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A new three-axis loading frame has been developed to enable real-time visualization of in-situ soil and rock structure interactions via X-ray tomography during small-scale model testing. The constructed frame is capable of performing a wide range of small-scale 1gtests and can accommodate monotonic and cyclic actuation under both load and displacement control. The compact size of the system enables remote multi-axis operation from within an X-ray cone-beam scanning bay, a capability which is owed to a comprehensive design process. Design and fabrication involved a blend of physical and numerical experiments to assess suitable construction materials and performance. In this scope, the new equipment is discussed and its capability is showcased.

In recent years, synthetic lethality has been recognized as a solid paradigm for anticancer therapies. The discovery of a growing number of synthetic lethal targets has led to a significant expansion in the use of synthetic lethality, far beyond poly(ADP-ribose) polymerase inhibitors used to treat BRCA1/2-defective tumors. In particular, molecular targets within DNA damage response have provided a source of inhibitors that have rapidly reached clinical trials. This Perspective focuses on the most recent progress in synthetic lethal targets and their inhibitors, within and beyond the DNA damage response, describing their design and associated therapeutic strategies. We will conclude by discussing the current challenges and new opportunities for this promising field of research, to stimulate discussion in the medicinal chemistry community, allowing the investigation of synthetic lethality to reach its full potential.

The demand for free-form steel structures having improved performances, reducing labour and resource usage is increasing in the construction sector. Structural nodes are some of the most critical regions for steel structures characterised often by large dimensions. These nodes can exploit the geometrical freedom of metal additive manufacturing (MAM) processes. Laser powder bed fusion (LPBF) is arguably the most developed MAM process, which has limitations regarding the size of the parts to be produced. A way to overcome the size limits of LPBF for producing structural nodes while still exploiting its geometrical capacity is producing hybrid components by welding them to traditionally manufactured beams. Such hybrid joints would constitute a complex system from a mechanical design perspective requiring a systematic analysis in order to be certified for structural use. Accordingly, this work studies the mechanical behaviour of hybrid steel components generated by welding LPBF plates and quarto plates made of AISI 316L stainless steel. The work was guided by a case study based on a large steel node, which helped defining the requirements to fill the gap of the international standards. The mechanical characterisation of LPBF-produced plates and quarto plates, as well as the welded hybrid components revealed a maximum of 10% difference between the properties of the differently manufactured plates. Through the digital image correlation (DIC) analyses, the anisotropic deformation behaviour along the LPBF, weld seam, and quarto plate regions have been identified, and the properties after welding did not show relevant modifications. The tests allowed to define that the failure behaviour is mainly governed by interlayer bounds, and a 0.9 safety reduction parameter for considering the reduction of ductility induced by arc welding to LPBF. Finally, design and production suggestions have been provided for a correct evaluation of gross and effective sections of the designed nodes.

The combined manufacturing approach has the potential to facilitate large-scale manufacturing processes, enable on-site manufacturing, and limit welding and joining processes currently used to create complex and flexible components. Laser Metal Wire Deposition (W-LMD) has emerged as a highly promising technology in the field of additive manufacturing (AM). The use of wire feedstock as a cost-effective and safe alternative to powder ensures optimal productivity and meets the demands of the industry. W-LMD would be employed in combined manufacturing for the repair of existing components or the incorporation of intricate features into existing components, thereby facilitating the integration of additive manufacturing across a range of sectors. Nevertheless, an investigation is necessary to determine whether the inherent AM process-related defect or inhomogeneity affects the performance of the hybrid components in question. This study examines the microstructural and mechanical performance of hybrid W-LMD components in continuous, interrupted, and combined manufacturing scenarios. The results demonstrated that the process development strategy is of vital in the production of fully consolidated components (density > 99.9%) for a stable process, irrespective of the deposition scenarios. The tensile properties varied with the process conditions, emphasizing the importance of considering deposition conditions for heat-sensitive alloys in combined manufacturing. The findings aim to provide valuable insights applicable to the production of real industrial components using W-LMD.

Ti-5Al-5V-5Mo-3Cr (Ti-5553) alloy is increasingly used in structural airplane components, such as landing gear and fuselage, thanks to its high strength, good ductility, and low density. These components are consistently subjected to sub-zero temperatures during the flight. In this study, pulsed laser powder bed fusion (L-PBF) parameters were firstly optimized to fabricate highly dense (>99%) parts, and their effect on microstructure and microhardness was analyzed. Finally, tensile properties were evaluated under sub-zero temperature conditions and compared to the standard room ones to validate the feasibility of using Ti5553 under low-temperature environments.

