bluuebunny/crossref_metadata_2025_split huggingface dataset:
1604-P: Lrrc2 Preserves Mitochondrial ATP Production in Diabetic Muscle and Promotes Adaptations to Exercise
Authors: PENNIMAN CHRISTIE M. , BHARDWAJ GOURAV , ALLEN RYAN , LIRA VITOR A. , O'NEILL BRIAN T. 
Published: June 2024

Uncontrolled diabetes impairs muscle strength and mitochondrial metabolism, leading to disabilities. FoxOs are key mediators of insulin signaling and we demonstrated that FoxOs mediate mitochondrial dysfunction in mice with streptozotocin (STZ) diabetes. Unfortunately, knockout of FoxOs in proliferative tissues causes cancer. We aimed to investigate FoxO targets restricted to skeletal muscle in hopes of improving strength in diabetic conditions without carcinogenic effects. RNA-seq from STZ mice with/without FoxO1/3/4 triple knockout showed LRRC2 (Leucine rich repeating containing 2) is a striated-muscle specific FoxO target that is transiently increased in diabetic muscle. The function of LRRC2 is unknown, but gene expression databases show LRRC2 is restricted to muscle and heart. Adenoviral overexpression of LRRC2 in C2C12 cells localized to mitochondria and showed increase mRNA levels of biogenesis marker PGC1α, and antioxidant genes SOD2 and Gpx3. To determine LRRC2’s effect on exercise tolerance and mitochondrial bioenergetics in vivo, we created muscle specific LRRC2 knockout (LKO) mice and rendered them diabetic with STZ. Diabetic LKO mice had the poorest performance on treadmill exercise to exhaustion, and female LKO mice showed impaired exercise training with free wheel running when compared to controls. Interestingly, soleus muscles from LKO mice were 17% larger than their controls, whereas extensor digitorum longus (EDL) were 25% smaller in the diabetic LKO mice, indicating divergent effects on oxidative vs. glycolytic muscle. Soleus permeabilized fibers showed 20% decreased ATP production in diabetic LKO compared to controls that was uncoupled from respiration with glutamate/malate. Mitochondria from quad/gastroc of LKO mice showed increased H2O2 production compared to controls.
In conclusion, Lrrc2 is a novel FoxO target that helps preserve mitochondrial function and exercise tolerance in a type 1 diabetes mouse model.

Disclosure
C.M. Penniman: None. G. Bhardwaj: None. R. Allen: None. V.A. Lira: None. B.T. O'Neill: None.

Funding
VA Merit Review Award Number (lO1 BXOO4468); Fraternal Order of Eagles Diabetes Research
1605-P: Skeletal Muscle Ubiquitin Protease Function Governs Mitochondrial Quality Control and Insulin Sensitivity in Type 2 Diabetes
Authors: AXELROD CHRISTOPHER L. , DANTAS WAGNER S. , HEINTZ ELIZABETH C. , ZUNICA ELIZABETH R.M. , DAVULURI GANGARAO , KIRWAN JOHN P. 
Published: June 2024

Introduction: Skeletal muscle mitochondrial content declines in patients with type 2 diabetes (T2D), which is driven by prolonged hyperactivation of DRP1-mediated organelle fission. However, the mechanism underlying activation of fission and its relation to the regulation of glucose uptake in T2D remains largely unknown. The purpose of this study was to examine the influence of ubiquitin function on mitochondrial quality control and DRP1 hyperactivation in patients with T2D.
Methods: 58 sedentary adults (37±12 years) were enrolled into one of three groups based upon the following criteria: (1) healthy weight without T2D (HW); (2) obesity without T2D (Ob); or (3) obesity with T2D (T2D). Participants underwent a 3-day inpatient stay for measurements of body composition (DXA), aerobic capacity (VO2MAX), and insulin sensitivity (hyperinsulinemic euglycemic clamp). A skeletal muscle biopsy was obtained for determination of mitochondrial dynamics (Western blot) and isolation of primary human skeletal muscle (pHSkM) cells. pHSkM cells were transfected with FLAG-USP15/USP30 to induce overexpression. Glucose uptake was measured by incorporation of [3H]-2-deoxy-d-glucose. Comparisons were made by one-way ANOVA with contrasts.
Results: USP13, USP15, and USP30 expression were increased in T2D relative to Ov/Ob and HW (all P&lt;0.05). USP15 and USP30 interaction with Parkin decreased in T2D relative to Ov/Ob and HW (all P&lt;0.05). USP15 (R2=0.55, P&lt;0.0001) and USP30 (R2=0.40, P&lt;0.0001) expression negatively correlated with peripheral insulin sensitivity. USP15 and USP30 overexpression activated DRP1 while blocking ubiquitin-mediated Parkin activation.
Conclusions: Ubiquitin protease function is heightened in patients with T2D which impairs mitochondrial quality control, promotes excessive mitochondrial fission, depletes mitochondrial volume, and restricts glucose uptake.

