection of the tumor and exhibited excellent outcome. IRF4+ cases featured a significantly higher complete remission rate, and better survivals compared with IRF4− ones. Multivariate analysis confirmed IRF4+ correlates with a better survival.Twenty‐one tumors were diagnosed as LBCL, IRF4+, and disclosed for the first time the independent favorable prognostic impact of IRF4+. These findings may further unravel the heterogeneity of LBCL occurring in youth, and aid in risk stratification and tailoring the therapeutic strategy.Our work confirmed the unique clinicopathologic features of LBCL,  IRF4 gene not only defines a group of LBCL with distinct clinicopathologic features, but also is of practical implications for prognosis prediction and therapeutic strategy decision.The rearrangement of  Those lymphomas were overwhelmingly of the germinal center B‐cell (GCB) subtype, and featured high‐level expression of IRF4/MUM1 protein, but lacked the t /BCL2 gene translocation. It was found such lymphomas possessed a distinctive gene expression profile.IRF4 and NF‐kB‐related gene mutations, overexpression of the downstream genes of the NF‐kB pathway, losses of 17p13 and gains of chromosome 7, 11q12.3‐q25.IRF4+ hence represents a previously unrecognized subset of B‐cell lymphomas with distinctive clinicopathologic characteristics and molecular alterations.In 2011, the translocations of IRF4+ patients are children and young adults with a GCB‐derived tumor, and the probability of IRF4 rearrangement has been reported to decrease significantly with aging,IRF4+ is attributable or related to the young age or the molecular changes such as IRF4 rearrangement. In other words, whether IRF4 rearrangement is an independent prognostic factor of LBCL in children and young adults remains unclear.Most pediatric germinal center‐derived B‐cell non‐Hodgkin lymphomas, such as follicular lymphoma or diffuse LBCL (DLBCL), feature a relatively favorable outcome. Given the facts that most LBCL, IRF4 rearrangement in young patients with a primary head and neck LBCL.We thus conduct the current retrospective case–control study to evaluate the clinicopathologic correlates of 22.1Patients with DLBCL diagnosed between 2015 and 2020 were selected from the files of the Department of Pathology, Fudan University Shanghai Cancer Center. All of the selected cases fulfilled the following criteria: (1) patients with a Stage I–II disease of primary DLBCL of the head and neck region at the age ≤35 years, (2) transformed DLBCL from other low‐grade B‐cell lymphomas were excluded. Altogether 106 cases were collected, among which 100 with follow‐up information and available materials were employed for pathologic review. Clinical data, including sex, age, Ann Arbor stage, B symptoms, treatment, and the outcome were collected either from medical records or by telephone inquiries. The use of human tissue samples was approved by the Ethics Committee at Fudan University Shanghai Cancer Center.2.2Formalin‐fixed, paraffin‐embedded (FFPE) specimens were used for the morphological and ancillary studies. Routine hematoxylin and eosin‐stained sections were reviewed by three of the authors  and diagnosis was rendered according to the updated WHO classification.2.3BCL2, MYC , and IRF4  was performed by using FISH. A positive result was concluded when ≥15% of tumor cells demonstrating split signals. Epstein–Barr virus (EBV)‐encoded small RNA (EBER) was detected by in situ hybridization.Immunohistochemical and FISH analyses were performed by using standard protocols. FFPE sections were stained with primary antibodies against CD5 , CD10 , BCL6 , BCL2 , MYC , and IRF4/MUM1  on a BenchMark XT automated immunostainer . A positive result was concluded if ≥30% of tumor cells were stained with antibodies against CD10, BCL6, and MUM1. GCB and non‐GCB subtypes of DLBCL were determined by the Hans algorithm.2.4p < 0.1 in univariate analysis were submitted for multivariate model analysis. The results were considered statistically significant if a p value <0.05. Statistical analysis was carried out by using GraphPad Prism .Overall survival (OS) was calculated from the date of diagnosis to the date of death or the last follow‐up. Progression‐free survival (PFS) was calculated from the date of diagnosis to the date of disease progression, relapse, death from any cause, or the last follow‐up. The survival rates of DLBCL patients were estimated by the life table method. OS and PFS curves were generated by using the Kaplan–Meier method and the log‐rank test. Multivariate analyses were performed using a logistic regression model for response and Cox regression models for survival. All variables with a value of 33.1IRF4 rearrangement was detected in 21 patients. The median age of IRF4+ cases was 17 years, with a male to female ratio of 2:1. The most common site of involvement was cervical lymph nodes (61.9%), followed by Waldeyer ring/tonsils (38.1%). All of the IRF4+ cases featured an IPI score of 0–2, and all except one case were demonstrated to have Stage I disease. No obvious differences in the distribution of age, sex, tumor location, staging, or IPI score were observed between the IRF4+ cases and those lacking IRF4 rearrangement (IRF4−).The clinical and pathologic characteristics of the 100 young patients with a Stage I–II disease of primary DLBCL of the head and neck region are summarized in Table IRF4− cases, IRF4+ tumors exhibited more frequently a follicular growth pattern (42.9% vs. 11.4%) (p = 0.0020). In the current study, we defined a follicular pattern by the presence of more than one low‐power field (2.4 mm2) comprising compact, or sometimes, confluent neoplastic follicles  .Histologically, the vast majority of the cases displayed changes compatible with a diagnosis of DLBCL. Of note, nine cases each of both cohorts displayed a concurrent follicular component, that is, follicular LBCL, in addition to the diffuse neoplastic infiltrate. Compared with s Figure . Follicus Figure . Scattere Figure . Cytolog) Figure , with ths Figure   featured a GCB subtype  displayed a non‐GCB phenotype (p = 0.001). Of note, 23.8% of IRF4+ tumors were CD5‐positive  (p = 0.0010). In general, CD5‐positive LBCL, IRF4+ cases demonstrated similar clinicopathologic characteristics with CD5‐negative LBCL, IRF4− ones, although the former tended to be more frequently associated with younger patients, Waldeyer ring lesions, and medium‐sized blastoid cytology (p < 0.0001)  Table . In addis Figure . Neither3.2IRF4− cases (94.9%) received chemotherapy or combined treatment, a remarkable proportion (38%) of LBCL, IRF4+ cases received surgical excision only and were not submitted for further chemoradiotherapy (p < 0.0001).The patients received diverse treatments, including surgical excision, immunochemotherapy, with regimens most commonly of R‐CHOP  and occasionally of R‐CVP , excisional surgery followed by chemotherapy, or sometimes combined chemotherapy and radiotherapy with or without a prior tumor mass excision. Involved site radiation therapy was administered to 10 patients in 1 month after the last cycle of chemotherapy, with a prescribed dose of 30 Gy  than the LBCL, IRF4− ones (88.6%) (p = 0.0030). In addition, more advanced stage and a non‐GCB phenotype also had an adverse impact on the response rate. In the logistic regression, the only variable showing an independent adverse influence on the CR rate was a higher stage (II), with a risk ratio (RR) of 6.9% and 95% confidence interval (CI) of 1.2–43.9 (p = 0.047).As for the outcome to the treatment Table , altogetIRF4+ patients had a better OS (100% vs. 82.3%) (p < 0.0001) and PFS (100% vs. 79.7%) (p < 0.0001) than IRF4− patients    instead of OS  (p = 0.0499) and PFS  (p = 0.0328), whereas a more advanced stage was only associated with an unfavorable PFS  (p < 0.0001).After a median follow‐up of 60.5 months, the 