Next-generation fiber laser sources can dynamically combine Gaussian beams with ring distributions within the source. The irradiance manipulation may add flexibility to the Laser Powder Bed Fusion process, for instance to control microstructure or surface roughness. However, their use is limited by a lack of studies revealing how beam shaping can be exploited in a reproducible manner. Accordingly, this work shows the use of novel beam profiles provided by a multi-core fiber laser source in the LPBF of AlSi7Mg0.6. Irradiance profiles were characterized, then large experiments were conducted to investigate their effect on surface roughness and microstructure of produced parts.

The design of temperature controllers is impaired by the limited accuracy of the models employed for thermal systems, which are commonly estimated from uninformative data, such as step responses, due to the restrictive experimental design connected to the long duration of the experiments. This paper focuses on modelling an industrial convection oven following different rationales. Three continuous-time models are proposed and compared: a grey-box parametric thermal network model, a black-box parametric first order lag plus time delay model, and a black-box non-parametric model based on reproducing kernel Hilbert spaces. These are all estimated and validated on step response experimental data. Lastly, the pros and cons of each model are highlighted.

This paper presents a lumped-parameter grey-box sampled-data state-space model for the industrial oven of a shrink tunnel. The model is derived following the thermal-electrical analogy. A novel discretization strategy is developed to take into account that the sampling time of the system is equal to the lowest period of the pulse-width-modulated voltage signals which drive the heat resistors of the industrial oven. The model parameters are estimated by means of an extensive experimental campaign. Experimental results show that the derived model outperforms state-of-the-art transfer-function models while depending on fewer parameters.

Shrink tunnels are machines composed of an industrial oven and a conveyor belt; they are widely used in manufacturing applications for polymeric packaging. Manufacturing products are wrapped in a thin plastic film and inserted into the oven via the conveyor belt. The heat shrinks the plastic around the products, creating the pack. This paper presents a model-based temperature control architecture that tackles numerous goals: setpoint tracking in the presence of manual-automatic transitions, demanding disturbance rejection requirements, energy saving, and actuator limitations. The performances of the control architecture are experimentally validated on a workbench, highlighting its effectiveness in satisfying the specifications.

Despite the advantages of laser powder bed fusion (LPBF), part defects may arise from inaccurately chosen process parameters or heat accumulation during the scanning of complex geometries. Amongst different monitored entities the chemistry or the process fingerprints related to the material requires further attention. Monitoring the spectral content of light emitted from the laser-material interaction provides insight into thermal conditions and chemical composition of the processed material. This work implements an off-axial spectral monitoring setup for Optical Emission Spectroscopy (OES) in LPBF. Single-point experiment was conducted on AISI316L and Ti-6Al-4V. The study showed that the variation of laser energy input causes consequent variation of spectral emission intensity, as well as that the developed setup successfully captures spectral peaks of alloying elements. Principal Component Analysis demonstrated clear differentiation between the two materials. These findings prove the potential of OES for monitoring alloying elements of processed material and processing conditions in LPBF.

Remote laser welding is typically exploited for the joining of hairpin couples for the manufacturing of electric drives. Laser welding of copper hairpins poses several challenges due to the high optical reflectivity and elevated thermal conductivity of the material. Moreover, the welding operation is required to be clean, since it is carried out in a sub-assembly of the electric drive. The contemporary laser systems provide numerous possibilities for the welding process in terms of beam shapes and wavelengths. Hence, comparative analyses with well-defined criteria and protocols are required to assess the available technologies. Accordingly, this work illustrates the benchmarking of different laser welding systems in terms the mechanical strength and the process cleanliness during the welding Cu hairpins. Moreover, the monitoring approaches are described to ensure quality in a broad and distributed production environment. Additionally, mid-fidelity simulation is proposed to address the rapid selection between different beam solutions. The results of the presented framework presented are used to infer future beam configurations.

Electromobility applications require several welded connections using demanding materials often in dissimilar combinations. Copper, aluminium, or steel alloys are laser welded for energy storage and traction related components. On the one hand, high power fiber laser sources provide in-source beam shaping solutions able to modify the irradiance profile towards ring-shaped beams. On the other hand, research focused on the effect of the beam shapes on the melting mechanisms and process quality is still in progress. This work studies the effect of different beam profiles on AISI301LN, AA6082 and pure Cu with a 5 kW fiber laser. Linear trends of power over penetration depth as a function of speed confirms the validity of employing the lumped heat capacity model for ring-shaped beams. Moreover, the specific melting fluence is observed to exhibit an exponential decaying trend with the proportion of power allocated in the fiber core, irrespective of tested material.

