6 research outputs found
Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma : an analysis of the Spanish Myeloma Group
An analysis of the impacts of climatic variability and hydrology on the coastal fisheries, Engraulis encrasicolus and Sepia officinalis, of Portugal
The notion that climate change may impact coastal fish production suggests a need to understand how climatic variables may influence fish catches at different time scales. Evidence suggests that the effect of climatic variability and fishing effort on landed catches (as proxy of fish abundance) may vary at the regional scale. This study aims to assess the sensibility of two commercial species with a short life cycle (Engraulis encrasicolus and Sepia officinalis) to climatic and fisheries effects across different regions of the coast of Portugal: northwestern, southwestern and southern Portugal. The effect of environmental explanatory variables, i.e. NAO index, sea surface temperature (SST), upwelling (UPW) index, river discharge, wind magnitude (WmaG), wind direction (Wdir), and fishing variables (fishing effort) on catch rates time series were studied between 1989 and 2009. The sensibility of the species studied to climatic variability differed among regions and were explained by different climatic variables. River discharge had a significant effect on catch rates of the two species, region independently. However, wind driven phenomenon and UPW were the variables that better explained the observed fishing trends across the three regions. Changes in catch rate trends among the studied regions, at a given time, were mostly associated with the reproduction periods of the species. Therefore, regional analyses will significantly contribute to a better understanding of the relationship between climate change and coastal fisheries, aiming to improve integrated coastal zone management
Prognostic Value of Serum Paraprotein Response Kinetics in Patients With Newly Diagnosed Multiple Myeloma
Response kinetics is not well-established as a prognostic marker in multiple myeloma (MM). We developed a mathematical model to assess the prognostic value of serum monoclonal component (MC) response kinetics during 6 induction cycles in 373 newly diagnosed MM patients. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent, dividing the patients into two kinetics categories with significantly different progression-free survival (PFS). Introduction: Response kinetics is a well-established prognostic marker in acute lymphoblastic leukemia. The situation is not clear in multiple myeloma (MM) despite having a biomarker for response monitoring (monoclonal component [MC]). Materials and Methods: We developed a mathematical model to assess the prognostic value of serum MC response kinetics during 6 induction cycles, in 373 NDMM transplanted patients treated in the GEM2012Menos65 clinical trial. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent. Results: Two patient subgroups were defined based on low and high resistance, that respectively captured sensitive and refractory kinetics, with progression-free survival (PFS) at 5 years of 72% and 59% (HR 0.64, 95% CI 0.44-0.93; P =.02). Resistance significantly correlated with depth of response measured after consolidation (80.9% CR and 68.4% minimal residual disease negativity in patients with sensitive vs. 31% and 20% in those with refractory kinetics). Furthermore, it modulated the impact of reaching CR after consolidation; thus, within CR patients those with refractory kinetics had significantly shorter PFS than those with sensitive kinetics (median 54 months vs. NR; P =.02). Minimal residual disease negativity abrogated this effect. Our study also questions the benefit of rapid responders compared to late responders (5-year PFS 59.7% vs. 76.5%, respectively [P <.002]). Of note, 85% of patients considered as late responders were classified as having sensitive kinetics. Conclusion: This semi-mechanistic modeling of M-component kinetics could be of great value to identify patients at risk of early treatment failure, who may benefit from early rescue intervention strategies. (C) 2022 The Authors. Published by Elsevier Inc
Characterisation of the lactation curve of Gyr and Sardo Negro cattle
The objectives were to characterize the lactation curves (LC) of tropical Gyr and Sardo Negro (SN) cattle from Mexico for the design of breeding and management programs for these breeds. A total of 3561 records of 504 lactations and 3927 records of 449 lactations were used for Gyr and SN, respectively. Three lactation lengths (LL) were evaluated, namely 240 (240d), 270 (270d), and 300 (300d) days, with five non-linear models (NLM): Wood, Wiltmink, Cobby, Brody, and Sikka. Milk production was obtained at the beginning (PI; kg), daily average (PMD; kg), maximum at peak (PMX; kg), days to reach maximum production (DP), and accumulated total (PT; kg). The selection of models was made based in the Akaike and Bayesian information criteria. The NLM explained at least 88% of the variability in the data. Brody model provided the best fit for 240d and 270d, and Sikka for 300d in SN; for Gyr, Wood model showed the best fit for 240d and 270d, while Wiltmink had the best fit for 300d. The means for PMD were 5.3 kg in SN and 10.2 kg in Gyr; for PMX the averages were 6.9 kg and 12.7 kg, respectively. The average of PT, within LL (240d, 270d, and 300d), was 1297 kg, 1418 kg, and 1552 kg for SN, and 2653 kg, 2930 kg, and 3202 kg for Gyr, respectively. The first third of the LC presented the highest contribution (%), with average values of 37.4 in Gyr and 39.5 in SN; the second and third periods, contributed (%) 33.5 and 29.1 in Gyr, and 33.0 and 27.5 in SN, respectively. The 240d LL, are the proposals for the design of management, feeding, and genetic improvement programs, they presented the best statistical adjustment in both breeds
Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance
Tumor recognition by T cells is essential for antitumor immunity. A comprehensive characterization of T cell diversity may be key to understanding the success of immunomodulatory drugs and failure of PD-1 blockade in tumors such as multiple myeloma (MM). Here, we use single-cell RNA and T cell receptor sequencing to characterize bone marrow T cells from healthy adults (n = 4) and patients with precursor (n = 8) and full-blown MM (n = 10). Large T cell clones from patients with MM expressed multiple immune checkpoints, suggesting a potentially dysfunctional phenotype. Dual targeting of PD-1 + LAG3 or PD-1 + TIGIT partially restored their function in mice with MM. We identify phenotypic hallmarks of large intratumoral T cell clones, and demonstrate that the CD27 and CD27 T cell ratio, measured by flow cytometry, may serve as a surrogate of clonal T cell expansions and an independent prognostic factor in 543 patients with MM treated with lenalidomide-based treatment combinations
Prognostic Value of Serum Paraprotein Response Kinetics in Patients With Newly Diagnosed Multiple Myeloma
Introduction: Response kinetics is a well-established prognostic marker in acute lymphoblastic leukemia. The situation is not clear in multiple myeloma (MM) despite having a biomarker for response monitoring (monoclonal component [MC]). Materials and Methods: We developed a mathematical model to assess the prognostic value of serum MC response kinetics during 6 induction cycles, in 373 NDMM transplanted patients treated in the GEM2012Menos65 clinical trial. The model calculated a "resistance" parameter that reflects the stagnation in the response after an initial descent. Results: Two patient subgroups were defined based on low and high resistance, that respectively captured sensitive and refractory kinetics, with progression-free survival (PFS) at 5 years of 72% and 59% (HR 0.64, 95% CI 0.44-0.93; P =.02). Resistance significantly correlated with depth of response measured after consolidation (80.9% CR and 68.4% minimal residual disease negativity in patients with sensitive vs. 31% and 20% in those with refractory kinetics). Furthermore, it modulated the impact of reaching CR after consolidation; thus, within CR patients those with refractory kinetics had significantly shorter PFS than those with sensitive kinetics (median 54 months vs. NR; P =.02). Minimal residual disease negativity abrogated this effect. Our study also questions the benefit of rapid responders compared to late responders (5-year PFS 59.7% vs. 76.5%, respectively [P <.002]). Of note, 85% of patients considered as late responders were classified as having sensitive kinetics. Conclusion: This semi-mechanistic modeling of M-component kinetics could be of great value to identify patients at risk of early treatment failure, who may benefit from early rescue intervention strategies