5‐year OS and PFS in the global series were 86% and 84%, respectively. s Figure . Univari) Figure  and PFS ) Figure , whereasS Figure . There w4DLBCL represents a large group of biologically heterogeneous neoplasms, among which have been recognized some specific entities or subtypes with characteristic clinicopathologic and molecular features, such as plasmablastic lymphoma, EBV‐positive DLBCL and so on, whereas the remaining ones are provisionally labeled as DLBCL, not otherwise specified (NOS), in the WHO classification. DLBCL may affect any site of the body, including the head and neck region. Most head and neck DLBCL cases actually represent systemic disease with head and neck involvement, while about 40% of DLBCL cases are localized to head and neck sites, that is, primary head and neck lymphomas, with both nodal and extranodal involvement. Any extranodal site may be involved, including Waldeyer ring/palatine tonsil, palate, mandible, maxilla, and tongue.IRF4+ is a rare disease affecting most frequently children and young adults, with a decreasing relative incidence with age among all LBCLs.IRF4:IG juxtaposition. Although IRF4 rearrangement is a defining feature of this special type of lymphoma with relatively favorable prognosis, it should be noted such a molecular alteration is not specific for the entity. Since it has been found that IRF4 rearrangement can occur in some other aggressive B‐cell lymphomas as well, especially those which are associated with MYC or BCL2 rearrangement, mainly in adults.IRF4+ and IRF4− ones, and to observe the prognostic implication of IRF4 rearrangement in these patients. The LBCL, IRF4+ cases in the current study present most frequently with cervical lymphadenopathy or tonsillar masses. A slight male predominance, although not statistically significant, is noticed in the IRF4+ patients compared with IRF4− ones. Histologically, the presence of a follicular growth pattern may be highly suggestive of a potential diagnosis of LBCL, IRF4+, which is much less frequently observed in IRF4− cases. The cytologic features of IRF4+ tumors differ from those of IRF4− ones, too, since the characteristic medium‐sized blastoid cells are rather commonly seen in IRF4+ tumors, but are generally lacking in the latter ones. In addition, the cell‐of‐origin subtype of the tumors seems critical for the diagnosis of LBCL, IRF4+, as all but one case feature a GCB phenotype. In contrast, 40% of IRF4− cases are of non‐GCB subtype. None of the tested cases in our series carries chromosomal translocations involving the MYC or BCL2 gene, which is also in consistent with that documented in the literature.IRF4+, therefore, seems to harbor low genomic complexity. It is noteworthy that a small fraction of LBCL, IRF4+ cases may also harbor BCL6 rearrangement, most of which are young adult patients with Waldeyer ring, cervical lymph node, or bowel involvement.IRF4 and BCL2 rearrangement have been recognized as well, which frequently affects other sites of older adults, and is often morphologically atypical, and may thus represent DLBCL, NOS, rather than typical LBCL, IRF4+.LBCL, IRF4+ includes first pediatric‐type follicular lymphoma (PTFL), which also affects children and adolescence predominantly, and present similarly with a follicular lymphoid proliferation composed of large neoplastic cells. PTFLs, however, are principally nodal lesions and rarely involve extranodal sites.IRF4 translocation.IRF4+ frequently harbors mutations of NF‐kB‐related genes such as CARD11. Intriguingly, CARD11 alterations are present exclusively in cases with a diffuse growth pattern, while the MAP2K1 gene mutations are predominantly present in PTFL,IRF4+, too, due to the similar morphological findings and a frequent IRF4/MUM1‐positive phenotype, but conventional FL3B occurs more commonly in adults, and lacks the IRF4 translocation.IRF4+ may express CD5, distinction with CD5‐positive DLBCL should be also taken into consideration; the later more frequently affects adults, and usually lacks follicular components and IRF4 rearrangement.IRF4+ cases with CD5 or CD23 expression need to be distinguished from prolymphocytic progression or large cell transformation of chronic lymphocytic leukemia/small lymphocytic lymphoma. The latter, however, is basically a disease affecting elderly population, and LEF1 positivity and lack of IRF4 rearrangement may aid in differential diagnosis as well.The differential diagnosis of LBCL, IRF4+ is a peculiar lymphoma type associated with relatively favorable prognosis.IRF4 rearrangement, or other clinical and pathologic features of this tumor, such as the young age of the patients, relatively early‐stage disease at presentation, and a predominant GCB‐derived tumor phenotype, which are all well‐known factors associated with a better prognosis. We hence design the current study to compare the clinicopathologic characteristics of LBCL, IRF4+ and LBCL, IRF4− that occur in the head and neck region of young patients with limited stage disease. The results indicate that IRF4+ cases feature better initial response to the treatment and better survival during follow‐up. To ascertain whether the cell‐of‐origin, that is, GCB and non‐GCB subtypes, will influence the biological behavior, we further conducted subgroup analysis  correlates with a relatively favorable outcome in those DLBCLs arising from the head and neck region. Of note, while Stage I correlates with a better PFS only, the rearrangement of IRF4 correlates not only with a superior PFS, but also a better OS. Therefore, it seems reasonable and necessary to enroll both clinical staging and the detection for IFR4 rearrangement into the prognosis‐estimating system for those young patients with limited stage disease of DLBCL involving the head and neck region. Twenty‐five percent of IRF4+ cases in our series were CD5‐positive LBCLs; such an incidence is almost the same as that documented in the literature. CD5 can be expressed in 5%–10% of DLBCL, NOS, and CD5‐positivity is believed to be associated with an inferior outcome of this tumor.IRF4+ case series, CD5‐positivity seems to have no effects on the behavior of this tumor.It has been indicated that LBCL, is Table , and fouIRF4+ patients have been administered systemic treatment, including chemotherapy, with or without radiation, and the cure rate is usually high.IRF4+ patients in our series received mere surgical resection, without additional chemotherapy or radiation, all of whom turned to be cured later. These patients were all characterized by localized lesions (Stage I and no bulky disease), and other clinicopathologic characteristics comparable with those patients who had received systemic treatment ; formal analysis (lead); funding acquisition ; investigation ; methodology (lead); project administration ; software (lead); visualization (lead); writing – original draft (lead); writing – review and editing . Fang Yu: Data curation ; investigation ; resources . Tian Xue: Data curation ; investigation ; methodology . Qing‐Xin Xia: Resources . Qian‐Ming Bai: Investigation ; methodology ; software . Bao‐Hua Yu: Resources . Ruo‐Hong Shui: Resources . Xiao‐Yan Zhou: Methodology ; validation . Xiong‐Zeng Zhu: Validation . Jun‐Ning Cao: Validation . Xiao‐Nan Hong: Validation . Xiao‐Qiu Li: Conceptualization (lead); investigation (lead); project administration (lead); resources (lead); funding acquisition ; supervision (lead); validation (lead); writing – review and editing .This work was supported by grants from the Chinese Society of Clinical Oncology (No. Y‐XD202001‐0152), Science and Technology Commission of Shanghai Municipality (No. 22YF1408200), and Shanghai Anticancer Association EYAS Project (No. SHCY‐ZH‐202106).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.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Table S3.Click here for additional data file.


