Evaluating Sex-specific Differences in Abdominal Fat Volume and Proton Density Fat Fraction at MRI Using Automated nnU-Net-based Segmentation.

Sex-specific abdominal organ volume and proton density fat fraction (PDFF) in people with obesity during a weight loss intervention was assessed with automated multiorgan segmentation of quantitative water-fat MRI. An nnU-Net architecture was employed for automatic segmentation of abdominal organs, including visceral and subcutaneous adipose tissue, liver, and psoas and erector spinae muscle, based on quantitative chemical shift-encoded MRI and using ground truth labels generated from participants of the Lifestyle Intervention (LION) study. Each organ's volume and fat content were examined in 127 participants (73 female and 54 male participants; body mass index, 30-39.9 kg/m2) and in 81 (54 female and 32 male participants) of these participants after an 8-week formula-based low-calorie diet. Dice scores ranging from 0.91 to 0.97 were achieved for the automatic segmentation. PDFF was found to be lower in visceral adipose tissue compared with subcutaneous adipose tissue in both male and female participants. Before intervention, female participants exhibited higher PDFF in subcutaneous adipose tissue (90.6% vs 89.7%; P < .001) and lower PDFF in liver (8.6% vs 13.3%; P < .001) and visceral adipose tissue (76.4% vs 81.3%; P < .001) compared with male participants. This relation persisted after intervention. As a response to caloric restriction, male participants lost significantly more visceral adipose tissue volume (1.76 L vs 0.91 L; P < .001) and showed a higher decrease in subcutaneous adipose tissue PDFF (2.7% vs 1.5%; P < .001) than female participants. Automated body composition analysis on quantitative water-fat MRI data provides new insights for understanding sex-specific metabolic response to caloric restriction and weight loss in people with obesity. Keywords: Obesity, Chemical Shift-encoded MRI, Abdominal Fat Volume, Proton Density Fat Fraction, nnU-Net ClinicalTrials.gov registration no. NCT04023942 Supplemental material is available for this article. Published under a CC BY 4.0 license.

Impaired Sensitivity to Thyroid Hormones Is Associated With the Change of Abdominal Fat in Euthyroid Type 2 Diabetes Patients: A Retrospective Cohort Study.

Background and Aims: This study is aimed at investigating the potential correlation of thyroid hormone sensitivity with visceral fat area (VFA), subcutaneous fat area (SFA), and body mass index (BMI) among euthyroid type 2 diabetes mellitus (T2DM) subjects. Methods: Thyroid hormone sensitivity indices were calculated by thyroid feedback quantile-based index (TFQI), TSH index (TSHI), thyrotropin thyroxine resistance index (TT4RI), and free thyroxine (fT4)/free triiodothyronine (fT3) ratio. These indices were then categorized into quartiles for analysis. The outcomes were the change rates in VFA, SFA, and BMI among the participants. Result: The present study included 921 patients, with a median follow-up of 2.2 years. In multivariate linear regression, when compared to the first quartile, SFA demonstrated a notable decline in the fourth quartile of TFQI, TSHI, and TT4RI (ß coefficient = -5.78, -7.83, and - 6.84 cm2 per year), while it significantly increased in the fourth quartile of fT4/fT3 ratio (ß coefficient = 6.13 cm2 per year). Similarly, in the fourth quartile of TFQI, TSHI, and TT4RI, VFA decreased significantly, evidenced by ß coefficients of -5.14, -4.80, and -4.08 cm2 per year. Yet, among the quartiles of the fT4/fT3 ratio, no discernible trend in VFA was observed. There was no significant association between indices of thyroid hormone sensitivity and change in BMI. Conclusion: Impaired central sensitivity to thyroid hormones was significantly associated with the reduction of VFA and SFA, while impaired peripheral sensitivity was associated with an increase of SFA in euthyroid individuals with T2DM.

Comprehensive analysis of changes in expression of lncRNA, microRNA and mRNA in liver tissues of chickens with high or low abdominal fat deposition.