Disclosure
C.L. Axelrod: None. W.S. Dantas: None. E.C. Heintz: None. E.R.M. Zunica: None. G. Davuluri: None. J.P. Kirwan: None.

Funding
National Institutes of Health (DK108089 and GM104940)
1606-P: Modelling Muscle Function Loss in Engineered Human Tissues
Authors: HØJFELDT MARTINA , BIRK JESPER , SEGERITZ-WALKO CHARIS , WOJTASZEWSKI JØRGEN F.P. , PEHMØLLER CHRISTIAN , KNUDSEN JONAS R. 
Published: June 2024

Introduction and Objective: Loss of muscle function is detrimental to the human body and understanding its molecular underpinnings and identifying therapeutic avenues to modify these is of major importance. To enable this, we aimed to develop a translatable drug discovery model that circumvents limitations by species-driven biological differences and demonstrates high sensitivity to readouts related to muscle function.
Methods: A human primary myoblast-based engineered muscle tissue model was established, differentiated, and cultured for weeks. We characterized tissue maturity through contractility and gene and protein expression longitudinally and under various electrical stimulation regimens. Key physiological features such as force-frequency relationship, post-tetanic potentiation, and fatigue during exercise was assessed. Finally, functionality of the tissues following two different atrophy-inducing interventions was studied.
Results: Differentiated tissues maintained stable maximal force production for over 30 days. Maturity markers (muscle AMPK isoforms and mitochondrial, contractile and Ca2+ handling proteins) increased during a 23-day evaluation. Electrical stimulation also increased maturity, including improved maximal contractile force. The tissues exhibited expected physiological responses (force-frequency relationship, post tetanic potentiation and fatigue following exercise mimicking electrical stimulation). Activation of glucocorticoid (by dexamethasone) and activin (by Activin A) signaling pathways dose dependently caused a decline in maximal force development which was mitigated by antagonism. Intriguingly, the model demonstrated sensitivity to detect significant force changes with effect sizes below 15%.
Conclusion: Our human-based engineered muscle tissue model offers a robust platform with high sensitivity for elucidating mechanisms related to muscle function decline and therapeutic exploration.

Disclosure
M. Højfeldt: Employee; Novo Nordisk A/S. J. Birk: None. C. Segeritz-Walko: None. J.F.P. Wojtaszewski: Consultant; Pfizer Inc. Stock/Shareholder; Pfizer Inc., Novo Nordisk A/S. C. Pehmøller: Employee; Novo Nordisk A/S. J.R. Knudsen: Employee; Novo Nordisk A/S.
1608-P: MyoScreen—A High-Content–Based Discovery Platform to Model Key Metabolic Processes in Human Skeletal Muscle
Authors: MOROZZI GIULIO , ZABLOCKI ANIELA , MARTIN-TISSIER ANTOINE , TRAVARD LAURIANE , MASSERA CÉLINE , FLAENDER MÉLANIE , FARGIER GUILLAUME , LORINTIU OANA , VENTRE ERWANN , YOUNG JOANNE , AUTIER VALERIE , SELIG LUC 
Published: June 2024

Introduction & Objective: Loss of muscle mass and function are now recognized as early and common abnormalities in a wide range of chronic diseases especially obesity, diabetes and cardiomyopathies. However, relevant in-vitro screening models mimicking human physiological processes in muscles are still lacking.
Method: Using MyoScreen, a high-throughput and robust skeletal muscle drug discovery platform derived from human primary myoblasts, we have developed a panel of predictive in-vitro image-based functional assays combined with newly developed image analysis scripts, that recapitulate key metabolic disease hallmarks such as autophagy, lipid accumulation, muscle atrophy and mitochondrial health.
Results: Dose dependent accumulation of LC3b spots (puncta) (EC50= 20.77 μM for CQ, Chloroquine, EC50= 3.9 nM for BafA1, Bafilomycin) and area of vesicles positive for LC3b (EC50= 25.97 μM for CQ, EC50= 6.1 nM for BafA1) can be monitored in fixed starved (8h) cells following inhibition of autophagy flux. Co-labeling of LAMP1-LC3b (EC50= 23.17 μM for CQ, EC50= 2.7 nM for BafA1) follows the autophagic flux and autophagolysosome formation. Oversupply of FAs (fatty acids) increases mitochondrial fragmentation and the relative area of LDs (lipid droplets) in myotubes by 13-23%: this accumulation can be modulated by siRNAs treatment. MyoScreen demonstrated the ability to distinguish phenotypic properties related to stimulatory or inhibitory effects of hypertrophic (IGF-1 EC50=95.5 pM for fusion index) or atrophic (TNF-α IC50=15.9 pM for fusion index) signaling compounds.
Conclusion: The MyoScreen platform brings new prospects for drug discovery in metabolic disorders facilitating a predictive research strategy for identifying and validating novel targets, understanding mechanism of action, and supporting preclinical development to select innovative drug candidates targeting key aspects of muscle metabolic function.