Real-time defects’ estimation and control of the cut quality through the coaxial camera monitoring of the kerf are amongst the most promising developments for laser cutting. In industrial systems, sheets are positioned on a metallic grid creating discontinuities in the cutting process due to unpredictable thickness, blown and resolidified material and the time varying position of the grid. The interaction between laser radiation escaping from the kerf and the grid, along with the difficult outflow of molten material, causes changes in the process emission images. These changes influence the defect estimation approach, and, consequently, the control action. In this work, a real-time grid identification and classification-based machine learning algorithm was developed and tested during the fusion cutting of 6 mm thick Al5754, exploiting a NIR coaxial monitoring system. Real-time control experiments with dross estimates were performed, demonstrating a correct identification of the grid and highlighting a feasible industrial application.

In fusion laser cutting of intricate geometries, the processing speed often varies significantly from its nominal value due to inherent machine dynamics. These variations can lead to excessive energetic input and drifts from the reference cut quality. To address defect formation during transient conditions, a conventional approach involves power reduction to compensate for speed variations. This help prevent thermal imbalances and material overheating issues, ultimately preserving the final cut’s quality. An alternative solution is based on pulsed wave emission, providing dynamic and precise control over the thermal energy delivered to the workpiece. In this work, pulsed wave emission was employed to ensure process stability during transient conditions for fusion cutting of 10mm AISI304. A 6kW fiber laser was utilized alongside a coaxial camera-based monitoring setup to observe the melt dynamics. Results demonstrate that power modulation effectively reduces defect formation, and process emission images can be exploited to identify successful cuts.

Additive Manufacturing (AM) can provide several benefits for battery manufacturing by combining geometrical flexibility and controlled porosity. Zinc is an appealing battery material because it is an abundant metal with relatively low cost, and potential recyclability. However, the processing of Zn and its alloys through melting based AM processes is cumbersome. The use of novel ring-shaped beams can widen the processing window in Laser Powder Bed Fusion (LPBF), which is an appealing technology to produce electrodes. In this work, single-track formation during the LPBF of pure Zn with Gaussian and doughnut shaped beams was studied. In a wide range of experiments, geometrical attributes were observed through cross-sectional analyses and high-speed imaging. The conditions that range from surface heating to conduction melting and keyholing were determined. The feasibility of producing thin walls for anodes was also demonstrated.

BackgroundShoe inserts, orthopaedic shoes, ankle-foot orthoses (AFOs) are important devices in Charcot-Marie-Tooth disease (CMT) management, but data about use, benefits and tolerance are scanty.MethodsWe administered to Italian CMT Registry patients an online ad hoc questionnaire investigating use, complications and perceived benefit/tolerability/emotional distress of shoe inserts, orthopaedic shoes, AFOs and other orthoses/aids. Patients were also asked to fill in the Quebec User Evaluation of Satisfaction with assistive Technology questionnaire, rating satisfaction with currently used AFO and related services.ResultsWe analysed answers from 266 CMT patients. Seventy per cent of subjects were prescribed lower limb orthoses, but 19% did not used them. Overall, 39% of subjects wore shoe inserts, 18% orthopaedic shoes and 23% AFOs. Frequency of abandonment was high: 24% for shoe inserts, 28% for orthopaedic shoes and 31% for AFOs. Complications were reported by 59% of patients and were more frequently related to AFOs (69%). AFO users experienced greater emotional distress and reduced tolerability as compared with shoe inserts (p<0.001) and orthopaedic shoes (p=0.003 and p=0.045, respectively). Disease severity, degree of foot weakness, customisation and timing for customisation were determinant factors in AFOs’ tolerability. Quality of professional and follow-up services were perceived issues.ConclusionsThe majority of CMT patients is prescribed shoe inserts, orthopaedic shoes and/or AFOs. Although perceived benefits and tolerability are rather good, there is a high rate of complications, potentially inappropriate prescriptions and considerable emotional distress, which reduce the use of AFOs. A rational, patient-oriented and multidisciplinary approach to orthoses prescription must be encouraged.