1. The liver of chickens is a dominant lipid biosynthetic tissue and plays a vital role in fat deposition, particularly in the abdomen. To determine the molecular mechanisms involved in its lipid metabolism, the livers of chickens with high (H) or low (L) abdominal fat content were sampled and sequencing on long non-coding RNA (lncRNA), messenger RNA (mRNA) and small RNA (microRNA) was performed.2. In total, 351 expressed protein-coding genes for long non-coding RNA (DEL; 201 upregulated and 150 downregulated), 400 differentially expressed genes (DEG; 223 upregulated and 177 downregulated) and 10 differentially expressed miRNA (DEM; four upregulated and six downregulated) were identified between the two groups. Multiple potential signalling pathways related to lipogenesis and lipid metabolism were identified via pathway enrichment analysis. In addition, 173 lncRNA - miRNA - mRNA interaction regulatory networks were identified, including 30 lncRNA, 27 mRNA and seven miRNA.3. These networks may help regulate lipid metabolism and fat deposition. Five promising candidate genes and two lncRNA may play important roles in the regulation of adipogenesis and lipid metabolism in chickens.

AATCT-IDS: A benchmark Abdominal Adipose Tissue CT Image Dataset for image denoising, semantic segmentation, and radiomics evaluation.

BACKGROUND AND OBJECTIVE: The metabolic syndrome induced by obesity is closely associated with cardiovascular disease, and the prevalence is increasing globally, year by year. Obesity is a risk marker for detecting this disease. However, current research on computer-aided detection of adipose distribution is hampered by the lack of open-source large abdominal adipose datasets. METHODS: In this study, a benchmark Abdominal Adipose Tissue CT Image Dataset (AATCT-IDS) containing 300 subjects is prepared and published. AATCT-IDS publics 13,732 raw CT slices, and the researchers individually annotate the subcutaneous and visceral adipose tissue regions of 3213 of those slices that have the same slice distance to validate denoising methods, train semantic segmentation models, and study radiomics. For different tasks, this paper compares and analyzes the performance of various methods on AATCT-IDS by combining the visualization results and evaluation data. Thus, verify the research potential of this data set in the above three types of tasks. RESULTS: In the comparative study of image denoising, algorithms using a smoothing strategy suppress mixed noise at the expense of image details and obtain better evaluation data. Methods such as BM3D preserve the original image structure better, although the evaluation data are slightly lower. The results show significant differences among them. In the comparative study of semantic segmentation of abdominal adipose tissue, the segmentation results of adipose tissue by each model show different structural characteristics. Among them, BiSeNet obtains segmentation results only slightly inferior to U-Net with the shortest training time and effectively separates small and isolated adipose tissue. In addition, the radiomics study based on AATCT-IDS reveals three adipose distributions in the subject population. CONCLUSION: AATCT-IDS contains the ground truth of adipose tissue regions in abdominal CT slices. This open-source dataset can attract researchers to explore the multi-dimensional characteristics of abdominal adipose tissue and thus help physicians and patients in clinical practice. AATCT-IDS is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/AATTCT-IDS/23807256.

Associations of appendicular lean mass and abdominal adiposity with insulin resistance in older adults: A cross-sectional study.

Loss of lean muscle mass and accumulation of adipose tissue are changes associated with aging. Previous studies have documented various components of body composition as predictors for insulin resistance. The objective of this study was to investigate whether components of body composition-appendicular lean mass (ALM) and/or abdominal fat mass (AFM)-correlate with insulin resistance in older men and women. This was a cross-sectional study of 92 older men and women. Weight was classified according to body mass index (BMI)-normal (BMI <25), overweight (BMI 25-30), and obese (BMI >30). All body composition data was determined by dual energy x-ray absorptiometry (DEXA), and insulin resistance was assessed by the homeostatic model assessment of insulin resistance (HOMA-IR). Multivariable regression models with two-way interaction terms were employed to assess whether the associations between components of body composition and log HOMA varied by BMI categories. Adjusted regression showed that log HOMA was significantly associated with AFM (estimate ± standard error: 0.055 ± 0.026) and ALM (0.057 ± 0.029) for the overweight participants (p-values <0.05). Additionally, the adjusted associations between log HOMA and ALM were significantly greater for participants who were either obese or overweight compared to those with a normal BMI (p<0.002). Less consistent relationships were observed between insulin resistance and abdominal fat mass across BMI categories, whereas more consistent associations were observed between insulin resistance and appendicular lean mass in individuals with greater BMI. Further research is needed to clarify if lipid deposition within muscle tissue promotes muscle dysfunction and thereby increases risk for insulin resistance.

Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment.

This study investigates the application of cavitation in non-invasive abdominal fat reduction and body contouring, a topic of considerable interest in the medical and aesthetic fields. We explore the potential of cavitation to alter abdominal fat composition and delve into the optimization of fat prediction models using advanced hyperparameter optimization techniques, Hyperopt and Optuna. Our objective is to enhance the predictive accuracy of abdominal fat dynamics post-cavitation treatment. Employing a robust dataset with abdominal fat measurements and cavitation treatment parameters, we evaluate the efficacy of our approach through regression analysis. The performance of Hyperopt and Optuna regression models is assessed using metrics such as mean squared error, mean absolute error, and R-squared score. Our results reveal that both models exhibit strong predictive capabilities, with R-squared scores reaching 94.12% and 94.11% for post-treatment visceral fat, and 71.15% and 70.48% for post-treatment subcutaneous fat predictions, respectively. Additionally, we investigate feature selection techniques to pinpoint critical predictors within the fat prediction models. Techniques including F-value selection, mutual information, recursive feature elimination with logistic regression and random forests, variance thresholding, and feature importance evaluation are utilized. The analysis identifies key features such as BMI, waist circumference, and pretreatment fat levels as significant predictors of post-treatment fat outcomes. Our findings underscore the effectiveness of hyperparameter optimization in refining fat prediction models and offer valuable insights for the advancement of non-invasive fat reduction methods. This research holds important implications for both the scientific community and clinical practitioners, paving the way for improved treatment strategies in the realm of body contouring.

Optimizing CT Abdomen-Pelvis Scan Radiation Dose: Examining the Role of Body Metrics (Waist Circumference, Hip Circumference, Abdominal Fat, and Body Mass Index) in Dose Efficiency.

Objective: This study investigates the correlation between patient body metrics and radiation dose in abdominopelvic CT scans, aiming to identify significant predictors of radiation exposure. Methods: Employing a cross-sectional analysis of patient data, including BMI, abdominal fat, waist, abdomen, and hip circumference, we analyzed their relationship with the following dose metrics: the CTDIvol, DLP, and SSDE. Results: Results from the analysis of various body measurements revealed that BMI, abdominal fat, and waist circumference are strongly correlated with increased radiation doses. Notably, the SSDE, as a more patient-centric dose metric, showed significant positive correlations, especially with waist circumference, suggesting its potential as a key predictor for optimizing radiation doses. Conclusions: The findings suggest that incorporating patient-specific body metrics into CT dosimetry could enhance personalized care and radiation safety. Conclusively, this study highlights the necessity for tailored imaging protocols based on individual body metrics to optimize radiation exposure, encouraging further research into predictive models and the integration of these metrics into clinical practice for improved patient management.

Assessment of transabdominal fat volumes as a predictor of prognosis in patients undergoing transcatheter aortic valve replacement.

Transcatheter aortic valve replacement (TAVR) has emerged as a well-established treatment option for eligible patients with severe aortic stenosis. This study aimed to investigate the correlation between abdominal fat tissue volumes, measured using computed tomography (CT), and all-cause mortality in patients undergoing TAVR. The study included 258 consecutive patients who underwent TAVR at a single center between September 2017 and November 2020. During the preoperative preparation, CT scans were used to perform a semi-quantitative measurement of abdominal fat components. Body mass index (BMI) for each participant was calculated. The relationship between fat parameters and overall survival was determined using multivariable Cox proportional hazards models. Participants had a mean age of 76.8 ± 7.8 years, of whom 32.9% were male. The median follow-up period was 12 months, during which 38 patients (14.7%) died. Both the survivor and non-survivor groups showed comparable risk factors. Regarding transabdominal fat volume parameters, deceased individuals exhibited significantly lower values. However, no significant differences were observed in BMI and transabdominal area measurements. Among transabdominal fat parameters, only subcutaneous fat volume [adjusted Hazard Ratio (aHR) = 0.83, p = 0.045] and total fat volume (TFV) [aHR = 0.82, p = 0.007] were identified as significant predictors of reduced all-cause mortality. Furthermore, TFV demonstrated the highest discriminative performance with a threshold of ≤ 9.1 L (AUC = 0.751, p < 0.001, sensitivity 71.1%, specificity 70.9%). Preoperative CT-based abdominal fat volume parameters, particularly TFV, can serve as potential predictors of survival in patients undergoing TAVR.