Disclosure
G. Morozzi: None. A. Zablocki: None. A. Martin-Tissier: None. L. Travard: None. C. Massera: None. M. Flaender: None. G. Fargier: None. O. Lorintiu: None. E. Ventre: Employee; CYTOO. J. Young: None. V. Autier: None. L. Selig: None.
1609-P: Whole-Body Metabolic Flexibility Is Discordant with Skeletal Muscle Metabolism
Authors: KRASSOVSKAIA POLINA , JEVTOVIC FILIP , CHORZEPA MARTA , JONES TERRY E. , TANNER CHUCK J. , ZHENG DONGHAI , PORIES WALTER J. , DOHM LYNIS , HOUMARD JOSEPH A. , BROSKEY NICHOLAS T. 
Published: June 2024

Introduction & Objective: Metabolic inflexibility is the inability to appropriately switch substrate use in response to a metabolic challenge and is seen in individuals with metabolic disease. Metabolic inflexibility can be observed in seemingly healthy individuals, potentially predisposing them to metabolic disease. The goal of this study was to examine if whole-body metabolic inflexibility is reflected by differential substrate use at the skeletal muscle (SkM) level.
Methods: This study recruited young (27 ± 8 years) healthy individuals with overweight. Anthropometric measures, VO2max test, hyperinsulinemic-euglycemic clamp, and a vastus lateralis biopsy was performed. Based on difference in the respiratory quotient (ΔRQ) during the clamp, participants were median stratified to a “metabolically flexible” (FLEX) (ΔRQ&gt;0.06; n=10) or “metabolically inflexible” (INFLEX) (ΔRQ&lt;0.06; n=9) group. SkM biopsy samples were assessed for substrate oxidation with 14C-pyruvate and 14C-palmitate, mitochondrial respiration, and muscle fiber type. Data was analyzed with descriptive statistics, Mann-Whitney U-test, and Student’s t-test.
Results: FLEX had a lower BMI than INFLEX (26.4 ± 1.3 vs 28.7 ± 1.5 kg/m2; p=0.002) but had a similar percentage of body fat (p=0.3) or lean mass (p=0.2). Groups did not differ in age (p=0.06), VO2max (p=0.3), M value (p=0.1), or basal RQ (p=0.5). FLEX had lower palmitate oxidation than INFLEX (p=0.03) and trended towards a higher ratio of pyruvate to palmitate oxidation (p=0.06). Incomplete palmitate oxidation was also higher in FLEX (p=0.003). Groups did not differ in mitochondrial respiratory capacity (p=0.3) or fiber type (p=0.9). ΔRQ was significantly associated with the M value (p=0.02, r=0.55) and did not associate with fiber type (p=0.6, r=0.16).
Conclusions: FLEX and INFLEX individuals differ in substrate oxidation in SkM tissue with INFLEX showing greater and more efficient fat oxidation. Differences in ΔRQ are not influenced by muscle fiber type.

Disclosure
P. Krassovskaia: None. F. Jevtovic: None. M. Chorzepa: None. T.E. Jones: None. C.J. Tanner: None. D. Zheng: None. W.J. Pories: None. L. Dohm: None. J.A. Houmard: None. N.T. Broskey: None.