Energy-efficient retrofitting of existing buildings is a key aspect for reaching the proposed energy consumption reduction targets fixed by public authorities in different countries. For this task, the availability of as-built building models is of primary importance for both diagnosis of thermal dispersion and designing of retrofitting. In this paper, we present an automated methodology to derive highly detailed 3D vector models of existing building façades starting from terrestrial laser scanning data. The presented methodology first accomplishes the segmentation of the point cloud of a building façade into its planar elements. Then, starting from the identified planar clusters, façade breaklines are automatically extracted to be used later to generate a 3D vector model. During this final step, some priors on urban scenes like the prevalence of straight lines and orthogonal intersections are exploited to set additional constraints. The final product is a semantically enriched 3D model of the building façade that can be integrated in Building Information Model (BIM) for planned maintenance. Eventually, the integration between derived façade models and infrared thermography (IRT) is presented for energy efficiency evaluation of buildings and detection of thermal anomalies.

The transition towards electric mobility requires the development of manufacturing systems capable of realising products with elevated electrical and mechanical performance and in-line qualification. Laser welding of thin sheets is an enabling technology for the production of battery packs. Given the numerosity of the joints and the stringent requirements, in-situ monitoring of the process and advanced data analysis with Machine Learning (ML) algorithms are fundamental tools which need to be explored. The current study presents a methodological approach for the process development and integration of a monitoring architecture for the realisation of dissimilar material busbar connections (0.2 mm Ni-plated steel over 0.6 mm Cu in lap joint configuration) for the production of a high-performance battery pack for an electric racing motorbike. A single mode fiber laser welding system was equipped with different sensors to retrieve data during the laser-material interaction. The monitoring system was composed of three photodiodes positioned off-axis respectively observing the visible, thermal near-infrared and laser back-reflection region. A spectroscope also sampled process emission from an off-axis perspective whilst another photodiode was positioned within the laser source to observe the process coaxially. Following a preliminary phase required to characterise the process and data provided by the sensors, experiments were designed to identify defects and variations with respect to the reference condition. On a single sensor basis, supervised classification machine learning algorithms were trained to discern joints performed on an out of focus workpiece or in the presence of gap between the sheets. Results indicate that photodiodes observing the laser back-reflected light are capable of providing process relevant information which can be exploited to identify drifts from the reference processing condition. ML algorithms exhibited high accuracy classification even with a reduced amount of data.

Laser metal deposition (LMD) is one of the most important techniques in additive manufacturing (AM) thanks to the high flexibility of the process, which makes the production of free-form shapes possible. However, working with some materials presents some challenges. This is the case with aluminum alloys due to their reflectivity and their very high thermal conductivity. On the other hand, aluminum and its alloys are quite important in several industrial fields, including aerospace, among others, due to their mechanical properties with low density. In this work, LMD is applied on an A357 aluminum alloy. The techniques are investigated moving from a single-track approach up to multi-pass and multi-layer strategies. Densities, microstructures and mechanical performance are investigated as a function of process parameters. Porosities are reduced, resulting in overall densities of over 97% and microhardness values are in the range of 80–100 HV. Differences in mechanical performance are analysed considering different building directions, showing a dependency on loading direction and the distance from the substrate. Tensile tests reveal a promising performance for further investigation with the LMD technique. The obtained evidence is interesting for future trends where large and light components are required while maintaining the mechanical performance of traditional manufacturing methods. Moreover, a comprehensive study is done for the first time on A357 alloy that is deeply used in the aerospace and automotive fields. The investigation and definition of the best process parameters open the possibility of exploiting LMD technology in the production of wide components or for adding features to already existing components overcoming some limits of other AM technologies.

This global phase 3 study compared lisocabtagene maraleucel (liso-cel) with a standard of care (SOC) as second-line therapy for primary refractory or early relapsed (≤12 months) large B-cell lymphoma (LBCL). Adults eligible for autologous stem cell transplantation (ASCT; N = 184) were randomly assigned in a 1:1 ratio to liso-cel (100 × 106 chimeric antigen receptor–positive T cells) or SOC (3 cycles of platinum-based immunochemotherapy followed by high-dose chemotherapy and ASCT in responders). The primary end point was event-free survival (EFS). In this primary analysis with a 17.5-month median follow-up, median EFS was not reached (NR) for liso-cel vs 2.4 months for SOC. Complete response (CR) rate was 74% for liso-cel vs 43% for SOC (P < .0001) and median progression-free survival (PFS) was NR for liso-cel vs 6.2 months for SOC (hazard ratio [HR] = 0.400; P < .0001). Median overall survival (OS) was NR for liso-cel vs 29.9 months for SOC (HR = 0.724; P = .0987). When adjusted for crossover from SOC to liso-cel, 18-month OS rates were 73% for liso-cel and 54% for SOC (HR = 0.415). Grade 3 cytokine release syndrome and neurological events occurred in 1% and 4% of patients in the liso-cel arm, respectively (no grade 4 or 5 events). These data show significant improvements in EFS, CR rate, and PFS for liso-cel compared with SOC and support liso-cel as a preferred second-line treatment compared with SOC in patients with primary refractory or early relapsed LBCL. This trial was registered at www.clinicaltrials.gov as #NCT03575351.