Grb7 Ablation in Mice Improved Glycemic Control, Enhanced Insulin Signaling, and Increased Abdominal fat Mass in Females.

OBJECTIVES: Growth factor receptor bound protein 7 (GRB7) is a multidomain signaling adaptor. Members of the Grb7/10/14 family, specifically Gbrb10/14, have important roles in metabolism. We ablated the Grb7 gene in mice to examine its metabolic function. METHODS: Global ablation of Grb7 in FVB/NJ mice was generated. Growth, organ weight, food intake, and glucose homeostasis were measured. Insulin signaling was examined by Western blotting. Fat and lean body mass was measured by nuclear magnetic resonance, and body composition after fasting or high-fat diet was assessed. Energy expenditure was measured by indirect calorimetry. Expression of adiposity and lipid metabolism genes was measured by quantitative PCR. RESULTS: Grb7-null mice were viable, fertile, and without obvious phenotype. Grb7 ablation improved glycemic control and displayed sensitization to insulin signaling in the liver. Grb7-null females but not males had increased gonadal white adipose tissue mass. Following a 12-week high-fat diet, Grb7-null female mice gained fat body mass and developed relative insulin resistance. With fasting, there was less decrease in fat body mass in Grb7-null female mice. Female mice with Grb7 ablation had increased baseline food intake, less energy expenditure, and displayed a decrease in the expression of lipolysis and adipose browning genes in gonadal white adipose tissue by transcript and protein analysis. CONCLUSION: Our study suggests that Grb7 is a negative regulator of glycemic control. Our results reveal a role for Grb7 in female mice in the regulation of the visceral adipose tissue mass, a powerful predictor of metabolic dysfunction in obesity.

Gender-specific abdominal fat distribution and insulin resistance associated with organophosphate esters and phthalate metabolites exposure.

The worldwide prevalence of obesity highlights the potential contribution of endocrine-disrupting chemicals (EDCs). However, common epidemiological measures such as body mass index and waist circumference may misrepresent the intricate obesity risks these chemicals pose across genders. This study delves deeper into abdominal fat by differentiating between subcutaneous and visceral regions by analyzing data from National Health and Nutrition Examination Surveys (NHANES). We particularly investigated the gender-specific associations between organophosphorus flame-retardant metabolites (mOPFRs), phthalates (mPAEs) and accumulated fat indexes from 2536 people. Aiding by Bayesian Kernel Machine Regression (BKMR), we found while co-exposure to mOPFRs and mPAEs was linked to general and abdominal obesity across the entire and gender-specific populations, a gender-specific fat distribution emerged. For women, urinary BDCPP and MBzP were linked to an increased subcutaneous fat index (SFI) [BDCPP OR: 1.12 (95% CI: 1.03-1.21), MBzP OR: 1.09 (95% CI: 1.01-1.18)], but not to visceral fat index (VFI). These metabolites had a combined linkage with SFI, with BDCPP (weighting 22.0%) and DPHP (weighting 31.0%) being the most influential in Quantile g-computation model (qgcomp) model. In men, BCEP exposure exclusively associated with the elevated VFI [OR: 1.14 (95% CI: 1.03-1.26)], a trend further highlighted in mixture models with BCEP as the predominant association. Intriguingly, only males displayed a marked correlation between these metabolites and insulin resistance in subpopulation. An attempted mediation analysis revealed that elevated C-reactive protein mediated 12.1% of the association between urinary BCEP and insulin resistance, suggesting a potential role of inflammation. In conclusion, the gender-specific fat distribution and insulin resistance that associated with mOPFRs represented the potential risk of these chemicals to man.

Comparison of abdominal adipose tissue versus body mass index (BMI) as a predictor of complications and survival in liver transplantation.