Funding
National Institutes of Health R01DK120296
1613-P: Sphingolipid Imbalance and Insulin Resistance in MAFLD-Related Sarcopenia
Authors: YAN QIANHUA , SU LIANYONG , LING TAI YUN , ZHAO DERRICK , WANG XUAN , C GURLEY EMILY , B HYLEMON PHILLIP , ZHOU XIQIAO , ZHOU HUIPING 
Published: June 2024

Introduction & Objective: Metabolic fatty liver disease (MAFLD) is closely related to dysregulation of systemic metabolism and insulin resistance (IR). Sarcopenia is often observed in individuals with MAFLD. Sphingolipids, known for their pivotal role in muscle cell regeneration and repair, have been suggested as key regulators in this context. This study aims to elucidate the potential connection between sphingolipid dysregulation in muscle and MAFLD.
Methods: Ten-week-old male mice with a C57BL/6J and 129S1/SvlmJ mixed background were subjected to either a WDSW (Western diet, Harlan, TD88137, and a high fructose-glucose solution, 23.1g/L D-fructose plus 18.9g/L D-glucose) or standard chow diet for 24 weeks, with free access to food and water. IPGTT and ITT tested were conducted at the end of the study. The sphingolipid profiles in the gastrocnemius muscle were determined using LC-MS/MS. The expression levels of sphingosine-1 phosphate receptors (S1PRs) were measured by qRT-PCR. The GEO data set (GSE73036) was downloaded and analyzed.
Result: Mice on the WDSW (MASH mice) exhibited significantly higher blood glucose levels and increased IR after 24 weeks of WDSW feeding. LC-MS/MS analysis indicated elevated levels of C18-Sphingomyelin (SM), C26-SM and C18:1 Dihydroceramide in the muscle of the WDSW group, while S1P levels were markedly reduced. The expression levels of S1PR1-3, the major types of S1PR in muscle, were also significantly decreased in MASH mice. Analysis of GSE73036 highlighted a strong correlation between IR and upregulation of S1P lyase (Spgl), an enzyme crucial for S1P degradation.
Conclusion: The findings of this study indicate a clear association between disrupted sphingolipid metabolism and IR in MASH mouse model. The observed increase in ceramide levels coupled with a decrease of S1P may contribute to sarcopenia associated with MAFLD.

Disclosure
Q. Yan: None. L. Su: None. Y. Tai: None. D. Zhao: None. X. Wang: None. E. Gurley: None. P. Hylemon: None. X. Zhou: None. H. Zhou: None.

Funding
National Natural Science Foundation Of China (No.82004286)
1615-P: Adrenal Gland Volume and Development of Type 2 Diabetes Using Deep Learning Techniques
Authors: JEONG KU EU , HO YOON SOON , SHIN PARK SEUNG , HEE KIM JUNG , YOON JIWON 
Published: June 2024

Objectives: Current insights into the dynamic between adrenal gland volume (AGV) and changes in blood glucose levels are insufficiently explored. This research aims to establish an association between AGV, evaluated through a deep learning-based method, and the risk of developing type 2 diabetes (T2D).
Research Design and Methods: Our study included an analysis of 9,708 adults who underwent abdominopelvic CT scans during health examinations between 2011 and 2012. Eligibility for the study was contingent on the absence of adrenal nodules in participants. We obtained AGV measurements from CT scans using a three-dimensional nnU-Net deep learning framework. The research approach to understanding the AGV-T2D relationship was designed to be both cross-sectional and longitudinal.
Results: The AI model demonstrated notable precision in segmenting the adrenal gland, with a correlation coefficient of 0.71 (standard deviation [SD], 0.11) and an average volume discrepancy of 0.6 mL (SD 0.9) in an external dataset. At the outset, individuals with T2D showed higher AGV compared to those without T2D (7.3 vs. 6.7 cm³ in males and 6.3 vs. 5.5 cm³ in females, all P &lt;0.05). Furthermore, AGV was positively correlated with various metabolic factors, including waist size, area of abdominal visceral fat, triglyceride-glucose index, and levels of glycated hemoglobin. We determined optimal AGV cutoffs for T2D prediction to be 7.2 cm³ for males and 5.5 cm³ for females. Following a median 7-year observation period, 938 subjects were diagnosed with T2D. A significant observation was that individuals with higher AGV faced a greater cumulative risk of developing T2D, this finding remained significant after controlling for other known risk factors (hazard ratio [95% confidence interval], 1.268 [1.105-1.455]).
Conclusions: In summary, AGV evaluated using deep learning techniques demonstrated a significant association with current diabetes status and can be considered a reliable predictor for T2D.

Disclosure
E. Ku: None. S. Yoon: Stock/Shareholder; MEDICAL IP. S. Park: None. J. Kim: None. J. Yoon: None.