The outcomes were all‐cause and cardiovascular mortality. Cox proportional hazards models were used to explore the association between LVH and the outcomes. C‐statistics and time‐dependent receiver operating characteristic curve (ROC) was used to evaluate the value of those indicators. During a median follow‐up of 49 months (interquartile range 2–54 months), 174 participants (7.1%) died from any cause (n = 174), with 71 died of cardiovascular disease. LVM/BSA defined by the Chinese thresholds was significantly associated with cardiovascular mortality . LVM/BSA was significantly associated with all‐cause mortality using Chinese thresholds  and using Guideline thresholds . LVM/Height1.7 was significantly associated with all‐cause mortality using Chinese thresholds  and using Guideline thresholds . LVM/Height2.7 was not significantly associated with all‐cause mortality. C‐statistics indicated that LVM/BSA and LVM/Height1.7 by Chinese thresholds had better predictive ability for mortality. Time‐ROC indicated that only LVM/Height1.7 defined by Chinese threshold had incremental value for predicting mortality. We found that in community hypertensive populations, race‐specific thresholds should be used to classify LV hypertrophy related to mortality risk stratification. LVM/BSA and LVM/Height1.7 are acceptable normalization method in Chinese hypertension.To compare the predictive value of mortality between left ventricular hypertrophy (LVH) defined by Chinese thresholds and defined by international guidelines in hypertension individuals and investigate better indexation methods for LVH in Chinese population. We included 2454 community hypertensive patients with Left ventricular mass (LVM) and relative wall thickness. LVM was indexed to body surface area (BSA), height One method for overcoming the limitation has been indexing LVM to body size. Most commonly this is done by dividing LVM by body surface area, height22.1This was a community‐based cohort study conducted in Liao Bu County, Dongguan, Guangdong Province, China, as previously reported.2.22 was defined as obesity.2) = (Weight [kg]0.425 * Height [cm]0.725) * 0.007184. Fasting venous blood was used to assess fasting plasma glucose (FPG), lipid profiles, and serum creatinine, which was used to calculate estimated glomerular filtration rate (eGFR) using the Modification of Diet in Renal Disease formula,2 was defined as chronic kidney disease (CKD).Clinical characteristics, including age, sex, prior medical history and current medication use, were collected by trained community healthcare staffs using standardized questionnaire. Weight and height were measured with participants standing without wearing heavy clothes or shoes by trained healthcare staffs. Body mass index (BMI) was calculated by weight in kilograms divided by height in squared meters. BMI ≥ 28 kg/m2.3Participants were required to sit in a quiet room for 5 min before blood pressure (BP) measurements. According to the Chinese hypertension guideline,2.4Echocardiographic examination was performed by two experienced sonographers from Guangdong Provincial People's Hospital, using a Vivid S6 M4S‐RS Probe (GE Ving‐Med) interfaced with a 2.5‐ to 3.5‐MHz phased‐array probe. Left ventricular (LV) parameters were measured using standard 2D echocardiography according to the American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) guideline recommendation. Interventricular septal end‐diastolic thickness (IVSTd), LV posterior wall end‐diastolic thickness (LVPWTd), and LV end‐diastolic diameter (LVEDD) were recorded from the parasternal long‐axis view at the level of the mitral valve leaflet tips. LVM was calculated as follow: LVM = 0.8* 1.04 *[(IVSTd + LVEDD + LVPWTd)2.5.1.7. Chinese thresholds were generated from recently published research.The echocardiographic values of LVM were indexed to BSA and height2.6The outcome was all‐cause mortality and cardiovascular mortality. Causes of cardiovascular mortality included ischemic heart disease, heart failure, stroke. Others were all‐cause mortality. Outcomes were obtained from the dataset linkage to Dongguan Medical Insurance Bureau and Liao Bu Community Health Center. This captures the death registry and all admission data when submitting medical expense. Patients were censored at the time of outcome or at the end of follow‐up .2.7To test the reproducibility of echocardiographic measurements, three key parameters, including IVSTd, LVEDD and LVPWTd, were remeasured in 200 randomly selected subjects from the study participants. Interobserver variability was assessed between two investigators (Z.D. and X.Q.). Intraobserver variability was assessed by Z.D. Bland‐Altman analysis was used to assess interobserver and intraobserver variability and interclass correlation coefficients were calculated Figure .2.8p‐value <.05 was considered as statistical significance.Continuous variables were presented as mean ± standard deviation if normal distribution, otherwise were presented as median and interquartile range (IQR). Categorical variables were presented as number (proportion). For categorical variables, the chi‐square test or Fisher exact test were used. When the continuous data were normal distribution, two groups were compared using the paired t‐test. Non‐parametric tests were used for analyzing data that were skew distribution. Univariable and multivariable Cox proportional hazards models were used to explore the association between LVH and outcome. Model 1 was unadjusted and model 2 was adjusted for age, sex, current smoking, waist circumference, BMI, SBP, heart