INTRODUCTION: Because of the obesity epidemic, more obese patients are on liver transplant (LT) waiting lists. The diseases associated with obesity may increase complications and limit survival after LT. However, there is no established measure or cut-off point to determine this impact and aid decision making. The aim of the present study is to evaluate obesity in patients undergoing LT via BMI and CT-based measurement of adipose tissue (AAT). These parameters will be used to predict the risk of postoperative complications and 5-year survival. METHODS: A retrospective, single-center study was carried out at a tertiary Spanish hospital, including all patients who received LT between January 2012 and July 2019 (n = 164). The patients were adults who underwent LT using the 'piggyback' technique, preserving the recipient vena cava. Visceral adipose tissue (VAT) and BMI were calculated to examine correlations with postoperative complications and 5-year survival. RESULTS: No significant association was found between postoperative complications by Comprehensive Complication Index, BMI, AAT/height, subcutaneous fat/height and VAT/height. Kaplan-Meier curves for 5-year survival compared LT recipients with BMI < 30.45 versus ≥30.45, with an estimated survival of 58.97 months versus 43.11 months, respectively (P < .001) (Fig. 3) and for LT recipients with an AAT/height <27.35 mm versus ≥27.35 mm, with an estimated survival of 57.69 months versus 46.34 months (P = .001). CONCLUSIONS: This study does not show a higher rate of postoperative complications in obese patients. There is a significantly lower long-term survival in patients with AAT/height ≥27.35 mm and BMI ≥ 30.45. BMI is a valid estimate of obesity and is predictive of survival.

Influence of abdominal fat distribution and inflammatory status on post-operative prognosis in non-small cell lung cancer patients: a retrospective cohort study.

PURPOSE: To evaluate the influence of visceral fat area (VFA), subcutaneous fat area (SFA), the systemic immune-inflammation index (SII) and total inflammation-based systemic index (AISI) on the postoperative prognosis of non-small cell lung cancers (NSCLC) patients. METHODS: 266 NSCLC patients received surgery from two academic medical centers were included. To assess the effect of abdominal fat measured by computed tomography (CT) imaging and inflammatory indicators on patients' overall survival (OS) and progression-free survival (PFS), Kaplan-Meier survival analysis and Cox proportional hazards models were used. RESULTS: Kaplan-Meier analysis showed the OS and PFS of patients in high-VFA group was better than low-VFA group (p < 0.05). AISI and SII were shown to be risk factors for OS and PFS (p < 0.05) after additional adjustment for BMI (Cox regression model II). After further adjustment for VFA (Cox regression model III), low-SFA group had longer OS (p < 0.05). Among the four subgroups based on VFA (high/low) and SFA (high/low) (p < 0.05), the high-VFA & low-SFA group had the longest median OS (108 months; 95% CI 74-117 months) and PFS (85 months; 95% CI 65-117 months), as well as the lowest SII and AISI (p < 0.05). Low-SFA was a protective factor for OS with different VFA stratification (p < 0.05). CONCLUSION: VFA, SFA, SII and AISI may be employed as significant prognostic markers of postoperative survival in NSCLC patients. Moreover, excessive SFA levels may encourage systemic inflammation decreasing the protective impact of VFA, which may help to provide targeted nutritional support and interventions for postoperative NSCLC patients with poor prognosis.

DNA methylation promotes the expression of PPARγ transcript 1 at least in part by preventing NRF1 binding to the promoter P1 of chicken PPARγ gene.

