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Answer set programming (ASP) has been applied fruitfully to a wide range of areas in AI and in other fields, both in academia and in industry, thanks to the expressive representation languages of ASP and the continuous improvement of ASP solvers. We present some of these ASP applications, in particular, in knowledge representation and reasoning, robotics, bioinformatics, and computational biology as well as some industrial applications. We discuss the challenges addressed by ASP in these applications and emphasize the strengths of ASP as a useful AI paradigm.

Purpose of ReviewIn the last decade many studies have suggested an association between the altered gut microbiota and multiple systemic diseases including diabetes. In this review, we will discuss potential pathophysiological mechanisms, the latest findings regarding the mechanisms linking gut dysbiosis and type 2 diabetes (T2D), and the results obtained with experimental modulation of microbiota.Recent FindingsIn T2D, gut dysbiosis contributes to onset and maintenance of insulin resistance. Different strategies that reduce dysbiosis can improve glycemic control.SummaryEvidence in animals and humans reveals differences between the gut microbial composition in healthy individuals and those with T2D. Changes in the intestinal ecosystem could cause inflammation, alter intestinal permeability, and modulate metabolism of bile acids, short-chain fatty acids and metabolites that act synergistically on metabolic regulation systems contributing to insulin resistance. Interventions that restore equilibrium in the gut appear to have beneficial effects and improve glycemic control. Future research should examine in detail and in larger studies other possible pathophysiological mechanisms to identify specific pathways modulated by microbiota modulation and identify new potential therapeutic targets.

Background The diabetic foot ulcer (DFU) is one of the most prevalent complications of diabetes mellitus and often develops severe effects that can lead to amputation. A non-healing “minor” amputation often precedes a major amputation resulting in a negative impact on the function and quality of life of the patients. Stem cell-based therapies have emerged as a promising option to improve healing, and the adipose tissue is an abundant and easy to access source. The injection of autologous micro-fragmented adipose tissue at the amputation stump of a diabetic population undergoing a lower limb minor amputation was evaluated and compared with the standard care. Methods In this randomized controlled trial with two arms (parallel assignment) and no masking, 114 patients undergoing a lower limb minor amputation were randomized to standard of care or to micro-fragmented adipose tissue injection prepared using a minimal manipulation technique (Lipogems®) in a closed system. Clinical outcomes were determined monthly up to 6 months. Primary endpoint of the study was the evaluation of the healing rate and time after the minor amputation. Secondary endpoints included the assessment of safety, feasibility, technical success, relapse rate, skin tropism, and intensity of pain. Results At 6 months, 80% of the micro-fragmented adipose tissue-treated feet healed and 20% failed as compared with the control group where 46% healed and 54% failed ( p  = 0.0064). No treatment-related adverse events nor relapses were documented, and technical success was achieved in all cases. The skin tropism was improved in the treatment group, and the pain scale did not differ between the two groups. Conclusion The results of this randomized controlled trial suggest that the local injection of autologous micro-fragmented adipose tissue is a safe and valid therapeutic option able to improve healing rate following minor amputations of irreversible DFU. The technique overcomes several stem cell therapy-related criticisms and its potential in wound care should be better evaluated and the therapeutic indications could be expanded. Trial registration ClinicalTrials.gov number: NCT03276312 . Date of registration: September 8, 2017 (retrospectively registered).

Answer Set Programming (ASP) is a popular logic programming paradigm that has been applied for solving a variety of complex problems. Among the most challenging real-world applications of ASP are two industrial problems defined by Siemens: the Partner Units Problem (PUP) and the Combined Configuration Problem (CCP). The hardest instances of PUP and CCP are out of reach for state-of-the-art ASP solvers. Experiments show that the performance of ASP solvers could be significantly improved by embedding domain-specific heuristics, but a proper effective integration of such criteria in off-the-shelf ASP implementations is not obvious. In this paper the combination of ASP and domain-specific heuristics is studied with the goal of effectively solving real-world problem instances of PUP and CCP. As a byproduct of this activity, the ASP solver wasp was extended with an interface that eases embedding new external heuristics in the solver. The evaluation shows that our domain-heuristic-driven ASP solver finds solutions for all the real-world instances of PUP and CCP ever provided by Siemens.

In the last few years, we have witnessed the spread of computing devices getting smaller and smaller (e.g., Smartphones, Smart Devices, Raspberry, etc.), and the production and availability of data getting bigger and bigger. This work presents DLV-EE, a framework based on Answer Set Programming (ASP) for performing declarative reasoning tasks over data-intensive, distributed applications. It relies on the DLV2 system and it features interoperability means for dealing with Big-Data over modern industry-level databases (relational and NoSQL). Furthermore, the work introduces DLV-IoT, an ASP system compatible with “mobile” technologies for enabling advanced reasoning capabilities on smart/IoT devices; eventually, DLV-EE and DLV-IoT via some real-world applications are illustrated as well.

