Determining therapeutic susceptibility in multiple myeloma by single-cell mass accumulation

Multiple myeloma (MM) has benefited from significant advancements in treatment that have improved outcomes and reduced morbidity. However, the disease remains incurable and is characterized by high rates of drug resistance and relapse. Consequently, methods to select the most efficacious therapy are of great interest. Here we utilize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based on measuring their mass accumulation rate (MAR). We show that MAR accurately and rapidly defines therapeutic susceptibility across human multiple myeloma cell lines to a gamut of standard-of-care therapies. Finally, we demonstrate that our MAR assay, without the need for extended culture ex vivo, correctly defines the response of nine patients to standard-of-care drugs according to their clinical diagnoses. This data highlights the MAR assay in both research and clinical applications as a promising tool for predicting therapeutic response using clinical samples

Soil respiratory quotient determined via barometric process separation combined with nitrogen-15 labeling

The barometric process separation (BaPS) and ¹⁵N dilution techniques were used to determine gross nitrification rates on the same soil cores from an old grassland soil. The BaPS-technique separates the O₂ consumption into that from nitrification and that from soil organic matter (SOM) respiration. The most sensitive parameter for the calculations via the BaPS technique is the respiratory quotient (RQ = ∆CO₂/∆O₂) for SOM turnover (RQSOM). Combining both methods (BaPS–¹⁵N ) allowed the determination of the RQSOM. The RQ value determined in such a way is adjusted for the influence of nitrification and denitrification, which are both characterized by totally different RQ values. The results for the grassland soil showed that 6 to 10% of O₂ was consumed by nitrification when incubated at 20°C and 0.49 g H₂O g⁻¹ soil. A set of BaPS measurements with the same soil at various temperature and moisture contents showed that up to 49% of the total O₂ consumption was due to nitrification. The calculated RQSOM values via the BaPS–¹⁵N technique presented here are more closely associated with the overall SOM turnover than the usual net RQ reported in the literature. Furthermore, the RQSOM value provides an overall indication of the decomposability and chemical characteristics of the respired organic material. Hence, it has the potential to serve as a single state index for SOM quality and therefore be a useful index for SOM turnover models based on substrate quality

Observations of Energetic-particle Population Enhancements along Intermittent Structures near the Sun from the Parker Solar Probe

Observations at 1 au have confirmed that enhancements in measured energetic-particle (EP) fluxes are statistically associated with "rough" magnetic fields, i.e., fields with atypically large spatial derivatives or increments, as measured by the Partial Variance of Increments (PVI) method. One way to interpret this observation is as an association of the EPs with trapping or channeling within magnetic flux tubes, possibly near their boundaries. However, it remains unclear whether this association is a transport or local effect; i.e., the particles might have been energized at a distant location, perhaps by shocks or reconnection, or they might experience local energization or re-acceleration. The Parker Solar Probe (PSP), even in its first two orbits, offers a unique opportunity to study this statistical correlation closer to the corona. As a first step, we analyze the separate correlation properties of the EPs measured by the Integrated Science Investigation of the Sun (IS⊙IS) instruments during the first solar encounter. The distribution of time intervals between a specific type of event, i.e., the waiting time, can indicate the nature of the underlying process. We find that the IS⊙IS observations show a power-law distribution of waiting times, indicating a correlated (non-Poisson) distribution. Analysis of low-energy (~15 – 200 keV/nuc) IS⊙IS data suggests that the results are consistent with the 1 au studies, although we find hints of some unexpected behavior. A more complete understanding of these statistical distributions will provide valuable insights into the origin and propagation of solar EPs, a picture that should become clear with future PSP orbits

Disrupted Maturation of the Microbiota and Metabolome among Extremely Preterm Infants with Postnatal Growth Failure

Growth failure during infancy is a major global problem that has adverse effects on long-term health and neurodevelopment. Preterm infants are disproportionately affected by growth failure and its effects. Herein we found that extremely preterm infants with postnatal growth failure have disrupted maturation of the intestinal microbiota, characterized by persistently low diversity, dominance of pathogenic bacteria within the Enterobacteriaceae family, and a paucity of strictly anaerobic taxa including Veillonella relative to infants with appropriate postnatal growth. Metabolomic profiling of infants with growth failure demonstrated elevated serum acylcarnitines, fatty acids, and other byproducts of lipolysis and fatty acid oxidation. Machine learning algorithms for normal maturation of the microbiota and metabolome among infants with appropriate growth revealed a pattern of delayed maturation of the microbiota and metabolome among infants with growth failure. Collectively, we identified novel microbial and metabolic features of growth failure in preterm infants and potentially modifiable targets for intervention