Peroxisome proliferator-activated receptor gamma (PPARγ) is a master regulator of adipogenesis. Our previous study revealed that chicken PPARγ has 3 alternative promoters named as P1, P2, and P3, and the DNA methylation of promoter P3 was negatively associated with PPARγ mRNA expression in abdominal adipose tissue (AAT). However, the methylation status of promoters P1 and P2 is unclear. Here we assessed promoter P1 methylation status in AAT of Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). The results showed that promoter P1 methylation differed in AAT between the lean and fat lines of NEAUHLF at 7 wk of age (p < 0.05), and AAT expression of PPARγ transcript 1 (PPARγ1), which was derived from the promoter P1, was greatly higher in fat line than in lean line at 2 and 7 wk of age. The results of the correlation analysis showed that P1 methylation was positively correlated with PPARγ1 expression at 7 wk of age (Pearson's r = 0.356, p = 0.0242), suggesting P1 methylation promotes PPARγ1 expression. To explore the underlying molecular mechanism of P1 methylation on PPARγ1 expression, bioinformatics analysis, dual-luciferase reporter assay, pyrosequencing, and electrophoresis mobility shift assay (EMSA) were performed. The results showed that transcription factor NRF1 repressed the promoter activity of the unmethylated P1, but not the methylated P1. Of all the 4 CpGs (CpG48, CpG49, CpG50, and CpG51), which reside within or nearby the NRF1 binding sites of the P1, only CpG49 methylation in AAT was remarkably higher in the fat line than in lean line at 7 wk of age (3.18 to 0.57, p < 0.05), and CpG49 methylation was positively correlated with PPARγ1 expression (Pearson's r = 0.3716, p = 0.0432). Furthermore, EMSA showed that CpG49 methylation reduced the binding of NRF1 to the P1. Taken together, our findings illustrate that P1 methylation promotes PPARγ1 expression at least in part by preventing NRF1 from binding to the promoter P1.

Evaluation of abdominal fat pad aspiration highlighting challenges to interpretation.

INTRODUCTION: Fine-needle aspiration (FNA) of abdominal fibroadipose tissue is a commonly utilized method for the detection of amyloidosis. While generally regarded as an accurate and specific detection method, the sensitivity is variable. The objective of this study was to investigate the performance of fat pad FNAs in detecting amyloidosis relative to other tissue biopsies. MATERIALS AND METHODS: Fat pad FNA results from January 1, 2014, to December 31, 2022, were catalogued. Clinical data including FNA indication were ascertained for each case. The results of any subsequent tissue biopsy/biopsies evaluated for amyloidosis by Congo red staining were also assessed. Challenges to diagnostic interpretation were explored. RESULTS: A total of 334 fat pad FNAs were identified. The most common indications were peripheral neuropathy (29.3%), cardiomyopathy/heart failure (28.1%), monoclonal gammopathy (27.8%), and multiple myeloma/lymphoplasmacytic lymphoma (21.0%). Cytologic interpretations were: 7 (2.1%) nondiagnostic, 284 (85.0%) negative, 18 (5.4%) indeterminate, 16 (4.8%) suspicious, and 9 (2.7%) positive for amyloid deposition. In our sample, 103 (30.8%) patients had Congo red testing performed on a subsequent surgical specimen(s) including: 3 of 7 of nondiagnostic cases, none which were positive on the subsequent surgical; 70 of 284 negative cases, 27 which were positive on the subsequent surgical; 11 of 18 indeterminate cases, 7 which were positive on the subsequent surgical; 13 of 16 suspicious cases, 2 which were positive on the subsequent surgical; and 6 of 9 positive cases, 3 which were positive on the subsequent surgical. Challenges to FNA interpretation included scant cellularity, focal staining/birefringence, and overstaining. CONCLUSIONS: It is best to view fat pad aspiration versus other tissue biopsy results as complimentary diagnostic tests that should be interpreted in the context of the clinical setting and overall clinical suspicion for amyloidosis.

Evaluation for Performance of Body Composition Index Based on Quantitative Computed Tomography in the Prediction of Metabolic Syndrome.

