Diffuse Large B-Cell Lymphomas: From Morphology to Genomic Profiling

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma in the western world. The classification of these lymphomas has been and continues to be one of the most challenging aspects of this entity. DLBCLs are clinically and morphologically very heterogeneous diseases presenting a barrier to successfully developing adequate classification systems with significant clinical, prognostic and therapeutic relevance. Recent gene expression profiling and next-generation sequencing advances have improved our understanding of the disease. This review will present an up-to-date overview of traditional and modern classification systems in DLBLC, emphasizing newly proposed subgroups based on integrating gene expression profiling and sequencing data

Nonthermal Atmospheric Plasma Reactors for Hydrogen Production from Low-Density Polyethylene

Hydrogen is largely produced via natural gas reforming or electrochemical water-splitting, leaving organic solid feedstocks under-utilized. Plasma technology powered by renewable electricity can lead to the sustainable upcycling of plastic waste and production of green hydrogen. In this work, low-temperature atmospheric pressure plasma reactors based on transferred arc (transarc) and gliding arc (glidarc) discharges are designed, built, and characterized to produce hydrogen from low-density polyethylene (LDPE) as a model plastic waste. Experimental results show that hydrogen production rate and efficiency increase monotonically with increasing voltage level in both reactors, with the maximum hydrogen production of 0.33 and 0.42 mmol/g LDPE for transarc and glidarc reactors, respectively. For the transarc reactor, smaller electrode-feedstock spacing favors greater hydrogen production, whereas, for the glidarc reactor, greater hydrogen production is obtained at intermediate flow rates. The hydrogen production from LDPE is comparable despite the markedly different modes of operation between the two reactors

Hydrogen from Cellulose and Low-density Polyethylene via Atmospheric Pressure Nonthermal Plasma

The valorization of waste, by creating economic value while limiting environmental impact, can have an essential role in sustainable development. Particularly, polymeric waste such as biomass and plastics can be used for the production of green hydrogen as a carbon-free energy carrier through the use of nonthermal plasma powered by renewable, potentially surplus, electricity. In this study, a Streamer Dielectric-Barrier Discharge (SDBD) reactor is designed and built to extract hydrogen and carbon co-products from cellulose and low-density polyethylene (LDPE) as model feedstocks of biomass and plastic waste, respectively. Spectroscopic and electrical diagnostics, together with modeling, are used to estimate representative plasma properties, namely electron and excitation temperatures, number density, and power consumption. Cellulose and LDPE are plasma-treated for different treatment times to characterize the evolution of the hydrogen production process. Gas products are analyzed using gas chromatography to determine the mean hydrogen production rate, production efficiency, hydrogen yield, selectivity, and energy cost. The results show that the maximum hydrogen production efficiency for cellulose is 0.8 mol/kWh, which is approximately double that for LDPE. Furthermore, the energy cost of hydrogen production from cellulose is 600 kWh/kg of H2, half that of LDPE. Solid products are examined via scanning electron microscopy, revealing the distinct morphological structure of the two feedstocks treated, as well as by elemental composition analysis. The results demonstrate that SDBD plasma is effective at producing hydrogen from cellulose and LDPE at near atmospheric pressure and relatively low-temperature conditions in rapid-response and compact processes

Vacuolization of hematopoietic precursors: an enigma with multiple etiologies

Cytoplasmic vacuoles in precursors can be seen in a number of clinical settings, including copper deficiency, zinc toxicity, alcohol abuse, antibiotic treatment, myelodysplasia, and VEXAS syndrome. Gurnari et al asked how common VEXAS syndrome is in patients whose bone marrow aspirates show this distinctive feature, finding 2 diagnoses of VEXAS among 24 cases with vacuoles

PHANGS-MUSE: Detection and Bayesian classification of ~40000 ionised nebulae in nearby spiral galaxies

In this work, we present a new catalogue of >40000 ionised nebulae distributed across the 19 galaxies observed by the PHANGS-MUSE survey. The nebulae have been classified using a new model-comparison-based algorithm that exploits the odds ratio principle to assign a probabilistic classification to each nebula in the sample. The resulting catalogue is the largest catalogue containing complete spectral and spatial information for a variety of ionised nebulae available so far in the literature. We developed this new algorithm to address some of the limitations of the traditional classification criteria, such as their binarity, the sharpness of the involved limits, and the limited amount of data they rely on for the classification. The analysis of the catalogue shows that the algorithm performs well when selecting H II regions. We can recover their luminosity function, and its properties are in line with what is available in the literature. We also identify a rather significant population of shock-ionised regions (mostly composed of supernova remnants), an order of magnitude larger than any other homogeneous catalogue of supernova remnants currently available in the literature. The number of supernova remnants we identify per galaxy is in line with results in our Galaxy and other very nearby sources. However, limitations in the source detection algorithm result in an incomplete sample of planetary nebulae, even though their classification seems robust. Finally, we demonstrate how applying a correction for the contribution of the diffuse ionised gas to the nebulae's spectra is essential to obtain a robust classification of the objects and how a correct measurement of the extinction using DIG-corrected line fluxes prompts the use of a higher theoretical Ha/Hb ratio (3.03) than what is commonly used when recovering the E(B-V) via the Balmer decrement technique in massive star-forming galaxies.Comment: 58 pages, 46 figures. Paper accepted for pubblications in A&A. The catalogue will be available via the CDS or at the following link: http://dx.doi.org/10.11570/23.000

