bluuebunny/crossref_metadata_2025_split huggingface dataset:
132-OR: Structured Medical Nutrition Therapy Improves Glycemia, Reduces Percentage Body Fat while Maintaining Fat-Free Mass in Individuals with Overweight/Obesity and Type 2 Diabetes
Authors: MOTTALIB ADHAM , HAMDY OSAMA 
Published: June 2024

Recently approved long-acting GLP-1 based therapies are effective in glycemic control and weight loss. However, they reduce fat free mass (FFM), a surrogate for muscle mass. We previously showed that structured medical nutrition therapy (SMNT) also improves glycemia but its effect on FFM is unknown. This is a sub-analysis of a clinical trial where 108 individuals with type 2 diabetes (T2D) and overweight/obesity (age 60±10 years; 57% female; HbA1c 8.07±1.05%; weight 101.4±21.1kg and BMI 35.2±7.7kg/m2) were randomized to 3 groups. Group A met with a registered dietitian (RD) to develop individualized meal plans. Group B & C met with RD and followed an isocaloric SMNT plan that included specific menus and diabetes-specific nutrition formula targeting a total daily protein intake of 1-1.5 gm/kg of adjusted body weight. Group C received additional weekly RD phone support. Body composition was evaluated using bioelectrical impedance. After 16 weeks, A1C did not change in group A but decreased in groups B (-0.66%, 95% CI -1.03 to -0.30) and C (-0.61%, 95% CI -1.0 to -0.23), p &lt;0.001 between groups over time. Weight change was not different between groups. Percentage body fat did not change in group A but decreased in groups B (−1.6%, 95% CI −2.4 to −0.8) and C (−1.2%, 95% CI −2 to−0.3), p &lt;0.05 between groups over time. All groups had no change in FFM. While protein intake was similar between groups at baseline, only groups B & C increased their % energy intake from protein by 4.8% (95% CI 2.8 to 6.8) and 4.2% (95% CI 2.1 to 6.2) respectively, p &lt;0.001 between groups over time. These data suggest that SMNT improves glycemia and reduces % body fat while maintaining FFM compared to individualized meal plans. These changes are likely attributed to increased % energy intake from protein. Further studies are needed to evaluate if SMNT mitigates FFM loss in individuals with overweight/obesity and T2D treated with GLP-1 based therapies.

Disclosure
A. Mottalib: None. O. Hamdy: Research Support; Eli Lilly and Company, Novo Nordisk. Consultant; Abbott Nutrition. Stock/Shareholder; Healthimation. Research Support; Gilead Sciences, Inc. Advisory Panel; Nemaura Medical, Twin Health, L-Nutra Inc.
1323-P: Machine Learning–Based Prediction Model for Neurodegenerative Disease in Patients with Type 2 Diabetes—Derivation and Validation in Two Independent Korean Cohorts
Authors: SANG HYUNJI , LEE MYEONGCHEOL , LEE HOJAE , PARK JAEYU , KIM SUNYOUNG , GEOL WOO HO , CHEOL HWANG YOU , SUN PARK TAE , LIM HYUNJUNG , KEON YON DONG , YOUL RHEE SANG 
Published: June 2024

Objective: This study aimed to assess the validity and utility of a machine learning (ML) model for predicting the 3-year incidence of neurodegenerative diseases (ND) in patients with type 2 diabetes (T2DM).
Methods: We used data from two cohorts, the discovery cohort (one hospital; n=22,311) and the validation cohort (two hospitals; n=2,915) of patients with T2DM recruited between 2008-2022. The outcome of interest was the presence/absence of ND at 3 years. We selected different ML-based models with hyperparameter tuning in the discovery cohort and conducted an area under the receiver operating characteristic curve (AUROC) analysis in the validation cohort.
Results: ND was observed in 133 (0.6%) in the discovery cohort and 15 (0.5%) in the validation cohort. The AdaBoost model had a mean AUROC of 0.82 (95% CI, 0.79-0.85) in the discovery dataset. When this result was applied to the validation dataset, the AdaBoost model exhibited the best performance among the models, with an AUROC of 0.83 (accuracy of 78.6%, sensitivity of 78.6%, specificity of 78.6%, and balanced accuracy of 78.6%). The most influential factors in the AdaBoost model were age and cardiovascular disease.
Conclusion: This study demonstrates the potential utility of ML in predicting ND incidence in patients with T2DM, highlighting its feasibility for patient screening.