Funding
This study was supported by the National Research Foundation of the Ministry of Science and ICT of Korea (Project No. NRF-2020R1C1C1010723) and a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute funded by the Ministry of Health and Welfare of the Republic of Korea (Project No. HI21C0032 and HI22C0049).
1622-P: Congruence of Laboratory vs. Histopathologic Findings of Acute Pancreatitis within nPOD Organ Donors
Authors: PENA LOPEZ JULIANA , CAMPBELL-THOMPSON MARTHA , BRUGGEMAN BRITTANY S. 
Published: June 2024

Acute pancreatitis may both result in development of diabetes and is more common in patients with diabetes. Due to its broad presentation, diagnosis typically includes elevated amylase or lipase values three times normal. We aimed to evaluate the performance of amylase and lipase as predictors of acute pancreatitis by histopathology in deceased organ donors within The Network for Pancreatic Organ Donors with Diabetes (nPOD) tissue biobank.Demographic and clinical characteristics were collected from deidentified terminal hospital records. Acute pancreatitis by laboratory criteria was defined as an amylase &gt;420 U/L or lipase &gt;240 U/L. Pancreatic histopathologic analysis was performed to evaluate for acute pancreatitis (acinar cell loss, polymorphonuclear cell infiltrate, fat necrosis, and hemorrhage) in organ donors with and without diabetes.Acute pancreatitis by histopathology was associated with higher mean amylase (477 vs 194; p=0.007) and lipase (823 vs 134 U/L; p=0.003) and acute pancreatitis by laboratory criteria (p=0.0005). However, 38% of individuals with acute pancreatitis by histopathology did not meet laboratory criteria (sensitivity 61.8%; specificity 83%). The positive and negative predictive value of these cutoffs were 70% and 77.2% respectively. Within individuals with type 1 diabetes (T1D), a diagnosis of diabetic ketoacidosis (DKA) was associated with elevated amylase and lipase (mean of 74.5 U/L and 83 U/L without and 461 U/L and 725 U/L with DKA, p&lt;0.03) and acute pancreatitis by laboratory criteria (p=0.006) but not by histopathology (p=0.23). However, the sensitivity and positive predictive value of acute pancreatitis laboratory criteria in donors with DKA improved (73.3% and 85%).Acute pancreatitis diagnosed by laboratory criteria alone is specific at 83% but with a lower sensitivity of 61.8%. These criteria can still be used in T1D individuals with DKA with a higher sensitivity and positive predictive value.

Disclosure
J. Pena Lopez: None. M. Campbell-Thompson: None. B.S. Bruggeman: Research Support; Tandem Diabetes Care, Inc.
1623-P: Artificial Intelligence with QuPATH in Pancreatic Cell Classification
Authors: GUYOT MICHAEL , WILLIAMS MACKENZIE D. , BUMGARNER BENJAMIN M. , MCGRAIL KIERAN M. , CAMPBELL-THOMPSON MARTHA , HALLER MICHAEL J. , BRUGGEMAN BRITTANY S. 
Published: June 2024

We developed Artificial Intelligence classification algorithms in QuPATH containing both supervised and unsupervised components to quantify and classify the pancreas cell types into their respective subtypes based on immunofluorescence (IF) data. The staining panel was performed in formalin-fixed paraffin embedded (FFPE) pancreatic tissue sections from a pancreas organ donor with no diabetes provided by nPOD. From the IF images, a training region was selected. This region was then segmented using a watershed algorithm and then an expert classified each cell in the region. In total, there were 6,899 cells, with an emphasis on the acinar and ductal cell types. This training data was used to train a Random Trees (RT), K Nearest Neighbor (KNN) and Artificial Neural Network (ANN) algorithm. Another region was selected for a validation data set, and once again, each cell was manually classified by an expert in the field. The accuracy of each algorithm was then assessed on the validation set. The accuracy of each algorithm is as follows: RT (89.53%), KNN (85.55%) and ANN (82.97%). In the future, we will include multiple no diabetes pancreases as well as pancreases from the different stages of T1D progression to ensure diversity of the training and validation data. With a more diverse training data set, we predict that ANN’s will become more accurate, and could potentially prove to be more useful than the RT algorithm. With a more diverse validation data set, we can look at the possibility of overfitting artificially inflating the accuracy of our algorithms.From this, we plan to extract relevant feature information such as cell size, number and density among others. After we have the architecture solidified, we hope to use it to analyze differences in control and diseased pancreases, specifically with regards to Type 1 Diabetes (T1D). We hope this will uncover previously overlooked information that may prove critical to the understanding of the mechanism of disease progression of T1D.

Disclosure
M. Guyot: None. M.D. Williams: None. B.M. Bumgarner: None. K.M. McGrail: None. M. Campbell-Thompson: None. M.J. Haller: Consultant; Sanofi. Advisory Panel; SAB Biotherapeutics, Inc. Consultant; MannKind Corporation. B.S. Bruggeman: Research Support; Tandem Diabetes Care, Inc.