rate, total cholesterol, eGFR, CKD, diabetes mellitus (T2DM), coronary artery disease (CAD), stroke, anti‐hypertension drugs with a forward stepwise procedure using the maximum likelihood ratio test. Hazard Ratio (HR) and 95% confidence interval (CI) were reported. Akaike Information Criterion (AIC) was provided to compare models. Kaplan−Meier curves were used to evaluate survival, and log‐rank tests were performed to analyze the differences. C‐statistics and time‐dependent receiver operating characteristic curves (time‐ROCs) were used to assess the predictive accuracy of each indicator. All the analyses were performed using IBM SPSS Statistics 25.0 software and R statistical software version 4.2.2. and a 33.12. The baseline characteristics comparison between participants with and without mortality were presented in Table Among the 2454 hypertensive patients  Table , 57.9% h.....The total proportion of LVH when using the Chinese thresholds compared to the international guideline thresholds was presented in Figure 3.2n = 174) and annual rate was 15.7 ‰, with cardiovascular mortality rate was 2.9% (n = 71) and annual rate was 6.4 ‰.During a median follow‐up of 49 months (IQR 2–54 months), the all‐cause mortality rate was 7.1% . LVH defined by LVM/Height1.7 using Chinese thresholds, not guideline threshold, had higher risk of mortality  . After adjusting for covariates in Table ..1.7 using Chinese threshold had the lowest AIC.Kaplan‐Meier curve showed that hypertensive patients with LVH, which using the LVM/BSA, LVM/Height3.52.7 and LVM/Height1.7 defined by Guideline thresholds. Among those indicators, LVH defined by LVM/BSA using Chinese threshold was better associated with all‐cause mortality (C‐statistics 0.578) and cardiovascular mortality (C‐statistics 0.587). LVH defined by LVM/Height1.7 using Chinese thresholds was also better associated with all‐cause mortality (C‐statistics 0.576) and cardiovascular mortality (C statistics 0.578). In Table 1.7 defined by Chinese thresholds had significantly increased the C‐statistics in the time of three‐year follow‐up. Although compared with the clinical model, adding LVH indicators slightly increased C‐statistics. For prediction of all‐cause mortality, LVM/Height1.7 by Chinese threshold had highest C‐statistics in all follow‐up time. For prediction of cardiovascular mortality, LVM/Heigh1.7 by Chinese threshold and LVM/BSA by Guideline had higher C‐statistics in all follow‐up time.The predictive value of those LVH indicators was showed in Table 3.6p < .001 for all). The intraclass correlation coefficients of intra‐observer reproducibility for IVSTd, LVEDD, LVPWTd were 0.96, 0.98, and 0.94, respectively . The Bland–Altman plots also demonstrated good agreement between interobserver reproducibility and intra‐observer reproducibility  and incident CVD has been demonstrated by Multi‐Ethnic Study of Atherosclerosis (MESA) involving 4 racial/ethnic groups . LVH has more prognostic utility predicting future CVD events for Chinese ...1.7 was more specific than LVM/BSA or LVM/Height2.7 to identify obesity‐related LVH and consistently associated with cardiovascular events and all‐cause mortality.1.7 using Chinese threshold was consistently associated with all‐cause mortality, however, failed to predict cardiovascular mortality. Previous study showed normalization for height.1.7 beyond clinical model also been revealed with using Chinese thresholds, not Guideline thresholds.Our results showed that the Chinese thresholds indexing BSA and heightThere are some limitations of our study. First, the Chinese threshold from EMINCA study was limited by the fact that it was obtained by age‐sex matching hypertensive patients. This threshold may not be generalizable to an otherwise general population. Second, we collected complete data on mortality but no other cardiovascular events. There were less cardiovascular mortality and less power to detect statistical significance. Although the number for cardiovascular mortality was small, LVM/BSA defined by Chinese thresholds have shown independent prognostic value for cardiovascular mortality, not guideline thresholds. Third, no probing biomarkers explain the potential underlying mechanisms involved in the relationship between LVH and mortality. Fourth, currently, our study did not have sufficient power to explore sex differences and further follow‐up was needed.In conclusion, in community hypertensive populations, current international guideline thresholds may lead to significant overestimate of LVH and the mortality risk attributable to LVH that is identified with the Chinese thresholds is different from the international guideline thresholds. The potential value of this paper is that race‐specific thresholds should be used to classify LV hypertrophy related to mortality risk stratification. The ability to properly account for ethnic body size difference will allow for more accurate quantification of LVM in Chinese threshold.Dan Zhou, Anping Cai contributed to the conception and design of the study. Dan Zhou, Mengqi Yan drafted the manuscript. Dan Zhou, Mengqi Yan revised the manuscript. Mengqi Yan, Qiu Xie, Qi Cheng, Songtao Tang contributed to the acquisition of data, interpretation of data, and analysis of data. Dan Zhou, Anping Cai, Yingqing Feng contributed to the interpretation of data and critical revision of the article for important intellectual content. All authors contributed to the article and approved the submitted version.The authors declare no conflicts of interest.Supp InformationClick here for additional data file.