Background: Although endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) using lumen-apposing metal stents (LAMS) has become one of the treatments of choice for acute cholecystitis (AC) in fragile patients, scant data are available on real-life settings and long-term outcomes. Methods: We performed a multicenter retrospective study including EUS-guided GBD using LAMS for AC in 19 Italian centers from June 2014 to July 2020. The primary outcomes were technical and clinical success, and the secondary outcomes were the rate of adverse events (AE) and long-term follow-up. Results: In total, 116 patients (48.3% female) were included, with a mean age of 82.7 ± 11 years. LAMS were placed, transgastric in 44.8% of cases, transduodenal in 53.3% and transjejunal in 1.7%, in patients with altered anatomy. Technical success was achieved in 94% and clinical success in 87.1% of cases. The mean follow-up was 309 days. AEs occurred in 12/116 pts (10.3%); 8/12 were intraprocedural, while 1 was classified as early (<15 days) and 3 as delayed (>15 days). According to the ASGE lexicon, two (16.7%) were mild, three (25%) were moderate, and seven (58.3%) were severe. No fatal AEs occurred. In subgroup analysis of 40 patients with a follow-up longer than one year, no recurrence of AC was observed. Conclusions: EUS-GBD had high technical and clinical success rates, despite the non-negligible rate of AEs, thus representing an effective treatment option for fragile patients.

Standardization of solver input languages has been a main driver for the growth of several areas within knowledge representation and reasoning, fostering the exploitation in actual applications. In this document, we present the ASP-CORE-2 standard input language for Answer Set Programming, which has been adopted in ASP Competition events since 2013.

Answer set programming is a declarative problem‐solving paradigm that rests upon a work flow involving modeling, grounding, and solving. While the former is described by Gebser and Schaub (2016), we focus here on key issues in grounding, or how to systematically replace object variables by ground terms in an effective way, and solving, or how to compute the answer sets, of a propositional logic program obtained by grounding.

Diabetic foot ulcers (DFUs) are severe complications of diabetes that often lead to major amputations. Despite care advancements, approximately 50% of minor amputations do not heal, resulting in major amputations and increased mortality. This study evaluated the effectiveness of adipose‐derived stem cells (ASCs) obtained through superficial enhanced fluid fat injection (SEFFI) in improving healing rates after minor amputations in DFUs. It was a prospective, single‐arm, observational cohort study. The patients were monitored for half a year using monthly assessments. The primary endpoint was the healing rate of the amputation stumps after minor amputations coupled with ASC injections. Secondary endpoints included safety, feasibility, adverse events and analysis of variables associated with healing including the analysis of the injected mesenchymal adipose stem cell populations. Of the 256 screened patients, 40 were enrolled. At 6 months, 55% of the treated stumps had healed completely. The median healing time was 69 days. Technical success was achieved in all cases without device‐related complications. Multivariable Cox models identified haemodialysis, opioid use and the injected number of CD45‐positive cells as risk factors for healing failure. CD73 expression was positively associated with healing. The SEFFIDiFA trial demonstrated a promising 69% healing probability at 6 months post‐amputation. This minimally invasive approach showed a higher healing rate with fewer complications. This study supports the potential of ASCs in enhancing wound healing in DFUs and highlights the importance of CD73 expression for successful outcomes. Further research is warranted to validate these findings and optimise the technique.

Purpose The optimal treatment strategy of patients affected by colorectal cancer (CRC) with synchronous unresectable liver metastases (SULM) is at present undefined. It is not known if a palliative primary tumor resection followed by chemotherapy could have a survival benefit compared to upfront chemotherapy (CT). The aim of the study is to analyze the safety and effectiveness of both therapeutic strategies in a group of patients treated at one institution. Methods A prospectively collected database was queried for patients affected by colorectal cancer with synchronous unresectable liver metastases between January 2004 and December 2018, defining and comparing 2 groups: patients treated by chemotherapy alone (group 1) vs patients who underwent primary tumor resection with or without a first line chemotherapy (group 2). The primary end point was Overall Survival (OS), estimated by the Kaplan–Meier method. Results One hundred sixty-seven patients were included: 52 in group 1 and 115 in group 2, median follow-up 48 months (range 25–126). A difference of 14 months in overall survival was observed between group 2 compared to group 1 (28 vs 14 months respectively; p  < 0.001). Furthermore, overall survival increased in patients who underwent liver metastases resection ( p  < 0.001) or percutaneous radiofrequency ablation after surgery ( p  < 0.001). Conclusion With the limits of a retrospective analysis, the study shows that surgical resection of the primary tumor has a significant impact on survival compared to chemotherapy alone. Randomized controlled trials are needed to confirm these data.