Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning

The aim of this work is to develop an application for autonomous landing. We exploit the properties of Deep Reinforcement Learning and Transfer Learning, in order to tackle the problem of planetary landing on unknown or barely-known extra-terrestrial environments by learning good-performing policies, which are transferable from the training environment to other, new environments, without losing optimality. To this end, we model a real-physics simulator, by means of the Bullet/PyBullet library, composed by a lander, defined through the standard ROS/URDF framework and realistic 3D terrain models, for which we adapt official NASA 3D meshes, reconstructed from the data retrieved during missions. Where such model were not available, we reconstruct the terrain from mission imagery - generally SAR imagery. In this setup, we train a Deep Reinforcement Learning model - using DDPG - to autonomous land on the lunar environment. Moreover, we perform transfer learning on the Mars and Titan environment. While still preliminary, our results show that DDPG can learn a good landing policy, which can be transferred to other environments

Deep Reinforcement Learning for Pin-Point Autonomous Lunar Landing: Trajectory Recalculation for Obstacle Avoidance

This work aims to present a method to perform autonomous precision landing—pin-point landing—on a planetary environment and perform trajectory recalculation for fault recovery where necessary. In order to achieve this, we choose to implement a Deep Reinforcement Learning—DRL—algorithm, i.e. the Soft Actor-Critic—SAC—architecture. In particular, we select the lunar environment for our experiments, which we perform in a simulated environment, exploiting a real-physics simulator modeled by means of the Bullet/PyBullet physical engine. We show that the SAC algorithm can learn an effective policy for precision landing and trajectory recalculation if fault recovery is made necessary—e.g. for obstacle avoidance

GTF2I mutations are common in thymic epithelial tumors but not in hematological malignancies

Background: Mutation of general transcription factor IIi (GTF2I) (chromosome 7 c.74146970T>A) is common in thymic epithelial tumors and is a candidate driver aberration for cancer growth. To our knowledge, this mutation has not been described in other diseases. We evaluated the presence of GTF2I mutation in hematological malignancies. Materials and Methods: We sequenced samples from 31 patients with acute leukemia, 29 with chronic leukemia and 12 with myelodysplastic syndrome. The genomic fragment of exon 15 containing the hotspot of mutation was amplified using polymerase chain reaction (PCR) and sequenced. Results: We did not identify any GTF2I mutation in patients with hematological malignancies. Conclusion: Even though our sample size was limited, our data and reports from the literature suggest that GTF2I mutation is not present or is uncommon in these diseases

A Moon Optical Navigation Robotic Facility on Simulated TERrain: MONSTER

This work presents MONSTER, a Moon optical navigation robotic facility on simulated terrain, i.e., an experimental facility that can be used to simulate lunar navigation problems. The facility consists of a 3D Cartesian manipulator that, once fully operative, will be equipped with a spherical joint allowing to simulate both attitude and orbital dynamics. All the experiments that have been performed so far and are planned to be performed in the future are based on innovative and disruptive approaches using artificial intelligence (AI) algorithms. Indeed, a crater detection algorithm based on a fully convolutional neural network has been implemented, and a reinforcement learning approach is under development for prescribing the control policy of the simulated system. MONSTER enables hardware-in-the-loop simulations of landers and spacecrafts using AI hardware accelerators such a graphics processing unit (GPU), visual processing unit (VPU) and field programmable gate arrays (FPGA)

Defining TCRγδ lymphoproliferative disorders by combined immunophenotypic and molecular evaluation

Tγδ large granular lymphocyte leukemia (Tγδ LGLL) is a rare lymphoproliferative disease, scantily described in literature. A deep-analysis, in an initial cohort of 9 Tγδ LGLL compared to 23 healthy controls, shows that Tγδ LGLL dominant clonotypes are mainly public and exhibit different V-(D)-J γ/δ usage between patients with symptomatic and indolent Tγδ neoplasm. Moreover, some clonotypes share the same rearranged sequence. Data obtained in an enlarged cohort (n = 36) indicate the importance of a combined evaluation of immunophenotype and STAT mutational profile for the correct management of patients with Tγδ cell expansions. In fact, we observe an association between Vδ2/Vγ9 clonality and indolent course, while Vδ2/Vγ9 negativity correlates with symptomatic disease. Moreover, the 7 patients with STAT3 mutations have neutropenia and a CD56-/Vδ2- phenotype, and the 3 cases with STAT5B mutations display an asymptomatic clinical course and CD56/Vδ2 expression. All these data indicate that biological characterization is needed for Tγδ-cell neoplasm definition

Polycomb genes are associated with response to imatinib in chronic myeloid leukemia.