•Liso-cel significantly improved EFS, CR rate, and PFS vs chemotherapy ± ASCT as a second-line treatment for LBCL.•Liso-cel was well tolerated as a second-line therapy, with low rates of any grade or severe cytokine release syndrome and neurological events.

New generation of multi-core fiber laser sources provide in-source dynamic beam shaping. Such sources can switch between Gaussian and ring beams, providing new irradiance profiles. The new irradiance profiles add up to the process flexibility for controlling the temperature fields generated in the laser powder bed fusion (LPBF) process. On the other hand, they bring further complexity as new process parameters should be defined and their influence on the mechanical properties unveiled. Accordingly, this work studies the use of seven different beam shapes provided by a multi-core industrial fiber laser source with beam diameters varying between 47 μm to 144 μm during the LPBF of AlSi7Mg0.6 alloy. The beam spatial profiles were measured and descriptive irradiance parameters were defined. The Al-alloy constituted a challenging material type due to its high reflectivity and low melting point, hence, more prone to lack-of-fusion and keyhole defects. LPBF experiments were conducted at fixed energy density and peak irradiance levels investigating the influence of the beam shapes on the melt pool geometry in prismatic samples. The results showed that the peak irradiance and the ring intensity had a direct impact on the melt pool aspect ratio (AR) and melt pool depth to layer thickness ratio (h/z). With all the conditions providing adequately dense parts (>99.5 %), the mechanical properties were found to be correlated to the melt pool geometry. The results confirm that the beam shape can be tuned between the central peak and the ring to further manipulate the material properties in LPBF.

Realising complex components in laser metal deposition (LMD) without process control can lead to heat accumulation due to varying heat dissipation capacities of the geometric features. Monitoring the temperature of the molten pool is crucial, and infrared pyrometry is a commonly employed technique. This study explores temperature monitoring using a coaxial pyrometer operating in two modes: single wavelength and ratio modes. The single wavelength pyrometer measures the target temperature through optical emission but requires knowledge of target emissivity. In contrast, the ratio pyrometer is more adaptable in LMD as it does not depend on emissivity information, but it can be affected by background interferences. Single wavelength and ratio pyrometry monitoring of the molten pool was tested in two deposition conditions, using either a small or a large laser spot, highlighting the importance of collecting the single wavelength temperature.

Recent studies have demonstrated that the Ukraine–Russia war has incurred evident changes to anthropogenic activities in the Kiev metropolis. Hence, this work employs Sentinel 5P imagery and a novel artificial intelligence model for predicting air pollution in Kiev. A well-known machine learning (ML) model, namely, multilayer perceptron neural network (MLPNN), is coupled with electromagnetic field optimization (EFO) algorithm to predict the daily concentration of particulate matter 2.5 (PM2.5). Initially, a dataset is prepared by collecting 11 meteorological, atmospheric, and temporal factors from remote sensing and ground measurements. Then, principal component analysis (PCA) is used to determine the most contributive factors and create a reduced dataset. Four scenarios are defined by considering the reduced/original dataset, along with, predicting the current day/one-day-ahead PM2.5. A sensitivity analysis revealed that the most accurate results were achieved for predicting one-day-ahead PM2.5 using the reduced dataset. After adjusting the EFO-MLPNN hybrid model, its performance is compared to classical MLPNN and adaptive neuro-fuzzy inference system (ANFIS). According to the results, the EFO-MLPNN with a root mean square error (RMSE) of $6.68\,\,\mu \text{g}\cdot \text{m}^{-3}$ and Pearson correlation coefficient ( ${R}_{P}$ ) of 0.82 outperformed both MLPNN and ANFIS outcomes. These findings infer that by optimizing the MLPNN by EFO, its prediction accuracy can be improved. The proposed hybrid model is therefore recommended for more practical air quality estimation and decision-making in the studied site. Lastly, a monolithic neural-based formula is extracted from the EFO-MLPNN hybrid for the explicit prediction of PM2.5.