Disclosure
H. Sang: None. M. Lee: None. H. Lee: None. J. Park: None. S. Kim: None. H. Woo: None. Y. Hwang: None. T. Park: None. H. Lim: None. D. Yon: None. S. Rhee: None.

Funding
National Institutes of Health Research Project of South Korea (No. 2022-ER1102-01).
1326-P: At-Risk MASH Diagnosis in Patients with Type 2 Diabetes Mellitus
Authors: MARTÍNEZ-ARRANZ IBON , ARRESE MARCO , MAYO REBECA , MINCHOLÉ ITZIAR , ENCARNACIÓN BLANCO MARÍA , ASPICHUETA PATRICIA , ALONSO CRISTINA , BANALES JESUS 
Published: June 2024

Introduction/Objectives: The prevalence of metabolic dysfunction-associated steatohepatitis (MASH) in patients with type 2 diabetes mellitus (T2DM) in US is around 30% and about 20% of patients have liver fibrosis. This study aims to explore the effect of glycemic control in T2DM patients on the diagnosis of At-risk MASH (MASH + Fibrosis≥2) by means of three non-invasive tests (MASEF score, FIB-4 and Fibroscan).
Methods: The study included 275 biopsy-proven MASLD (Metabolic Dysfunction-Associated Steatotic Liver Disease) patients with T2DM. Patients were categorized as good glycemic control (GHb≤7%) and poor glycemic control (GHb&gt;7%). A nested case-control study design was used, matching cohorts for age, BMI, gender and MASLD diagnosis. This process resulted in 97 patients in each group, with no significant differences in age (p=0.831), BMI (p=0.989), gender (p=0.991), and histology (p=0.714). MASEF score (non-invasive test based on metabolomics), FIB-4 and Fibroscan performance were compared to biopsy for the assessment of at-risk MASH.
Results: MASEF score (N=97/97), FIB-4 (N=83/87) and Fibroscan (N=54/54) performances in both cohorts were, respectively: GHb≤7%: AUC=0.76/0.77/0.75; GHb&gt;7%: AUC=0.75/0.67/0.77. There were no significant differences among the three methods for the detection of at-risk MASH in patients with good and poor glycemic control, except for FIB-4 that showed a lower performance on GHb&gt;7% cohort (p=0.01).
Conclusions: Glycemic control does not significantly influence the diagnosis of at-risk MASH in patients with T2DM when using MASEF score or Fibroscan as diagnostic tools.

Disclosure
I. Martínez-Arranz: None. M. Arrese: None. R. Mayo: None. I. Mincholé: None. M. Blanco: None. P. Aspichueta: None. C. Alonso: Employee; RUBIÓ METABOLOMICS. J. Banales: Advisory Panel; Owl-Rubio Metabolomics.
1330-P: Meta-analysis for Establishing Fasting Insulin Reference Ranges in Lean Healthy Asians across Different Ethnicities
Authors: HOR CHENG KOH , CHAN JAMES C.Y. 
Published: June 2024

Diagnostic tests for early prediabetes screening using blood glucose usually suffer from poor sensitivity as these individuals often exhibit slight increase or even normoglycemic blood levels. Conversely, they manifest markedly elevated insulin to compensate for initial insulin resistance. This renders insulin a more sensitive biomarker for prediabetes detection. To date, there is no official guideline for a normal fasting insulin range demarcating healthy individuals from those with prediabetes.
We performed a meta-analysis to establish healthy fasting insulin reference ranges for different Asian ethnicities (Chinese, Malays, South Asians, Koreans and Japanese).
The mean (and 95% reference range) for lean Asians with BMI &lt;25 kg/m2 is 6.12 µU/mL (1.53-24.53 µU/mL). When stratified by ethnicity, the values for Chinese, Malay, South Asians, Japanese and Korean are 6.21 µU/mL (1.55-24.95 µU/mL), 5.95 µU/mL (1.75-20.16 µU/mL), 8.27 µU/mL (1.45-47.19 µU/mL), 5.17 µU/mL (2.10-12.72 µU/mL) and 4.77 µU/mL (0.88-25.82 µU/mL) respectively. Mean and 95% reference range for Asians with BMI ≥ 25 kg/m2 were higher versus lean Asians at 11.23 µU/mL (3.06-41.15 µU/mL).
The fasting insulin ranges reported can serve as references for establishing official healthy fasting insulin ranges customized to specific ethnicities for assessing early insulin resistance for prediabetes diagnosis.