Aim: Imatinib is a tyrosine kinase inhibitor that has revolutionized the treatment of chronic myeloid leukemia (CML). Despite its efficacy, about a third of patients discontinue the treatment due to therapy failure or intolerance. The rational identification of patients less likely to respond to imatinib would be of paramount clinical relevance. We have shown that transmembrane transporter hOCT1 genotyping predicts imatinib activity. In parallel, Polycomb group genes (PcGs) are epigenetic repressors implicated in CML progression and in therapy resistance. Patients & methods: We measured the expression of eight PcGs in paired pre- and post-imatinib bone marrow samples from 30 CML patients. Results: BMI1, PHC3, CBX6 and CBX7 expression was significantly increased during imatinib treatment. Post-treatment levels of CBX6 and CBX7 predicted 3-month response rate. Measurement of post-treatment BMI1 levels improved the predictive power of hOCT1 genotyping. Conclusion: These results suggest that the expression levels of PcGs might be useful for a more accurate risk stratification of CML patients

LOW RPS14 EXPRESSION IS FREQUENTLY FOUND IN NON-5Q-MYELODYSPLASTIC SYNDROMES

Background and aim: The RPS14 gene, located on chromosome 5 and involved in the ribosomal protein synthesis, has been reported as a causal factor in the 5q- syndrome, where its up-regulation during treatment with lenalidomide has been associated with best responses. RPS14 expression in non-5q-MDS was reported in 53%-71% of cases. Interestingly, in low and intermediate-1 IPSS subgroups, patients with lower RPS14 expression had longer OS. Thus, the aim of this study was to assess the RPS14 expression in a larger series of non-5q- MDS patients. Patients and methods: A total of 112 patients, 45% females and 55% males, with a median age of 71-year (range 19-89), were enrolled in 5 different Italian institutions from March 2010 to October 2014. Nine patients were affected by CMMoL; the prognosis of the remaining 103 cases was determined according to the IPSS in low (36%), intermediate-1 (31%), intermediate-2 (21%), and high risk (12%). About 40% of cases were affected by RCMD, 24% by RAEB-2,and 13% by RA. Twelve bone marrow samples from healthy donors have been used as normal references. Results: In healthy donors, the mean RPS14 expression was 0.94±0.26; in the whole MDS series, it was 0.57±0.42. In comparison with healthy controls, the 52% of MDS cases showed lower RPS14 expression levels: 79% in the RA, 56% in the RAEB1, 44% in the RAEB-2, and 41% in the RCMD subgroups. When patients were stratified according to the IPSS, in the half of the low, intermediate-1 and intermediate-2 cases RPS14 was under-expressed, opposite to one third of the high risk and 13% of the CMMoL patients only. No relationships with age or sex were observed. To evaluate if the haploinsufficiency would be responsible of the low expression of RPS14 gene, we performed the copy number assay on 32 MDS, 15 healthy donors, and 3 patients with 5qsyndrome: in 91% of cases the copy number assay excluded the haploinsufficiency. Conclusions: Our study showed in a large series of patients that a lower RPS14 expression interests the half of the non-5q- cases, especially those affected by RA and at low and intermediate IPSS risk. Other authors previously reported that low expression of RPS14 was not due to promoter hypermethylation. Here we demonstrated that also the haploinsufficience is not the cause of the RPS14 low expression. Moreover, our findings suggest a possible role for lenalidomide in non-5q- MDS, especially in low risk patients

The c.480C>G polymorphism of hOCT1 influences imatinib clearance in patients affected by chronic myeloid leukemia.

The aim of the study was to investigate any possible influence of polymorphisms of transmembrane transporters human organic cation transporter 1 (hOCT1), ABCB1, ABCG2 on imatinib pharmacokinetics in 33 men and 27 women (median age and range, 56 and 27-79 years, respectively) affected by chronic myeloid leukemia. A population pharmacokinetic analysis was performed to investigate imatinib disposition in every patient and the role of transporter polymorphisms. Results showed that the α1-acid glycoprotein and the c.480C>G genotype of hOCT1 had a significant effect on apparent drug clearance (CL/F) being responsible, respectively, for a 20% and 10% decrease in interindividual variability (IIV) of CL/F (from 50.1 up to 19.6%). Interestingly, 25 patients carrying at least one polymorphic c.480 G allele had a significant lower CL/F value with respect to the 35 c.480CC individuals (mean±s.d., 9.6±1.6 vs 12.1±2.3 l h(-1), respectively; PG SNP may significantly influence imatinib pharmacokinetics, supporting further analyses in larger groups of patients