Introduction: To compensate for the lack of pragmatic information available when communicating via text message, texters make frequent use of texting-specific cues, or textisms, to convey meaning that would otherwise be apparent in spoken conversation. Here, we explore how one such cue, face emoji, can impact the interpretation of text messages.Methods: In Experiment 1, we paired neutral text messages with valenced face emoji to determine whether the emoji can alter the meaning of the text. In Experiment 2, we paired valenced text messages with valenced face emoji to determine whether the emoji can modulate the valence of the text.Results: In Experiment 1, we found that texts paired with positive emoji were rated more positively than texts paired with negative emoji. Furthermore, texts paired with stronger-valenced emoji were rated as less neutral compared to texts paired with milder-valenced emoji. In Experiment 2, we found that slightly positive texts paired with strong positive emoji were rated somewhat similarly to the same texts paired with mild positive emoji; however, slightly negative texts paired with strong negative emoji were rated much more negatively than the same texts paired with mild negative emoji.Discussion: These results indicate that the presence of face emoji, particularly negative face emoji, can alter the interpretation of text messages, allowing texters to communicate nuanced meaning and subtle emotion. Modern life relies heavily on computer-mediated communication (CMC), such as email, social media chat, and text messaging. This reliance increased due to the COVID-19 pandemic, which forced much of the world to move work, school, and commerce largely online. CMC became a vital part of daily life as individuals attempted to combat social isolation while society tried to tackle a public health crisis. With this greater dependence on digital communication, the frequency of text messaging increased by 43% to become the prevalent, preferred, and even, primary form of communication when compared to other forms of digital communication, including email, voice calls, video calls, and social media .Contrary to early research, which suggested that CMC is impoverished compared to face-to-face communication , text metextisms and they help texters create and interpret written messages more effectively and efficiently. They are especially important when the literal interpretation of the written message is not intended or is ambiguous–for example, when trying to convey humor  to 5 (Very Positive) to determine how the text messages were interpreted on their own, without the inclusion of the face emoji. Participants also rated the face emoji on two dimensions; they were asked to name the emotion conveyed by each emoji and to identify whether that emotion was mild or strong in intensity.In Experiment 1, we used these normed materials to explore how face emoji impact the interpretation of texts. Sentences rated as neutral were paired with each of our four face emoji categories . Participants were asked to read the text/face emoji pairs as though they had received them from someone they knew well and then to rate the tone of the text/face emoji pairs on a scale of 1 (Very Negative) to 5 (Very Positive). We expected (1) that texts paired with positive emoji would be rated more positively than texts paired with negative emoji and (2) that texts paired with mild emoji would be rated closer to neutral than texts paired with strong emoji.In Experiment 2, we investigated whether (1) non-neutral texts can be influenced by face emoji valence and (2) negative face emoji convey more nuanced, gradated information than positive face emoji. We paired slightly positive texts with mild positive face emoji or strong positive face emoji and slightly negative texts with mild negative face emoji or strong negative face emoji. Again, participants rated the tone of the text/face emoji pairs on a scale of 1 (Very Negative) to 5 (Very Positive). We expected (1) that texts paired with positive face emoji would be rated similarly, regardless of whether the face emoji were mild or strong but (2) that texts paired with negative face emoji would be rated more negatively when the face emoji were strong compared to when the face emoji were mild.In preparation for Experiment 1, we began with a norming procedure. The first portion of the norming procedure was meant to help us select texts that were neutral in tone. Participants rated the tone of individual texts that were written to be neutral on a scale of 1 (Very Negative) to 5 (Very Positive) to allow us to determine how each text would be interpreted without the inclusion of a face emoji. The second portion of the norming procedure was meant to help us select face emoji that were consistently used to express either positive emotion or negative emotion. Participants rated individual face emoji on two dimensions; they were asked to (1) name the emotion conveyed by each face emoji and (2) identify whether the intensity of that emotion was mild or strong.The neutral texts, mild positive face emoji, strong positive face emoji, mild negative face emoji, and strong negative face emoji identified in the norming procedure were used to create the experimental stimuli in Experiment 1 See .M = 18.82, SD = 1.10). Of the participants who answered the gender question, 58 (63.04%) identified as female and 34 identified as male. Of the participants who answered the item, “Would you consider yourself proficient in texting?” 78 (84.78%) said “Yes” and 14 said “No.”One hundred ten James Madison University undergraduates voluntarily participated in this procedure in exchange for course credit. Following their participation, we asked them to complete a brief demographic questionnaire. We received 92 responses. Of the participants who answered the age question, 41 were 18 years old, 36 were 19 years old, 11 were 20 years old, three were 21 years old, and one was 26 years old  to 5 (Very Positive).Thirty face emoji, styled to match those used on Apple devices, were selected for this task . Due to copyright restrictions, text descriptions of the emoji are included throughout this manuscript, and not the images . ParticiQuestionPro online survey software  was usedOne face emoji was eliminated due to a loading error. One participant was eliminated for failing to follow instructions. Any participant who did not rate 10% or more of the items in a section (text message or face emoji) was eliminated entirely from that section. For the text message section, 14 of 108 participants were removed, leaving 94 participants; for the face emoji section, 21 of the 108 participants were removed, leaving 87 participants.We calculated the average rating for each text. A text was discarded if the majority of its ratings was not “3 ” or if the average of its ratings was too far from “3 ,” which we defined as outside the range of 2.6–3.4. Twenty-five texts were retained, of which 24 were selected for use in Experiment 1.We also calculated the average rating for each face emoji. The two face emoji that had the highest averages between 3 and 5 and were generally named with a positive word became our strong positive face emoji for Experiment 1. The two face emoji that had the lowest averages between 3 and 5 and were generally named with a positive word became our mild positive face emoji. The two face emoji that had the lowest averages between 1 and 3 and were generally named with a negative word became our strong negative face emoji. Finally, the two face emoji that had the highest averages between 1 and 3 and were generally named with a negative word became our mild negative face emoji.SD = 1.19) and the mean arousal was 6.68 (SD = 2.28). For the strong positive face emoji (Beaming Face with Smiling Eyes), the mean valence was 7.73 (SD = 1.14) and the mean arousal was 5.48 (SD = 2.36). For the mild