Objective: We aimed to evaluate the performance of predicting metabolic syndrome (MS) using body composition indices obtained by quantitative computed tomography (QCT). Methods: In this cross-sectional study, data were collected from 4745 adults who underwent QCT examinations at a Chongqing teaching hospital between July 2020 and March 2022. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), total abdominal fat (TAT), abdominal muscle tissue (AMT), and liver fat content (LFC) were measured at the L2-L3 disc level using specialized software, and the skeletal muscle index (SMI) were calculated. The correlations between body composition indicators were analyzed using the Pearson correlation analysis. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess these indicators' predictive potential for MS. Results: VAT and TAT exhibited the best predictive ability for MS, with AUCs of 0.797 [95% confidence interval (CI): 0.779-0.815] and 0.794 (95% CI: 0.775-0.812) in males, and 0.811 (95% CI: 0.785-0.836) and 0.802 (95% CI: 0.774-0.830) in females. The AUCs for VAT and TAT were the same but significantly higher than body mass index and other body composition measures. SAT also demonstrated good predictive power in females [AUC = 0.725 (95%CI: 0.692-0.759)] but fair power in males [AUC = 0.6673 (95%CI: 0.650-0.696)]. LFC showed average predictive ability, AMT showed average predictive ability in males but poor ability in females, and SMI had no predictive ability. Correlation analysis revealed a strong correlation between VAT and TAT (males: r = 0.95, females: r = 0.89). SAT was strongly correlated with TAT only in females (r = 0.89). In the male group, the optimal thresholds for VAT and TAT were 207.6 and 318.7 cm2, respectively; in the female group, the optimal thresholds for VAT and TAT were 128.0 and 269.4 cm2, respectively. Conclusions: VAT and TAT are the best predictors of MS. SAT and LFC can also be acceptable to make predictions, whereas AMT can only make predictions of MS in males.

Abdominal fat depots are related to lower cognitive functioning and brain volumes in middle-aged males at high Alzheimer's risk.

OBJECTIVE: High BMI, which poorly represents specific fat depots, is linked to poorer cognition and higher dementia risk, with different associations between sexes. This study examined associations of abdominal fat depots with cognition and brain volumes and whether sex modifies this association. METHODS: A total of 204 healthy middle-aged offspring of Alzheimer's dementia patients (mean age = 59.44, 60% females) underwent abdominal magnetic resonance imaging to quantify hepatic, pancreatic, visceral, and subcutaneous adipose tissue and to assess cognition and brain volumes. RESULTS: In the whole sample, higher hepatic fat percentage was associated with lower total gray matter volume (ß = -0.17, p < 0.01). Primarily in males, higher pancreatic fat percentage was associated with lower global cognition (males: ß = -0.27, p = 0.03; females: ß = 0.01, p = 0.93) executive function (males: ß = -0.27, p = 0.03; females: ß = 0.02, p = 0.87), episodic memory (males: ß = -0.28, p = 0.03; females: ß = 0.07, p = 0.48), and inferior frontal gyrus volume (males: ß = -0.28, p = 0.02; females: ß = 0.10, p = 0.33). Visceral and subcutaneous adipose tissue was inversely associated with middle frontal and superior frontal gyrus volumes in males and females. CONCLUSIONS: In middle-aged males at high Alzheimer's dementia risk, but not in females, higher pancreatic fat was associated with lower cognition and brain volumes. These findings suggest a potential sex-specific link between distinct abdominal fat with brain health.

Cold Ambient Temperature Does Not Alter Subcutaneous Abdominal Adipose Tissue Lipolysis and Blood Flow in Endurance-Trained Cyclists.

This study sought to investigate the effect of cold ambient temperature on subcutaneous abdominal adipose tissue (SCAAT) lipolysis and blood flow during steady-state endurance exercise in endurance-trained cyclists. Ten males (age: 23 ± 3 years; peak oxygen consumption: 60.60 ± 4.84 ml·kg-1·min-1; body fat: 18.4% ± 3.5%) participated in baseline lactate threshold (LT) and peak oxygen consumption testing, two familiarization trials, and two experimental trials. Experimental trials consisted of cycling in COLD (3 °C; 42% relative humidity) and neutral (NEU; 19 °C; 39% relative humidity) temperatures. Exercise consisted of 25 min cycling at 70% LT and 25 min at 90% LT. In situ SCAAT lipolysis and blood flow were measured via microdialysis. Heart rate, core temperature, carbohydrate and fat oxidation, blood glucose, and blood lactate were also measured. Heart rate, core temperature, oxygen consumption, and blood lactate increased with exercise but were not different between COLD and NEU. SCAAT blood flow did not change from rest to exercise or between COLD and NEU. Interstitial glycerol increased during exercise (p < .001) with no difference between COLD and NEU. Fat oxidation increased (p < .001) at the onset of exercise and remained elevated thereafter with no difference between COLD and NEU. Carbohydrate oxidation increased with increasing exercise intensity and was greater at 70% LT in COLD compared to NEU (p = .030). No differences were observed between conditions for any other variable. Cycling exercise increased SCAAT lipolysis but not blood flow. Ambient temperature did not alter SCAAT metabolism, SCAAT blood flow, or fat oxidation in well-trained cyclists, though cold exposure increased whole-body carbohydrate oxidation at lower exercise intensities.