Disclosure
K. Hor Cheng: None. J.C.Y. Chan: None.
1339-P: Multiancestry Genome-Wide Association Study of Diabetic Ketoacidosis
Authors: RHEE MARY K. , DABBS-BROWN AMONAE , HUI QIN , RAGHAVAN SRIDHARAN , ZHOU JIN , REAVEN PETER , WILSON PETER W. , PHILLIPS LAWRENCE S. , SUN YAN 
Published: June 2024

Diabetic ketoacidosis (DKA) is a life-threatening complication disproportionately affecting people with African (AFR) and Hispanic (HIS) more than European (EUR) ancestry. To examine genetic susceptibility to DKA, we performed multi-ancestry meta-analysis of genome-wide association studies (GWAS) of DKA, and phenome-wide association studies (PheWAS) of significant loci, in VA Million Veteran Program (MVP) participants with diabetes, with vs. without DKA, and adjusted for age, sex and top ten principal components. Among 5,036 DKA cases (2,843 EUR; 1,733 AFR; 460 HIS) and 152,119 controls (105,504 EUR; 33,037 AFR; 13,578 HIS), both had mean BMI 31 kg/m2 and were 94% male, but cases were younger than controls (60 vs. 65 yr). Of five genome-wide significant loci identified, four had similar effects across all ancestry groups: increased DKA risk associated with a chromosome (chr) 3 locus (rs1716165575, nearest gene SLC2A2, OR 1.2, 95% CI 1.2-1.3, p=1.25E-18) and two loci on chr 6 (rs3130396, HCG17, OR 1.1 [1.1-1.2], p=1.34E-08; and rs539981616, HLA-DQA1, OR 1.7 [1.6-1.8], p=7.82E-43), and decreased DKA risk with a chr 11 locus (rs3842752, INS-IGF2, OR 0.8 [0.8-0.9], p=8.74E-10). In contrast, for a chr 17 locus (rs113748381, SLC16A11, OR 1.5 [1.3-1.8], p=3.16E-20), HIS and AFR, but not EUR (p&gt;0.05), individuals had higher risk for DKA (OR 1.7 [1.4-1.7] in HIS; OR 1.5 [1.4-1.6] in AFR), and higher effect allele frequencies (HIS 19% and AA 8%, vs. EUR 0.81%). In PheWAS analyses, all genetic loci, except chr 6 HCG17, were significantly associated with DKA (for both type 1 and type 2 diabetes), where SLC2A2, HLADQA1, and SLC16A11 were associated with increased risk of both, and INS-IGF2 was associated with decreased risk.
Conclusion: Both HLA and non-HLA chromosomal regions were associated with increased risk of DKA in a large multi-ancestry cohort. Variants at SLC16A11 were much more common in HIS and AFR compared to EUR individuals and might underlie racial/ethnic differences in the clinical presentation of DKA.

Disclosure
M.K. Rhee: Research Support; Kowa Pharmaceuticals America, Inc. A. Dabbs-Brown: None. Q. Hui: None. S. Raghavan: None. J. Zhou: None. P. Reaven: Research Support; Dexcom, Inc. P.W. Wilson: None. L.S. Phillips: Other Relationship; Diasyst, Inc. Research Support; Kowa Pharmaceuticals America, Inc., Janssen Pharmaceuticals, Inc., AbbVie Inc., Novo Nordisk, GlaxoSmithKline plc, Abbott, Sanofi-Aventis U.S., Pfizer Inc. Y. Sun: None.

Funding
VA Million Veterans Program (MVP 052)
1362-P: Influence of Sarcopenic Obesity on the Prognosis of Inpatients with Type 2 Diabetes—Results of the National MIDIA Registry
Authors: CARRETERO GOMEZ JUANA , ENA JAVIER , JAVIER CARRASCO-SÁNCHEZ FRANCISCO , CARLOS AREVALO LORIDO JOSE , GARCIA MARTINEZ LUIS , GONZÁLEZ GONZÁLEZ PATRICIA 
Published: June 2024