positive face emoji (Face Savoring Food), the mean valence was 7.59 (SD = 1.15) and the mean arousal was 4.53 (SD = 2.52). For the mild positive face emoji (Grinning Face with Big Eyes), the mean valence was 7.77 (SD = 1.19) and the mean arousal was 4.52 (SD = 2.53). For the strong negative face emoji (Face with Symbols on Mouth), the mean valence was 2.82 (SD = 1.86) and the mean arousal was 6.71 (SD = 1.92). For the strong negative face emoji (Angry Face), the mean valence was 3.32 (SD = 1.85) and the mean arousal was 6.07 (SD = 2.04). For the mild negative face emoji (Confused Face), the mean valence was 2.63 (SD = 1.35) and the mean arousal was (SD 5.07 = 1.89). For the mild negative face emoji (Slightly Frowning Face), the mean valence was 2.60 (SD = 1.25) and the mean arousal was (SD 5.90 = 2.08).In addition to the valence, the arousal inherent in each emoji is an important consideration as well. Valence values, taken from In Experiment 1, we used materials from Norming Procedure 1 to explore how texters use face emoji valence to inform text comprehension. Sentences rated as neutral were paired with one of each category of face emoji . Participants were asked to read the text/face emoji pairs as though they had received them from someone they knew well and to rate the tone of the text/face emoji pairs on a scale of 1 (Very Negative) to 5 (Very Positive), similar to what was done in the norming procedure.We expected that texts paired with positive face emoji would be rated more positively than texts paired with negative face emoji. In other words, ratings for texts paired with positive face emoji would cluster around 4 and 5 on the scale, whereas ratings for texts paired with negative face emoji would cluster around 1 and 2. We also expected that texts paired with strong face emoji would be rated more strongly than texts paired with mild face emoji. In other words, ratings for texts paired with strong face emoji would cluster around 1 and 5, whereas ratings for texts paired with mild face emoji would cluster around 2 and 4.One hundred James Madison University undergraduates voluntarily participated in this experiment in exchange for course credit. Due to experimenter error, the demographic questionnaire was unintentionally excluded.We selected 24 texts and two strong positive face emoji , two strong negative face emoji , two mild positive face emoji , and two mild negative face emoji , from Norming Procedure 1 to create our text/face emoji pairs See . For eacIn addition, we created 16 filler text/face emoji pairs, eight of which were positively valenced texts paired with our strong positive and mild positive face emoji  and eight of which were negatively valenced texts paired with our strong negative and mild negative face emoji . The text/face emoji pairs were designed with an online text message generator  to look Had we presented all stimuli to all participants, each participant would have seen each text four times, paired with a different face emoji each time. This could have alerted them to the manipulation, skewing our results. To minimize this likelihood, we decided to present a subset of the stimuli to each participant. Unfortunately, our software did not allow for this option. Thus, we created four stimuli sets to ensure that: (1) each experimental pair was seen by one-fourth of participants, (2) each participant saw one-fourth of experimental pairs, (3) each participant saw each text selected from Norming Procedure 1 only one time, and (4) each participant saw each face emoji selected from Norming Procedure 1 three times. Each stimuli set included 24 of the experimental pairs, all eight positive fillers, and all eight negative fillers. Participants were randomly assigned to a stimuli set, and within a stimuli set, text/face emoji pairs were randomly presented.After reviewing the experiment instructions and submitting their informed consent, participants were asked to read the text/face emoji pairs as though they had received them from someone they knew well and to rate the tone of the text/face emoji pairs on a scale of 1 (Very Negative) to 5 (Very Positive). Unlike Norming Procedure 1, where the texts were rated separately from the emoji, here, the texts and the emoji were paired together and thus, rated together. As with Norming Procedure 1, Experiment 1 utilized QuestionPro online survey software .t₁) and items as a random-effect variable (t₂). No data were discarded for this experiment.An alpha level of 0.05 was used for all analyses. All analyses were conducted with participants as a random-effect variable  were rated higher than texts paired with a negative face emoji : t₁(99) = 26.77, SEM₁ = 0.06, p₁ < 0.001, Cohen’s 1d = 2.68; t₂(23) = 23.64, SEM₂ = 0.07, p₂ < 0.001, Cohen’s 2d = 4.83. Thus, when participants saw a neutral text followed by a positive face emoji, they were more likely to rate the message as positive than when they saw that same neutral text followed by a negative face emoji.As anticipated, texts paired with a positive face emoji  were rated higher than texts paired with strong positive face emoji : t₁(99) = 3.87, SEM₁ = 0.04, p₁ < 0.001, Cohen’s d₁ = 0.39; 2t(23) = 2.16, SEM₂ = 0.08, p₂ < 0.05, Cohen’s 2d = 0.44. Counterintuitively, this indicates that texts paired with strong positive face emoji were rated more negatively than texts paired with mild positive face emoji. Although the underlying cause for this is not clear, we suspect that there are instances when too much positivity might be interpreted as sarcasm, and therefore, judged to be negative rather than positive. Texts paired with mild negative face emoji  were rated higher than texts paired with strong negative face emoji : t₁(99) = 10.71, SEM₁ = 0.04, p₁ < 0.001, Cohen’s d₁ = 1.07; 2t(23) = 7.93, 2SEM = 0.06, 2p < 0.001, Cohen’s 2d = 1.62. This indicates that texts paired with strong negative face emoji were rated more negatively than texts paired with mild negative face emoji.Additionally, texts paired with mild positive face emoji  were rated more positively than those paired with strong positive face emoji , which were rated more positively than those paired with no emoji , which were rated more positively than those paired with mild negative face emoji , which, in turn, were rated more positively than those paired with strong negative face emoji . Thus, when paired with positive face emoji, neutral texts from the norming saw a statistically significant increase in their ratings  and when paired with negative face emoji, those same neutral texts saw a statistically significant decrease in their ratings .To better understand how the valence of the face emoji impacted the interpretation of the text messages, we compared the text message ratings from Norming Procedure 1 to those from Experiment 1. Recall that in the norming procedure, the text messages were presented in isolation—that is, they were not paired with the face emoji. For Norming Procedure 1/Experiment 1, the texts paired with no emoji were rated significantly different from the texts paired with emoji see . Texts pBefore we conducted our next series of analyses, we converted participants’ Experiment 1 responses from a 1–5 scale to a 0–2 scale. This allowed us to determine whether texts paired with strong face emoji were rated as less neutral than texts paired with mild face emoji, independent of valence. Ratings of “3″ were converted to “0,” ratings of “2” and “4” were converted to “1,” and ratings of “1” and “5” were converted to “2.” In other words, neutral ratings (3) were set to “0,” less extreme ratings were set to “1,” and more extreme ratings were set to “2.”M₁ = 0.99, SD₁ = 0.33) were rated as less neutral than texts paired with a mild face emoji : t₁(99) = 6.15, 1SEM = 0.03, p₁ < 0.001, Cohen’s d₁ = 0.62; t₂(23) = 3.79, 2SEM = 0.04, p₂ < 0.001, Cohen’s 2d = 0.77. Thus, when participants saw a neutral text