Lisocabtagene maraleucel (liso-cel) has shown promising efficacy in clinical trials for patients with relapsed/refractory large B-cell lymphoma (LBCL). We present health-related quality of life (HRQOL) results from the TRANSFORM study, the first comparative analysis of liso-cel vs standard of care (SOC) as second-line therapy in this population. Adults with LBCL refractory or relapsed ≤12 months after first-line therapy and eligible for autologous stem cell transplantation were randomized 1:1 to the liso-cel or SOC arms (3 cycles of immunochemotherapy in which responders proceeded to high-dose chemotherapy and autologous stem cell transplantation). HRQOL was assessed by European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – 30 items and the Functional Assessment of Cancer Therapy-Lymphoma subscale. Patients with baseline and ≥1 postbaseline assessment were analyzed (liso-cel, n = 47; SOC, n = 43). The proportion of patients with meaningful improvement in global health status/quality of life (QOL) was higher, whereas deterioration was lower in the liso-cel arm vs SOC arm from day 126 to month 6. Mean change scores showed meaningful worsening in global health status/QOL at month 6, fatigue at day 29 and month 6, and pain at month 6 with SOC; mean scores for other domains were maintained or improved in both arms. Time to confirmed deterioration favored the liso-cel arm vs SOC arm in global health status/QOL (median: not reached vs 19.0 weeks, respectively; hazard ratio, 0.47; 95% confidence interval, 0.24-0.94). HRQOL was either improved or maintained from baseline in patients with relapsed/refractory LBCL in the liso-cel arm vs SOC arm as second-line treatment. This study is registered at clinicaltrials.gov as #NCT0357531.

•In TRANSFORM, health-related quality of life improved or was maintained with second-line lisocabtagene maraleucel vs standard of care.•HRQOL results coupled with favorable efficacy support liso-cel as a potential second-line option for patients with relapsed/refractory LBCL.

Objective The objective of this study was to evaluate the recall bias of symptoms evaluation in knee osteoarthritis (OA).Design In this multicentric pilot study, 50 patients with knee OA used a mobile App (Ecological Momentary Assessment [EMA]) to collect pain and function on two 0 to 10 numerical rating scales (NRS) 2 times a day for 2 months. At the 1-month and at the 2-month follow-up visits, patients retrospectively evaluated the mean level of pain/function of the last month. Recall bias was computed as the difference between the mean level of pain/function reported using the App and the level reported with the retrospective assessment. The correlation between the recall bias and patients’ characteristics, as well as pain/function trajectories, was analyzed.Results A statistically significant recall bias was documented with higher pain reported at 1-month with the retrospective assessment (P< 0.001). These results were confirmed also at the 2-month follow-up (P= 0.002). For function, no significant recall bias was documented. During the first and second months, 47 and 31 patients showed pain peaks, respectively. The number of pain peaks during the first month was correlated with the magnitude of the recall bias (P= 0.02).Conclusions The recall bias influences the retrospective self-assessment of pain at the follow-up visits and the presence of pain peaks, a common event in the patients with OA, increases the magnitude of recall bias. The EMA performed with a mobile App is a useful tool to limit the influence of recall bias in the clinical and research setting evaluation of knee OA.

Patients with large B-cell lymphoma (LBCL) primary refractory to or relapsed within 12 months of first-line therapy are at high risk for poor outcomes with current standard of care, platinum-based salvage immunochemotherapy and autologous haematopoietic stem cell transplantation (HSCT). Lisocabtagene maraleucel (liso-cel), an autologous, CD19-directed chimeric antigen receptor (CAR) T-cell therapy, has previously demonstrated efficacy and manageable safety in third-line or later LBCL. In this Article, we report a prespecified interim analysis of liso-cel versus standard of care as second-line treatment for primary refractory or early relapsed (within 12 months after response to initial therapy) LBCL.

