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Abstract Background The current EULAR definition of difficult-to-treat rheumatoid arthritis (D2T-RA) identifies patients with active disease refractory to multiple treatments at a single time point, without considering the persistence of this condition over time. The study aimed to assess difficult-to-treat rheumatoid arthritis (D2T-RA) over 12 months, considering persistence over time rather than a single time point, in a real-life cohort. Methods In a single-center real-life cohort, demographic and clinic data were cross-sectionally collected for each patient at baseline and retrospectively over the previous 12 months bimonthly. For each timepoint, the prevalence of D2T-RA patients was calculated, and patients meeting the EULAR definition for at least 6 months were defined as persistent D2T-RA (pD2T-RA). Finally, the clinical characteristics associated with the time-based definition of pD2T-RA were analyzed. Results Among 610 adult RA patients, 104 were refractory to ≥ 2 treatments. Initially, 41.3% met D2T-RA criteria, but only 27.9% fulfilled persistent D2T-RA (pD2T-RA) criteria over 6 months. The pD2T-RA group was associated with male gender, higher HAQ and Charlson Comorbidity Index scores, more failed treatments, and use of non-NSAID analgesics. Logistic regression linked pD2T-RA to higher SDAI and CRP values, and the use of glucocorticoids or analgesics. Chronic use of glucocorticoids was strongly associated with pD2T-RA. Conclusions The application of a temporal criterion allowed for the selection of a subgroup of pD2T-RA patients who differ from those who meet the definition of D2T-RA only episodically. Chronic use of glucocorticoids was the factor most strongly associated with pD2T-RA status.

In metastatic breast cancer (MBC), blood is a source of circulating tumor cells (CTCs). CTCs may serve as a ‘‘real-time liquid biopsy” as they represent metastatic tumor genetics better than primary tumor. PIK3CA is one of the most important oncogenes in treatment-unresponsive breast cancers. The aim of this study was to detect PIK3CA mutations and hereditary cancer variants in CTCs from MBC patients. Forty-seven blood samples were obtained from 20 MBC patients from at least 1/3 consecutive time points. CTCs were quantified using the CellSearch system and isolated from 11/20 patients with ≥5/7.5 ml CTCs (14/47 blood samples) using the DEPArray system. DNA was extracted and amplified to perform Sanger sequencing on PIK3CA gene. Sequencing revealed a pathogenic PIK3CA mutation in 2/11 (18 %) cases. Subsequently, we evaluated a 26-target hereditary gene panel by Next Generation Sequencing and identified a concomitant pathogenic mutation in the TP53 gene in a patient with a PIK3CA mutation. No pathogenic germline variants were found. Our data support the conclusion that CTCs analysis may be used to identify mutations in patients to identify those more likely to metastasize.

Neutron detectors are essential across disciplines such as fundamental science, nuclear security, safeguards, and civilian applications. While 3He-filled gas proportional counters have long been revered for their efficacy in detecting thermal neutrons and praised for their efficiency, neutron/gamma discrimination, and stability, the scarcity of 3He has spurred a search for alternatives. Here, we explore a solid structured scintillating particle composite (SPC) consisting of 6Li-containing scintillating glass particles within an acrylic matrix as a neutron detector for high dynamic range applications. We show for the first time that an SPC neutron detector can boast an intrinsic detection efficiency of 0.261% for pure 252Cf fission neutrons and an overall neutron detection efficiency of (0.546 ± 0.003)% at the Neutron Free-in-Air facility while being able to function in an intense gamma-ray environment. We also show that the SPC neutron detector supports fast neutron capture times and enables a dual-readout scheme that extends the detector dynamic range to high incident neutron fluxes. A scalable fabrication process allows for tailoring the SPC detector properties to the requirements of specific applications. Good agreement is found between the experimental results taken with a National Institute of Standards and Technology traceable 252Cf source and the coupled MCNP6 and optical-ray-tracing simulations. [ABSTRACT FROM AUTHOR]

Somatostatin receptor type 2 (SSTR2) is one of the five subtypes of somatostatin receptors and is overexpressed on the surface of most gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs), pituitary tumors, paraganglioma, and meningioma, as well as hepatocellular carcinoma and breast cancer. Chimeric antigen receptor (CAR) T-cells are genetically engineered to express an artificial, T-cell activating binder, leading upon ligation to biocidal activity against target-antigen expressing cells. Adaptor-CAR T-cells recognize, via the CAR, a tag on an antigen-binding molecule, building an activating bridge between the CAR and the target cell. We hypothesized that a novel fluorescent-peptide antagonist of SSTR2, called Octo-Fluo, in combination with anti-FITC adaptor CAR (AdFITC(E2)-CAR) T-cells, may function as an on-off tunable activating bridge between the CAR and SSTR2 expressing target cells. In vitro studies confirmed the binding of Octo-Fluo to Bon1-SSTR2 mCherry-Luc cells without evidence of internalization. AdFITC(E2)-CAR T-cells were activated and efficiently induced Bon1-SSTR2 cell death in vitro, in an Octo-Fluo concentration-dependent manner. Similarly, AdFITC(E2)-CAR T-cells in combination with Octo-Fluo efficiently infiltrated the tumor and eliminated Bon1-SSTR2 tumors in immunodeficient mice in therapeutic settings. Both, AdFITC(E2)-CAR T-cell tumor infiltration and biocidal activity were Octo-Fluo concentration-dependent, with high doses of Octo-Fluo, saturating both the CAR and the SSTR2 antigen independently, leading to the loss of tumor infiltration and biocidal activity due to the loss of bridge formation. Our findings demonstrate the potential of using AdFITC(E2)-CAR T-cells with Octo-Fluo as a versatile, on-off tunable bispecific adaptor for targeted CAR T-cell immunotherapy against SSTR2-positive NETs.