Introduction & Objective: Obesity is characterized by an increase of fat mass and a reduced muscle mass. Sarcopenia is diagnosed based on low muscle strength, quantity, and physical performance. Muscle is the main peripheral glucose metabolizer and insulin resistance induces muscle mass lost. Sarcopenic Obesity (SO) may be defined as a clinical and functional condition characterized by the coexistence of obesity and sarcopenia. SO is associated with a poor prognosis in chronic diseases and poor metabolic control. We aimed to assess the relationship between SO and both, metabolic control and comorbidities in T2DM inpatients.
Methods: Over 1300 inpatients, we analyzed 376 with screening (SARC-F: strength; walking assistance; rising from a chair; climbing stairs) for sarcopenia. We compared patients with and without sarcopenia (SARC-F &lt;u&gt;&gt;&lt;/u&gt;4).
Results: 243 patients had sarcopenia. In table 1 we show the main characteristics of the groups. In the unadjusted logistic regression model, the risk of mortality among sarcopenics was OR 3.67 (95% CI, 1.22-15.85), p=0.039; After adjustment, the risk of mortality is related to age (p=0.001), comorbidity (p=0.02) and frailty (p=0.04).
Conclusion: patients with SO were older and had greater frailty and comorbidities. They had more glycemic variability and poor prognosis which depends on their own characteristics.

Disclosure
J. Carretero Gomez: None. J. Ena: None. F. Carrasco-Sánchez: None. J. Arevalo Lorido: None. L. Garcia Martinez: None. P. González González: None.
1375-P: Study of Clinical Profile and Comparison of Metabolic Parameter and Vitamin D Level in Patients with Young-Onset Diabetes Mellitus
Authors: JENA DEBARCHAN , SWAIN JAYSHREE , TELI BRIJ 
Published: June 2024

Introduction: Metabolic phenotype of Indian population differs markedly from western population. Vitamin D deficiency has been associated with morbidities related to cardiovascular, inflammatory, autoimmune diseases and malignancy. Recent studies have linked vitamin D to the pathogenesis of diabetes and its complications.Objectives: To study the clinical profile and to correlate the metabolic parameters and Vitamin-D level among young onset diabetes patients.
Methodology: Total 148 Patients with young onset diabetes mellitus, presenting to the opd of Endocrinology department between July 2021 to August 2023 were included. Relevant sociodsemographic, metabolic and anthropometric parameters were obtained.
Results: Majority of patients were T1DM(64.2%), followed by T2DM(16.5%), FCPD(13.8%), MODY(2.8%) and Unclassified(2.7%.). Mean age was 15.6±8.9 years. Mean BMI was 17.27±5.1. BMI has significant(p&lt;0.05) positive correlation with serum TG. Overall dyslipidaemia observed in 10.1% of patients. HbA1C level has significantly(p&lt;0.05) negative correlation with TC and significant positive correlation with TG and significant(p&lt;0.05) negative correlation with Vit-D level. Vit-D level was low in 48% of patients.
Conclusion: HbA1C was found to have negative correlation with Vitamin-D level and positive correlation with TG level among young diabetic patients. About one in two patients had low Vitamin-D level. We may conclude that Vit-D level and TG level may play important role in young onset diabetes mellites. However, further research is mandated to establish any significant association.

Disclosure
D. Jena: None. J. Swain: None. B. Teli: None.
1376-P: Association of Lung Function and Glycemic Control with All-Cause and Cardiovascular Mortality in Persons with Type 2 Diabetes
Authors: LI CHIA-ING , LIN CHENG-CHIEH , LI TSAI-CHUNG , LIU CHIU-SHONG , YANG CHUAN-WEI 
Published: June 2024

Introduction & Objective: Hyperglycemia is associated with impaired pulmonary function, which can ultimately lead to all-cause and cardiovascular mortality. Few studies have examined the potential interaction effect of pulmonary function on the association between glycemic control and mortality. The aim of this study examined the association of pulmonary function parameters with mortality, and whether glycemic level modified the effect of pulmonary function on mortality in persons with type 2 diabetes (T2DM).
Methods: A retrospective cohort study identified 3846 persons with T2DM with pulmonary function testing in Taiwan between 2002 and 2020. Pulmonary function parameter was assessed by expiratory volume in 1 second (FEV1). Multivariate Cox proportional hazards model with product terms of pulmonary function parameters and glucose control were added to evaluate their interaction.
Results: A total of 733 deaths (19.06%) and 274 expanded CVD deaths (7.12%) were observed during an average follow-up of 7.83 years. The adjusted hazard ratios of all-cause mortality for persons with FEV1 Z-scores of &lt; 0 to -1, &lt;-1 to -2 and &lt;-2 were 1.47 (1.20, 1.80), 2.48 (1.95, 3.14) and 3.07 (1.74, 5.44) compared to participants with Z-score ≥ 0, respectively (P for trend p&lt;0.001). Subgroup analysis revealed that the association between FEV1 and all-cause mortality was stronger in persons with good glycemic control compared with poor glycemic control (FEV1-FPG interaction, P = 0.01; FEV1-HbA1c interaction, P = 0.03).
Conclusion: Our results showed that FEV1 is a strong predictor of mortality in persons with T2DM. Glycemic status had significantly modified the association between lung function parameters and mortality.