In laser powder bed fusion (LPBF), it is common practice to select process parameters to achieve high density parts starting from simple geometries such as cubes or cylinders. However, additive manufacturing is usually adopted to produce very complex geometries, where parameters should be tuned locally, depending on the local features to be processed. In fact, geometrical features, such as overhangs, acute corners, and thin walls may lead to over- or under-heating conditions, which may result in geometrical inaccuracy, high roughness, volumetric errors (i.e., porosity) or even job failure due to surface collapse. This work proposes a layer-wise control strategy to improve the geometrical precision of overhanging regions using a coaxial melt pool monitoring system. The melt-pool images acquired at each layer are used in a control-loop to adapt the process parameters locally at the next layer in order to minimize surface defects. In particular, the laser duty cycle is used as a controllable parameter to correct the energy density. This work presents the main architecture of the proposed approach, the control strategy and the experimental procedure that need to be applied to design the control parameters. The layer-wise control strategy was tested on AISI 316L stainless steel using an open LPFB platform. The results showed that the proposed layer-wise control solution results in a constant melt pool observed via the laser heated area size starting from the second layer onward, leading to a significant improvement in the geometrical accuracy of 5 mm-long bridge geometries.

Background: There is no consensus about the safety of outpatient total hip arthroplasty (THA). Therefore, the purpose of this meta-analysis was to quantitatively evaluate and compare outpatient and inpatient THA studies in terms of complication and readmission rates.Methods: A systematic search of the literature was performed on 26 July 2019 on PubMed, Web of Science, Cochrane library, and on the grey literature databases. The papers thus collected were used for a meta-analysis comparing outpatient and inpatient THA in terms of complication and readmission rates. Risk of bias and quality of evidence were defined according to Cochrane guidelines. The PRISMA guidelines were used to determine which papers to include in this study.Results: The literature search resulted in 2317 articles; of these, 8 articles were used for the meta-analysis. A total of 66,971 patients were included, of which 1428 were THA outpatients. The overall complication rate for outpatient THAs was 3.0%, while inpatient THAs had an overall complication rate of 4.7%. The readmission rate was 1.4% in outpatient THAs and 3.0% in inpatient THAs. Only 6 studies reported the number of deaths, which ranged from 0% to 0.01%. The included studies present a moderate risk of bias and, according to GRADE guidelines, the level of evidence for complications and readmissions is very low.Conclusions: This meta-analysis documented that outpatient THA is a feasible approach since it does not increase complications or readmissions with respect to inpatient THA, but the available studies present a moderate risk of bias and the quality of evidence of these findings is very low. Future high-level studies are needed to confirm results and indications for outpatient THA.

Azacitidine-mediated hypomethylation promotes tumor cell immune recognition but may increase the expression of inhibitory immune checkpoint molecules. We conducted the first randomized phase 2 study of azacitidine plus the immune checkpoint inhibitor durvalumab vs azacitidine monotherapy as first-line treatment for higher-risk myelodysplastic syndromes (HR-MDS). In all, 84 patients received 75 mg/m2 subcutaneous azacitidine (days 1-7 every 4 weeks) combined with 1500 mg intravenous durvalumab on day 1 every 4 weeks (Arm A) for at least 6 cycles or 75 mg/m² subcutaneous azacitidine alone (days 1-7 every 4 weeks) for at least 6 cycles (Arm B). After a median follow-up of 15.25 months, 8 patients in Arm A and 6 in Arm B remained on treatment. Patients in Arm A received a median of 7.9 treatment cycles and those in Arm B received a median of 7.0 treatment cycles with 73.7% and 65.9%, respectively, completing ≥4 cycles. The overall response rate (primary end point) was 61.9% in Arm A (26 of 42) and 47.6% in Arm B (20 of 42; P = .18), and median overall survival was 11.6 months (95% confidence interval, 9.5 months to not evaluable) vs 16.7 months (95% confidence interval, 9.8-23.5 months; P = .74). Durvalumab-related adverse events (AEs) were reported by 71.1% of patients; azacitidine-related AEs were reported by 82% (Arm A) and 81% (Arm B). Grade 3 or 4 hematologic AEs were reported in 89.5% (Arm A) vs 68.3% (Arm B) of patients. Patients with TP53 mutations tended to have a worse response than patients without these mutations. Azacitidine increased programmed cell death ligand 1 (PD-L1 [CD274]) surface expression on bone marrow granulocytes and monocytes, but not blasts, in both arms. In summary, combining azacitidine with durvalumab in patients with HR-MDS was feasible but with more toxicities and without significant improvement in clinical outcomes over azacitidine alone. This trial was registered at www.clinicaltrials.gov as #NCT02775903.