Visceral and subcutaneous abdominal fat is associated with non-alcoholic fatty liver disease while augmenting Metabolic Syndrome's effect on non-alcoholic fatty liver disease: A cross-sectional study of NHANES 2017-2018.

BACKGROUND: The aim was to evaluate the effect different types of abdominal fat have on NAFLD development and the effects of abdominal fat has on the association between Metabolic Syndrome (MetS) and NALFD. METHODS: Data was collected from the cross-sectional NHANES dataset (2017-2018 cycle). Using the controlled attenuation parameter (USG CAP, dB/m), which measures the level of steatosis, the cohort was stratified into two groups: NAFLD(+) (≥274 dB/m) and NAFLD(-). Using complex samples analyses, associations between liver steatosis or NAFLD and types of abdominal fat area [Total abdominal (TAFA), subcutaneous (SAT), and visceral (VAT)] were determined. Pearson's correlation coefficient (r) was calculated to evaluate the associations between adipose tissues and NAFLD. Logistic regression was used to determine the risk [odds ratio (OR) and 95% confidence interval (95%CI)]. Participants were also classified by MetS, using the Harmonizing Definition criteria. RESULTS: Using 1,980 participants (96,282,896 weighted), there was a significant (p<0.001) correlation between USG CAP and TAFA (r = 0.569), VAT (r = 0.645), and SAT (r = 0.479). Additionally, the risk of developing NAFLD was observed for total abdominal obesity (OR = 19.9, 95%CI: 5.1-77.8, p<0.001), visceral obesity (OR = 9.1, 95%CI: 6.2-13.5, p<0.001) and subcutaneous obesity (OR = 4.8, 95%CI: 3.2-6.9, p<0.001). Using 866 participants (44,399,696 weighted), for visceral obesity, participants with MetS and visceral obesity (OR = 18.1, 95%CI: 8.0-41.3, p<0.001) were shown to have a greater risk than participants with MetS only (OR = 6.3, 95%CI: 2.6-15.2, p<0.001). For subcutaneous obesity, again, participants with MetS and subcutaneous obesity (OR = 18.3, 95%CI: 8.0-41.9, p<0.001) were shown to have a greater risk than the MetS-only group (OR = 10.3, 95%CI: 4.8-22.4, p<0.001). CONCLUSION: TAFA, VAT, and SAT were positively associated with USG CAP values and increased the risk of developing NAFLD. Also, the type of abdominal fat depots did affect the association between MetS and NAFLD.

Estimation of genetic parameters for visceral diseases of fattening Japanese Black cattle in Shimane Prefecture, Japan.

In this study, the genetic parameters of major visceral diseases were estimated using the postmortem inspection records of 9057 fattening Japanese Black cattle in Shimane Prefecture, Japan, and the genetic correlation between visceral diseases and carcass traits was analyzed. There were six visceral diseases with a prevalence of 5% or higher, namely, pleurisy, pneumonia, bovine abdominal fat necrosis (BFN), rumenitis, hemorrhagic hepatitis, and perihepatitis. Variance components were estimated using the Gibbs sampling method, and the heritability of the visceral disease ranged from 0.07 to 0.49 for perihepatitis and BFN, respectively. Significant negative genetic correlations were identified between pleurisy and rib thickness (-0.32), BFN and carcass weight (-0.29), and BFN and rib eye area (-0.22). No significant genetic correlation was observed among the visceral diseases. The least squares analysis of variance suggested that some visceral diseases decrease the value of carcass traits. In particular, carcass weight and rib eye area in individuals with BFN were 11.7 kg and 1.87 cm2 lower than those of healthy cattle, respectively. Thus, it was inferred that genetic factors were involved in the visceral diseases of fattening Japanese Black cattle in Shimane Prefecture.