Disclosure
C. Li: None. C. Lin: None. T. Li: None. C. Liu: None. C. Yang: None.
1387-P: Prediabetes Subgroups, Type 2 Diabetes Risk, and Differential Intervention Effects
Authors: CASANOVA RAMON , STAFFORD JEANETTE M. , DEMESIE YITBAREK , JAEGER BYRON C. , WELLS BRIAN J. , BANCKS MICHAEL 
Published: June 2024

Introduction and Objective: Many studies have subclassified T2D with various physiological factors to better understand disease heterogeneity but few have subclassified prediabetes, a period critical to prevention of T2D. We derived prediabetes subgroups and assessed risk for T2D.
Methods: We included 3043 participants from the Diabetes Prevention Program. We used baseline data for 35 clinical variables (table footnote) to compare two clustering methods: 1) kmeans using model statistics to identify the optimal cluster/subgroup number and 2) Uniform Manifold Approximation Projection data reduction with Hierarchical Density Based Spatial Clustering of Applications with Noise (HDBSCAN). We used Cox regression to assess 3-year T2D risk and intervention effects, restricting to 2549 participants randomized to the placebo, metformin, or lifestyle arms (with selection weighting).
Results: Both kmeans and HDBSCAN methods supported two subgroups as optimal. Despite general subgroup similarities between methods (high obesity in subgroup 1), the kmeans subgroups differed more notably in glucose/insulin measures and HDBSCAN subgroups differed in adiposity measures (table). Within clustering method, subgroups differed in both risk for T2D (32% and 88% higher risk, respectively) and intervention effects.
Conclusions: Prediabetes physiological subgrouping may inform T2D risk and targeted prevention strategies.

Disclosure
R. Casanova: None. J.M. Stafford: None. Y. Demesie: None. B.C. Jaeger: None. B.J. Wells: None. M. Bancks: None.

Funding
American Diabetes Association (11-22-ICTSPM-18)
14-PUB: The Effect of Structured Intensive Lifestyle Intervention on Muscle Mass in Patients with Type 2 Diabetes Receiving GLP-1 Receptor Agonists
Authors: AL-BADRI MARWA , ALMASIH BARBAR ASKAR ABD , KHATER ABDELRAHMAN , SALAH TAREQ , DHAVER SHILTON E. , AL-ROOMI FATIMAH , MOTTALIB ADHAM , HAMDY OSAMA 
Published: June 2024

Glucagon-like-peptide-1 receptor agonists (GLP-1RAs) emerged as an important treatment option for type 2 diabetes (T2D) for their dual efficacy in improving glycemia and reducing body weight. However, they significantly reduce fat free mass (FFM), a surrogate for muscle mass, putting patients at a higher risk for sarcopenia and its sequelae. It is unknown whether structured intensive lifestyle intervention (sILI), that includes higher protein intake and strength exercises, can mitigate muscle mass loss with GLP-1RA use. We retrospectively evaluated 53 patients with T2D enrolled in a 12-week multidisciplinary sILI (mean age 58.17±11.3 years; 51% male; weight 104.3±19.7 kg; BMI 36.1±5.6 kg/m2, A1C 7.4±1.3%) and divided them into two groups: group 1, already taking GLP-1RA (n=32), and group 2, not on GLP-1RA (n=21). Both groups were instructed to follow a hypocaloric structured medical nutrition therapy plan with increased protein intake to 1-1.5 gm/kg of adjusted body weight. They were also instructed to exercise for 360 minutes/week with more emphasis on strength exercises. Body composition was analyzed by bioelectrical impedance. At 12 weeks, group 1 lost 7.4±4.5 kg (p&lt;0.001) and group 2 lost 6.2±5.4 kg (p&lt;0.001), and their A1C decreased by 0.84%±1.1% (p&lt;0.001) and by 1%±1.06% (p&lt;0.001) respectively, with no differences between groups over time. Group 1 had no change in FFM compared to baseline while group 2 lost 1.4±2.6 kg (p&lt;0.05). There was no difference in FFM loss between groups over time (p=0.28). Our findings suggest that increasing protein intake and strength exercises, as part of sILI, may mitigate the deleterious effect of GLP-1RA on muscle mass in patients with T2D. These results support recommending an increase in protein intake and incorporation of strength exercises when GLP-1RA is prescribed for patients with T2D to minimize muscle mass loss. Further research is needed to validate these findings in a randomized prospective study.