followed by a strong face emoji, they were more likely to rate the message as having a stronger valence (whether positive or negative) than when they saw that same neutral text followed by a mild face emoji.As predicted, texts paired with a strong face emoji  were rated higher than texts paired with mild negative face emoji : t₁(99) = 3.63, SEM₁ = 0.05, p₁ < 0.001, Cohen’s d₁ = 0.36; 2t(23) = 3.26, 2SEM = 0.06, p₂ < 0.01, Cohen’s 2d = 0.67. This indicates that texts paired with mild positive face emoji were rated as less neutral than texts paired with mild negative face emoji. Texts paired with strong negative face emoji  were rated higher than texts paired with strong positive face emoji : t₁(99) = 6.26, SEM₁ = 0.05, p₁ < 0.001, Cohen’s d₁ = 0.63; 2t(23) = 3.71, 2SEM = 0.08, 2p < 0.01, Cohen’s 2d = 0.76. This indicates that texts paired with strong negative face emoji were rated as less neutral than texts paired with strong positive face emoji. Thus, texts paired with positive face emoji (whether mild or strong) tended to cluster closer together than texts paired with negative face emoji.Furthermore, texts paired with mild positive face emoji  to 5 (Very Positive). The texts selected from this norming procedure were paired with the face emoji selected from the previous norming procedure to create the stimuli used in Experiment 2.M = 18.91, SD = 0.87). Of the participants who answered the gender question, 68 (69.39%) identified as female, 29 identified as male, and one identified as non-binary. Of the participants who answered the item, “Would you consider yourself proficient in texting?” 87 (88.78%) said “Yes” and 11 said “No.”One hundred James Madison University undergraduates voluntarily participated in this procedure in exchange for course credit. Following their participation, we asked them to complete a brief demographic questionnaire. We received 98 responses. Of the participants who answered the age question, 35 were 18 years old, 44 were 19 years old, 13 were 20 years old, 5 were 21 years old, and one was 22 years old  to 5 (Very Positive).QuestionPro online survey software  was usedThe results of this norming procedure were used to determine which texts to include as stimuli in Experiment 2. Two participants were eliminated for failing to follow instructions, leaving 98 participants. Each text had at least 97 responses; therefore, none were excluded due to lack of data. We did, however, exclude texts where the response pattern was highly variable. For the slightly negative texts, only those with an average rating between 2.1 and 2.6 in which 70% of responses fell within the “2-Slightly Negative” and “3-Neutral” range were maintained. Likewise, for the slightly positive texts, only those with an average rating between 3.4 and 3.9 in which 70% of responses fell within the “3-Neutral” and “4-Slightly Positive” range were maintained . All other texts were discarded. In total, 45 negative texts and 14 positive texts fit these criteria.Experiment 1 demonstrated that the tone of neutral text messages is malleable and can be influenced by the emotional valence of face emoji. This is consistent with prior work by In Experiment 2, we explored a similar but expanded question: If the recipient’s interpretation of a text’s valence is strengthened by the presence of a congruent emoji, can that be modulated by the intensity of the emoji? In other words, if a negative text is paired with a strong negative face emoji, will it be interpreted more negatively than a negative text paired with a mild negative face emoji? We investigated this question using the face emoji selected in Norming Procedure 1 and the valenced texts selected in Norming Procedure 2. For the slightly negative texts, we expected that those paired with strong negative face emoji would be rated more negatively than the same texts paired with mild negative face emoji. For the slightly positive texts, we expected that those paired with strong positive face emoji would be rated similarly to the same texts paired with mild positive face emoji–that is, we expected a diminished effect or no effect at all. It is possible that the difference between a mildly positive text/face emoji pair and strongly positive text/face emoji pair may not be pragmatically different for texters. Both responses are “good-enough” e.g., , and theM = 18.63, SD = 0.87). Of the participants who answered the gender question, 85 (85%) identified as female and 15 identified as male. Of the participants who answered the item, “Would you consider yourself proficient in texting?” 87 (87%) said “Yes” and 13 said “No.”One hundred fourteen James Madison University undergraduates voluntarily participated in this experiment in exchange for course credit. Following their participation, we asked them to complete a brief demographic questionnaire. We received 100 responses. Of the participants who answered the age question, 59 were 18 years old, 23 were 19 years old, 14 were 20 years old, and four were 21 years old  each experimental pair was seen by one-half of participants, (2) each participant saw one-half of experimental pairs, (3) each participant saw each text message selected from Norming Procedure 2 only once, and (4) each participant saw each face emoji used in Experiment 1 three to four times . Participants were randomly assigned to a stimuli set, and within a stimuli set, text/face emoji pairs were randomly presented.After reviewing the experiment instructions and submitting their informed consent, participants were asked to read the text/face emoji pairs as though they had received them from someone they knew well and to rate the tone of the text/face emoji pairs on a scale of 1 (Very Negative) to 5 (Very Positive). As with the previous norming procedures and experiment, Experiment 2 used QuestionPro online survey software .For the slightly negative texts, we expected that those paired with a strong negative face emoji would be rated more negatively than those paired with a mild negative face emoji. For the slightly positive texts, we expected a similar but diminished effect–or no effect of emoji strength at all.t₁) and items as a random-effect variable (t₂). No data were discarded for this experiment.An alpha level of 0.05 was used for all analyses. All analyses were conducted with participants as a random-effect variable  were rated higher  than the slightly negative texts paired with negative face emoji : t₁(113) = 36.69, SEM₁ = 0.06, p₁ < 0.001, Cohen’s 1d = 3.44; t₂(26) = 27.30, 2SEM = 0.07, 2p < 0.001, Cohen’s 2d = 10.32.Unsurprisingly, the slightly positive texts paired with a positive face emoji  were rated higher  than the same texts paired with strong positive face emoji , this difference was significant by participants only, and not by items: t₁(113) = 3.90, SEM₁ = 0.04, p₁ < 0.001, Cohen’s 1d = 0.37; t₂(13) = 1.71, 2SEM = 0.10, 2p = 0.11, Cohen’s 2d = 0.46. This is consistent with the explanation we put forth in Experiment 1—that texts that are seen as too positive might be interpreted as sarcastic and therefore, negative. When compared to the slightly positive texts from Norming Procedure 2 , those paired with mild positive face emoji were rated more positively by subjects and by items ; those paired with strong positive face emoji were rated more positively by subjects only , which were rated more negatively than slightly negative texts paired with no emoji [1M = 2.37, 1SD = 0.40; Strong Negative vs. No Emoji: 1t(210) = 12.15, 1SEM = 0.06, 1p < 0.001, Cohen’s 1d = 1.66; 2t(13) = 14.22, 2SEM = 0.05, 2p < 0.001, Cohen’s 2d = 4.90; Mild Negative vs. No Emoji: 1t(210) = 6.29, 1SEM = 0.05, 1p < 0.001, Cohen’s 1d = 0.87; 2t(13) = 11.38, 2SEM = 0.03, 2p < 0.001, Cohen’s 2d = 4.18; see For the slightly negative texts, we see a more gradated effect. Slightly negative texts paired with strong negative face emoji  than the slightly positive texts . Thus, we