Star Formation Laws and Efficiencies across 80 Nearby Galaxies

We measure empirical relationships between the local star formation rate (SFR) and properties of the star-forming molecular gas on 1.5 kpc scales across 80 nearby galaxies. These relationships, commonly referred to as "star formation laws," aim at predicting the local SFR surface density from various combinations of molecular gas surface density, galactic orbital time, molecular cloud free-fall time, and the interstellar medium dynamical equilibrium pressure. Leveraging a multiwavelength database built for the PHANGS survey, we measure these quantities consistently across all galaxies and quantify systematic uncertainties stemming from choices of SFR calibrations and the CO-to-H$_2$ conversion factors. The star formation laws we examine show 0.3-0.4 dex of intrinsic scatter, among which the molecular Kennicutt-Schmidt relation shows a $\sim$10% larger scatter than the other three. The slope of this relation ranges $\beta\approx0.9{-}1.2$, implying that the molecular gas depletion time remains roughly constant across the environments probed in our sample. The other relations have shallower slopes ($\beta\approx0.6{-}1.0$), suggesting that the star formation efficiency (SFE) per orbital time, the SFE per free-fall time, and the pressure-to-SFR surface density ratio (i.e., the feedback yield) may vary systematically with local molecular gas and SFR surface densities. Last but not least, the shapes of the star formation laws depend sensitively on methodological choices. Different choices of SFR calibrations can introduce systematic uncertainties of at least 10-15% in the star formation law slopes and 0.15-0.25 dex in their normalization, while the CO-to-H$_2$ conversion factors can additionally produce uncertainties of 20-25% for the slope and 0.10-0.20 dex for the normalization.Comment: 10 pages main text + 2 appendices. ApJL in press. Data products available at https://www.canfar.net/storage/list/phangs/RELEASES/Sun_etal_2023 . Slides summarizing key results can be found at https://www.dropbox.com/s/5gsegexeo9n0t05/Sun_et_PHANGS_2023.pptx?dl=

Histone H4 acetylation by immunohistochemistry and prognosis in newly diagnosed adult acute lymphoblastic leukemia (ALL) patients

Background: Histone deacetylase (HDAC) inhibitors are a novel anti-tumor therapy. To determine whether HDAC inhibitors may be useful in the treatment of adult acute lymphoblastic leukemia (ALL), we examined the acetylation of histone H4 by immunohistochemistry in newly diagnosed ALL patients and evaluated the impact of acetylation on complete remission (CR) rate, relapse-free survival (RFS), and overall survival (OS). Methods: Patients >= 18 years of age and an available diagnostic bone marrow biopsy were evaluated. Cox proportional hazards analysis was used to identify univariate and multivariate correlates of CR, RFS, and OS. The variables histone H4 acetylation (positive or negative), white blood count, cytogenetic (CG) risk group (CALGB criteria), and age were used in multivariate analysis. Results: On multivariate analysis, histone acetylation was associated with a trend towards an improved OS (for all CG risk groups) (HR = 0.51, p = 0.09). In patients without poor risk CG, there was an impressive association between the presence of histone acetylation and an improved CR rate (OR 3.43, p = 0.035), RFS (HR 0.07, p = 0.005), and OS (HR 0.24, p = 0.007). This association remained statistically significant in multivariate analysis. Conclusions: These data provide a rationale for the design of novel regimens incorporating HDAC inhibitors in ALL

Stratifying diffuse large B-cell lymphoma patients treated with chemoimmunotherapy: GCB/non-GCB by immunohistochemistry is still a robust and feasible marker

Diffuse large B cell lymphoma (DLBCL) is a heterogeneous group of aggressive lymphomas that can be classified into three molecular subtypes by gene expression profiling (GEP): GCB, ABC and unclassified. Immunohistochemistry-based cell of origin (COO) classification, as a surrogate for GEP, using three available immunohistochemical algorithms was evaluated in TMA-arranged tissue samples from 297 patients with de novo DLBCL treated by chemoimmunotherapy (R-CHOP and R-CHOP-like regimens). Additionally, the prognostic impacts of MYC, BCL2, IRF4 and BCL6 abnormalities detected by FISH, the relationship between the immunohistochemical COO classification and the immunohistochemical expression of MYC, BCL2 and pSTAT3 proteins and clinical data were evaluated. In our series, non-GCB DLBCL patients had significantly worse progression-free survival (PFS) and overall survival (OS), as calculated using the Choi, Visco-Young and Hans algorithms, indicating that any of these algorithms would be appropriate for identifying patients who require alternative therapies to R-CHOP. Whilst MYC abnormalities had no impact on clinical outcome in the non-GCB subtype, those patients with isolated MYC rearrangements and a GCB-DLBCL phenotype had worse PFS and therefore might benefit from novel treatment approaches