Evidence suggests that combining immunotherapy with hypomethylating agents may enhance antitumor activity. This phase 2 study investigated the activity and safety of durvalumab, a programmed death-ligand 1 (PD-L1) inhibitor, combined with azacitidine for patients aged ≥65 years with acute myeloid leukemia (AML), including analyses to identify biomarkers of treatment response. Patients were randomized to first-line therapy with azacitidine 75 mg/m2 on days 1 through 7 with (Arm A, n = 64) or without (Arm B, n = 65) durvalumab 1500 mg on day 1 every 4 weeks. Overall response rate (complete response [CR] + CR with incomplete blood recovery) was similar in both arms (Arm A, 31.3%; Arm B, 35.4%), as were overall survival (Arm A, 13.0 months; Arm B, 14.4 months) and duration of response (Arm A, 24.6 weeks; Arm B, 51.7 weeks; P = .0765). No new safety signals emerged with combination treatment. The most frequently reported treatment-emergent adverse events were constipation (Arm A, 57.8%; Arm B, 53.2%) and thrombocytopenia (Arm A, 42.2%; Arm B, 45.2%). DNA methylation, mutational status, and PD-L1 expression were not associated with response to treatment. In this study, first-line combination therapy with durvalumab and azacitidine in older patients with AML was feasible but did not improve clinical efficacy compared with azacitidine alone. ClinicalTrials.gov: NCT02775903.

Azacitidine-mediated hypomethylation promotes tumor cell immune recognition but may increase the expression of inhibitory immune checkpoint molecules. We conducted the first randomized phase 2 study of azacitidine plus the immune checkpoint inhibitor durvalumab vs azacitidine monotherapy as first-line treatment for higher-risk myelodysplastic syndromes (HR-MDS). In all, 84 patients received 75 mg/m2subcutaneous azacitidine (days 1-7 every 4 weeks) combined with 1500 mg intravenous durvalumab on day 1 every 4 weeks (Arm A) for at least 6 cycles or 75 mg/m2subcutaneous azacitidine alone (days 1-7 every 4 weeks) for at least 6 cycles (Arm B). After a median follow-up of 15.25 months, 8 patients in Arm A and 6 in Arm B remained on treatment. Patients in Arm A received a median of 7.9 treatment cycles and those in Arm B received a median of 7.0 treatment cycles with 73.7% and 65.9%, respectively, completing ≥4 cycles. The overall response rate (primary end point) was 61.9% in Arm A (26 of 42) and 47.6% in Arm B (20 of 42; P= .18), and median overall survival was 11.6 months (95% confidence interval, 9.5 months to not evaluable) vs 16.7 months (95% confidence interval, 9.8-23.5 months; P= .74). Durvalumab-related adverse events (AEs) were reported by 71.1% of patients; azacitidine-related AEs were reported by 82% (Arm A) and 81% (Arm B). Grade 3 or 4 hematologic AEs were reported in 89.5% (Arm A) vs 68.3% (Arm B) of patients. Patients with TP53mutations tended to have a worse response than patients without these mutations. Azacitidine increased programmed cell death ligand 1 (PD-L1 [CD274]) surface expression on bone marrow granulocytes and monocytes, but not blasts, in both arms. In summary, combining azacitidine with durvalumab in patients with HR-MDS was feasible but with more toxicities and without significant improvement in clinical outcomes over azacitidine alone. This trial was registered at www.clinicaltrials.govas #NCT02775903.

Current practice in large infrastructure management requires new procedures for cost-effective maintenance and safe operation. In this sense, the availability of new surveying, inspection and monitoring procedures as well as new instruments can play a significant role in securing a fundamental asset with an affordable cost. Indeed, inspection and monitoring with automated or semi-automated instruments can guarantee a significant reduction of time in operations that are currently manual, risky and time-consuming. The availability of new sensing platforms and instruments like lightweight mobile mapping systems and drones is fundamental for rethinking current survey and inspection practice. However, their performance, in terms of metric accuracy and reliability, in real applications is still limited. On the other hand, the acquisition of primary data is only the first step of the maintenance workflow. Indeed, even if the adoption of informative content models for structural health monitoring (SHM) for large infrastructures clearly presents important advantages compared with standard management; the adoption of proper tolls for such complex infrastructures poses some issues that need to be solved to develop smooth management and maintenance workflows. This paper presents a methodology for the generation of a detailed informative model starting from multi-sources data: terrestrial laser scanning (TLS), Mobile Mapping Systems (MMS) and photogrammetry. The integration of those different techniques is discussed and a comparative analysis is carried out. The enrichment of the informative model with further data coming from load testing and inspection is presented to create a unique informative platform suitable for different end-users involved in maintenance operations.