have additional support suggesting that negative face emoji are more impactful and nuanced than positive face emoji when the texts they are paired with already carry valence information of their own.Finally, the magnitude of the strong vs. mild effect was considerably more pronounced for the slightly negative texts  as well as slightly valenced text messages (Experiment 2). For both experiments, we found that our effects were more pronounced for negative face emoji than for positive face emoji. Interestingly, texts paired with mild positive face emoji were rated more positively than those same texts paired with a strong positive face emoji. Negative face emoji, on the other hand, functioned more as predicted. Texts paired with strong negative face emoji were rated more negatively than those same texts paired with mild negative face emoji. As discussed, the valence values  were somIt is important to note that the difference in effect size between the strong and mild positive text/face emoji pairs was much smaller than the difference in effect size between the strong and mild negative text/face emoji pairs, indicating that although face emoji appear to carry some gradated emotional information, whether positively or negatively valenced, this was more evident for the negative face emoji. Overall, these results indicate that positive face emoji and negative face emoji are not merely two sides to the same coin, but rather, that they function differently from one another. The gradated emotional information carried by positive face emoji seems stunted compared to negative face emoji–the latter appearing communicatively richer in conveying intensity and, perhaps, meaning. This is supported by findings from Our current findings, too, support the notion that positively valenced emoji can be somewhat difficult to interpret when paired with text messages. In isolation, the strong positive emoji were rated more positively than the mild positive emoji. However, when these emoji were paired with text messages , the mild pairings were rated more positively than the strong pairings. Earlier, we suggested that perhaps the strong pairings were interpreted sarcastically. We are not the first to make this observation. Some emoji, although judged as positive in isolation, show evidence of being used sarcastically, and thus, are judged as negative when paired with a text message. One common example of this involves framing a piece of bad news within the sparkles emoji or the heart emoji . Perhapstextoids as they would real texting conversations. Granted, our experiments presented texts involving a sender who was unknown to the participant, without providing much context for the conversation or the relationship. But the texts were presented as text bubbles on a smartphone to create a more realistic experience. This is an important distinction from earlier work where it is less clear whether participants treated the material in the experiment as text messages or other types of text/narratives  at James Madison University. The patients/participants provided their written informed consent to participate in this study.Portions of these data were reported at the 31st Annual Meeting of the Society for Text and Discourse and the 93rd Annual Meeting of the Eastern Psychological Association.SU: conceptualization of research, creating stimuli, creating surveys for data collection, data coding, and writing, formatting, and submission of manuscript. DG: conceptualization of research, creating stimuli, data coding, cleaning, and analysis, and writing of manuscript. NP: creating stimuli, creating surveys for data collection, data coding, and writing of manuscript. 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.https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1183299/full#supplementary-materialThe Supplementary material for this article can be found online at: Click here for additional data file.


The authors report a case of abdominal compartment syndrome caused by massive pyonephrosis in an infant with primary obstructive megaureter successfully treated with emergency surgical decompression. Abdominal compartment syndrome (ACS) is associated with high mortality if unrecognized and untreated –3. It ma3, and white blood cell (WBC) count of 10600/mm3 ; the neutrophils showed toxic granulation and vacuolation. C-reactive protein was 28.3 mg/dL, and arterial blood gas analysis (while the patient was breathing room air) revealed a pH of 7.38, PCO2 of 28 mm Hg, PO2 of 67 mm Hg, and bicarbonate of 16 mEq/L. Arterial lactate was 1.4 mmol/L, serum urea concentration was 25 mg/dL, and serum creatinine concentration was 0.3 mg/dL. Urine was cloudy, and her urine output was 0.3 mL/kg/h. Urinalysis showed 15–20 WBC per high-power field and 6–8 red blood cells per high-power field, with 1+ protein, a pH of 5, and a negative nitrite test. Chest radiography showed elevated hemidiaphragms, with reduced lung expansion. Abdominal plain radiography showed prominent gaseous distension of bowel loops which were completely deviated to the right side of the abdomen and homogeneous opacity of the left hemiabdomen  admission, the patient appeared obtunded and febrile, with moderate respiratory distress. Her vital signs were as follows: temperature 38°C, respiratory rate 72 breaths/min, heart rate 180 beats/min, and blood pressure 119/72 mm Hg. Respirations were rapid and shallow. Nasal flaring and moderate subcostal retractions were noted. Her central and peripheral pulses were strong, with capillary refill time < 2 sec in upper extremities and 4 sec in lower extremities. Both lower limbs had a mottled cyanotic appearance. Abdominal examination revealed marked distension with diminished bowel sounds and moderate discomfort with deep palpation of the left upper quadrant and left flank. Signs of peritoneal irritation were absent. A 10 × 5 cm firm abdominal mass was palpable from the left costal margin to the left iliac fossa. Intra-abdominal pressure measured by the intravesical route was 14 mm Hg. Laboratory investigations revealed a hemoglobin of 7.4 g/dL, platelets of 695000/mmiabdomen . Abdomeniabdomen . The rigiabdomen . AntibioBecause signs and symptoms of ACS are often subtle, its diagnosis depends on a high index of suspicion in patients who acutely develop tense abdominal distension. In our patient, ACS manifested as oliguria, respiratory insufficiency with hypoxia, and venous congestion of the lower limbs and ileus. Nevertheless, given the low sensitivity of the physical examination alone 40–60%) for the detection of increased IAP 0% for th, it is aObstructed renal collecting systems are at risk for superimposed infections. Our patient had an obstructive urinary tract malformation which complicated with pyonephrosis. Of note, she was not receiving prophylactic antibiotics because of poor parental compliance with treatment. In a cohort of 49 children with primary obstructive megaureter, urinary tract infection was the most common complication, and its incidence in children less than 1 year of age was 55% lower during antibiotic prophylaxis . Delayed diagnosis and treatment of pyonephrosis have been associated with irreversible damage to the kidneys and the development of septic shock . HoweverOne alternative treatment to open pyelostomy is percutaneous nephrostomy. Nevertheless, because the patient parents had been poorly compliant with treatment before, the surgical team opted for an open pyelostomy as it does not require the maintenance of an indwelling catheter. In conclusion, massive pyonephrosis complicating urinary tract obstruction can cause ACS which may be successfully treated by timely surgical drainage and abdominal decompression. This case illustrates the importance of awareness, early diagnosis, and management of ACS to avoid the progression to multiple organ failure, thus resulting in improved outcome.