Disclosure
M. Al-Badri: None. A. Barbar Askar: None. A. Khater: None. T. Salah: None. S.E. Dhaver: None. F. Al-Roomi: None. A. Mottalib: None. O. Hamdy: Research Support; Eli Lilly and Company, Novo Nordisk. Consultant; Abbott Nutrition. Stock/Shareholder; Healthimation. Research Support; Gilead Sciences, Inc. Advisory Panel; Nemaura Medical, Twin Health, L-Nutra Inc.
140-OR: The Coronary Flow Reserve Increase after Dapagliflozin Treatment in Patients with Type 2 Diabetes Is Maintained after Four Years—A Four-Year DAPAHEART Follow-up Study
Authors: MORCIANO CASSANDRA , CINTI FRANCESCA , PIO SORICE GIAN , LECCISOTTI LUCIA , GUGLIANDOLO SHAWN , CAPECE UMBERTO , CAPPANNOLI LUIGI , D'AMARIO DOMENICO , MEZZA TERESA , DI GIUSEPPE GIANFRANCO , CICCARELLI GEA , SOLDOVIERI LAURA , GIACCARI ANDREA 
Published: June 2024

Introduction & Objective: Cardiovascular (CV) outcome trials have shown that in patients with type 2 diabetes (T2D), treatment with sodium-glucose cotransporter-2 inhibitors (SGLT-2i) reduces CV mortality for heart failure. We demonstrated that 4-weeks-treatment with SGLT-2i leads to a 30% increase in coronary flow reserve (CFR) in T2D people with stable coronary artery disease (CAD) (DAPAHEART trial). The aim of this study is to evaluate the long-term effects of treatment with dapagliflozin on CFR in patients with T2D.
Methods: T2D patients with CAD already enrolled for a single-center, 4 weeks, prospective, randomized (1:1 dapagliflozin 10 mg or placebo), double-blind, controlled study have been followed up for 4 years. At the end of the trial all the patients in placebo group started therapy with dapagliflozin. After 4 years of treatment the CFR has been evaluated using 13N-ammonia PET-CT.
Results: During the follow-up, the antidiabetic treatment remained stable. The 2 groups were metabolically well balanced.In DAPA group (n=5), the increase of 30% in CFR was sustained over 4 years (p=ns). A comparison between pre and post-4-years follow-up in DAPA group showed a 35% increase in CFR (p=0.09). The placebo group (n=4), after 4 years of dapagliflozin treatment, exhibited a 28.6% increase in CFR (p=0.07). Overall, a 25% increase in CFR was observed across all patients after 4 years (p=0.008, n=9), along with a reduction in myocardial resting blood flow (p=0.002, n=9) as observed in the DAPAHEART trial.
Conclusions: This 4-years follow up trial demonstrates that the 30% increase of CFR obtained after 4 weeks treatment is maintained after 4 years, confirming the previous published results in a new population. This improvement in CFR may have important implications on the management and prognosis of patients with T2D and CAD.
Keywords: Coronary Flow Reserve, SGLT2i, Dapagliflozin, Type 2 Diabetes, Coronary Artery Disease, Long-Term.

Disclosure
C. Morciano: None. F. Cinti: None. G. Sorice: None. L. Leccisotti: None. S. Gugliandolo: None. U. Capece: None. L. Cappannoli: None. D. D'amario: None. T. Mezza: None. G. Di Giuseppe: None. G. Ciccarelli: None. L. Soldovieri: None. A. Giaccari: None.