ABSTRACTWe present the geomorphological map of the upper sector of the Roncovetro active landslide (Enza Valley, Emilia-Romagna, Italy). The 1:1500 scale map provides an accurate picture of the landslide in October 2014. The map is mainly based on the data collected during an airborne LiDAR survey. The capability of LiDAR to ‘penetrate’ the vegetation cover makes these data the most complete and accurate topographic dataset of this landslide. The map shows that the upper sector of the Roncovetro landslide consists of gravity- and water runoff-related forms. Gravitational features are linked to sliding and flowing movements that characterize the short- and long-term behaviour of the landslide. By comparing the 2014 LiDAR-Digital Elevation Model (DEM) with the 1973 DEM provided by the Emilia-Romagna Region, we calculated that 6.2 ± 0.8 × 105 m3 of material has moved from the top of the Roncovetro landslide in about 40 years.

ObjectivesAn increased number of elderly individuals affected by rheumatoid arthritis (RA) has been reported, including both patients with RA onset in advanced age and patients aged with the disease. In this registry-based study, we aimed to analyze the retention rate and cause of discontinuation of biologic (b) and targeted synthetic (ts)-disease-modifying anti-rheumatic drugs (DMARDs) in RA patients over 65 year old.MethodsRA patients enrolled in the Italian GISEA registry and starting a b- or a ts-DMARD over 65 years of age were included. Demographic, clinical, serologic, and therapeutic features were collected.ResultsA total of 1,221 elderly RA patients were analyzed (mean age 71.6 ± 5.2 years). RA was diagnosed before 65 years in 72.5% of cases, a 60.6% of patients experienced a previous b- or ts-DMARD. In patients older than 65 initiating a new b- or ts-DMARDS, tumor necrosis factor alpha inhibitors (TNFi) were prescribed in 29.6% of patients, abatacept in 24.8%, anti-interleukin 6 receptor antagonists (anti-IL6R) in 16.3%, Janus kinases inhibitors (JAKi) in 24.9%, and rituximab in 4.4%. The main causes of discontinuation were primary or secondary inadequate responses (66.1%). The median retention rate for all treatments was 181.3 weeks. A statistically higher retention rate was observed for abatacept when compared to TNFi (p = 0.02), JAKi (p

Brain-computer interfaces (BCIs) are a cutting-edge neurotechnology that allows direct interaction between the neural system and external electronic systems. Over the past decade, the field of BCI has witnessed far-reaching promises and expectations, especially regarding the merging of humans and machines. Drawing from the STS literature analysing the relationship between technological innovation and representations of the future, the paper looks at the field of BCIs and at the related expert-scientific debate as a discursive arena where particular visions of cyborg are enacted. Through the notion of visions, representations of the future and discourses of BCIs are explored and analysed within the scholarly literature. Whilst the future of these technologies is usually approached through the question: “Are we all going to become cyborgs?”, the question addressed in this contribution is the following: “Which kind of cyborgs are enacted here?”. The findings reveal two visions of cyborg; the first considers the subject’s intentionality as a key element in steering the human-machine interaction, while the second looks at human-machine entanglement as a machine adaptation that takes place beyond the subject’s intentionality. A detailed analysis also shows how these visions are enacted as assemblages of different discursive repertoires and associations mediating and shaping specific cyborg visions.

Abstract Passive Gamma Emission Tomography (PGET) has been developed by the International Atomic Energy Agency to directly image the spatial distribution of individual fuel pins in a spent nuclear fuel assembly and determine potential diversion. The analysis and interpretation of PGET measurements rely on the availability of comprehensive datasets. Experimental data are expensive and limited, so Monte Carlo simulations are used to augment them. However, Monte Carlo simulations have a high computational cost to simulate the 360 angular views of the tomography. Similar challenges pervade numerical science. With the aim to create a large dataset of PGET simulated scenarios, we addressed the computational cost of Monte Carlo simulations by developing a physics-aware reduced order modeling approach. This approach combines a small subset of the 360 angular views (limited views approach) with a computationally inexpensive proxy solution (real-time forward model) that brings the essence of the physics to obtain a real-time high-fidelity solution at all angular views but at a fraction of the computational cost. The method’s ability to reconstruct 360 views with accuracy from a limited set of angular views is demonstrated by testing its performance for different types of reactor fuel assemblies.