Mosquitoes and malaria transmission in irrigated rice-fields in the Benoue valley of northern Cameroon

International audienc

Mass-Loss Rate Determination for the Massive Binary V444 Cyg using 3-D Monte-Carlo Simulations of Line and Polarization Variability

A newly developed 3-D Monte Carlo model is used, in conjunction with a multi-line non-LTE radiative transfer model, to determine the mass-loss rate of the Wolf-Rayet (W-R) star in the massive binary \object{V444 Cyg} (WN5+O6). This independent estimate of mass-loss rate is attained by fitting the observed \HeI (5876) \AA and \HeII (5412) \AA line profiles, and the continuum light curves of three Stokes parameters ((I, Q, U)) in the (V) band simultaneously. The high accuracy of our determination arises from the use of many observational constraints, and the sensitivity of the continuum polarization to the mass-loss rate. Our best fit model suggests that the mass-loss rate of the system is (\dot{M}_{\WR}=0.6(\pm 0.2) \times 10^{-5} M_{\sun} \mathrm{yr}^{-1} ), and is independent of the assumed distance to \object{V444 Cyg}. The fits did not allow a unique value for the radius of the W-R star to be derived. The range of the volume filling factor for the W-R star atmosphere is estimated to be in the range of 0.050 (for R_{\WR}=5.0 R_{\sun}) to 0.075 (for R_{\WR}=2.5 R_{\sun}). We also found that the blue-side of \HeI (5876 ) \AA and \HeII (5412) \AA lines at phase 0.8 is relatively unaffected by the emission from the wind-wind interaction zone and the absorption by the O-star atmosphere; hence, the profiles at this phase are suitable for spectral line fittings using a spherical radiative transfer model.Comment: 18 pages, 17 figures: Accepeted for publication in A&

Microfluidic active loading of single cells enables analysis of complex clinical specimens

A fundamental trade-off between flow rate and measurement precision limits performance of many single-cell detection strategies, especially for applications that require biophysical measurements from living cells within complex and low-input samples. To address this, we introduce ‘active loading’, an automated, optically-triggered fluidic system that improves measurement throughput and robustness by controlling entry of individual cells into a measurement channel. We apply active loading to samples over a range of concentrations (1–1000 particles μL[superscript −1]), demonstrate that measurement time can be decreased by up to 20-fold, and show theoretically that performance of some types of existing single-cell microfluidic devices can be improved by implementing active loading. Finally, we demonstrate how active loading improves clinical feasibility for acute, single-cell drug sensitivity measurements by deploying it to a preclinical setting where we assess patient samples from normal brain, primary and metastatic brain cancers containing a complex, difficult-to-measure mixture of confounding biological debris.National Cancer Institute (U.S.) (R01 CA170592)National Cancer Institute (U.S.) (R33 CA191143)National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)Bridge Projec

Microfluidic active loading of single cells enables analysis of complex clinical specimens

A fundamental trade-off between flow rate and measurement precision limits performance of many single-cell detection strategies, especially for applications that require biophysical measurements from living cells within complex and low-input samples. To address this, we introduce ‘active loading’, an automated, optically-triggered fluidic system that improves measurement throughput and robustness by controlling entry of individual cells into a measurement channel. We apply active loading to samples over a range of concentrations (1–1000 particles μL[superscript −1]), demonstrate that measurement time can be decreased by up to 20-fold, and show theoretically that performance of some types of existing single-cell microfluidic devices can be improved by implementing active loading. Finally, we demonstrate how active loading improves clinical feasibility for acute, single-cell drug sensitivity measurements by deploying it to a preclinical setting where we assess patient samples from normal brain, primary and metastatic brain cancers containing a complex, difficult-to-measure mixture of confounding biological debris.National Cancer Institute (U.S.) (R01 CA170592)National Cancer Institute (U.S.) (R33 CA191143)National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)Bridge Projec