Morphological and phylogenetic data do not support the split of Alexandrium into four genera

A recently published study analyzed the phylogenetic relationship between the genera Centrodinium and Alexandrium, confirming an earlier publication showing the genus Alexandrium as paraphyletic. This most recent manuscript retained the genus Alexandrium, introduced a new genus Episemicolon, resurrected two genera, Gessnerium and Protogonyaulax, and stated that: “The polyphyly [sic] of Alexandrium is solved with the split into four genera”. However, these reintroduced taxa were not based on monophyletic groups. Therefore this work, if accepted, would result in replacing a single paraphyletic taxon with several non-monophyletic ones. The morphological data presented for genus characterization also do not convincingly support taxa delimitations. The combination of weak molecular phylogenetics and the lack of diagnostic traits (i.e., autapomorphies) render the applicability of the concept of limited use. The proposal to split the genus Alexandrium on the basis of our current knowledge is rejected herein. The aim here is not to present an alternative analysis and revision, but to maintain Alexandrium. A better constructed and more phylogenetically accurate revision can and should wait until more complete evidence becomes available and there is a strong reason to revise the genus Alexandrium. The reasons are explained in detail by a review of the available molecular and morphological data for species of the genera Alexandrium and Centrodinium. In addition, cyst morphology and chemotaxonomy are discussed, and the need for integrative taxonomy is highlighted

Pretreatment tissue TCR repertoire evenness is associated with complete pathologic response in patients with NSCLC receiving neoadjuvant chemoimmunotherapy

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER); Comunidad de Madrid. Consejería de Ciencia, Universidades e Innovación (PEJD-2019-PRE/BMD-17006).Purpose: Characterization of the T-cell receptor (TCR) repertoire may be a promising source for predictive biomarkers of pathologic response to immunotherapy in locally advanced non-small cell lung cancer (NSCLC). Experimental Design: In this study, next-generation TCR sequencing was performed in peripheral blood and tissue samples of 40 patients with NSCLC, before and after neoadjuvant chemoimmunotherapy (NADIM clinical trial, NCT03081689), considering their complete pathologic response (CPR) or non-CPR. Beyond TCR metrics, tissue clones were ranked by their frequency and spatiotemporal evolution of top 1% clones was determined. Results: We have found a positive association between an uneven TCR repertoire in tissue samples at diagnosis and CPR at surgery. Moreover, TCR most frequently ranked clones (top 1%) present in diagnostic biopsies occupied greater frequency in the total clonal space of CPR patients, achieving an AUC ROC to identify CPR patients of 0.967 (95% confidence interval, 0.897-1.000; P ¼ 0.001), and improving the results of PD-L1 tumor proportion score (TPS; AUC = 0.767; P = 0.026) or tumor mutational burden (TMB; AUC = 0.550; P = 0.687). Furthermore, tumors with high pretreatment top 1% clonal space showed similar immune cell populations but a higher immune reactive gene expression profile. Finally, the selective expansion of pretreatment tissue top 1% clones in peripheral blood of CPR patients suggests also a peripheral immunosurveillance, which could explain the high survival rate of these patients. Conclusions: We have identified two parameters derived from TCR repertoire analysis that could outperform PD-L1 TPS and TMB as predictive biomarkers of CPR after neoadjuvant chemoimmunotherapy, and unraveled possible mechanisms of CPR involving enhanced tumor immunogenicity and peripheral immunosurveillance

Prediction of long-term outcomes of HIV-infected patients developing non-AIDS events using a multistate approach

Outcomes of people living with HIV (PLWH) developing non-AIDS events (NAEs) remain poorly defined. We aimed to classify NAEs according to severity, and to describe clinical outcomes and prognostic factors after NAE occurrence using data from CoRIS, a large Spanish HIV cohort from 2004 to 2013. Prospective multicenter cohort study. Using a multistate approach we estimated 3 transition probabilities: from alive and NAE-free to alive and NAE-experienced ("NAE development"); from alive and NAE-experienced to death ("Death after NAE"); and from alive and NAE-free to death ("Death without NAE"). We analyzed the effect of different covariates, including demographic, immunologic and virologic data, on death or NAE development, based on estimates of hazard ratios (HR). We focused on the transition "Death after NAE". 8,789 PLWH were followed-up until death, cohort censoring or loss to follow-up. 792 first incident NAEs occurred in 9.01% PLWH (incidence rate 28.76; 95% confidence interval [CI], 26.80-30.84, per 1000 patient-years). 112 (14.14%) NAE-experienced PLWH and 240 (2.73%) NAE-free PLWH died. Adjusted HR for the transition "Death after NAE" was 12.1 (95%CI, 4.90-29.89). There was a graded increase in the adjusted HRs for mortality according to NAE severity category: HR (95%CI), 4.02 (2.45-6.57) for intermediate-severity; and 9.85 (5.45-17.81) for serious NAEs compared to low-severity NAEs. Male sex (HR 2.04; 95% CI, 1.11-3.84), ag

Main belt asteroids taxonomical information from Dark Energy Survey data

International audienceWhile proper orbital elements are currently available for more than 1 million asteroids, taxonomical information is still lagging behind. Surveys like SDSS-MOC4 provided preliminary information for more than 100,000 objects, but many asteroids still lack even a basic taxonomy. In this study, we use Dark Energy Survey (DES) data to provide new information on asteroid physical properties. By cross-correlating the new DES database with other databases, we investigate how asteroid taxonomy is reflected in DES data. While the resolution of DES data is not sufficient to distinguish between different asteroid taxonomies within the complexes, except for V-type objects, it can provide information on whether an asteroid belongs to the C- or S-complex. Here, machine learning methods optimized through the use of genetic algorithms were used to predict the labels of more than 68,000 asteroids with no prior taxonomic information. Using a high-quality, limited set of asteroids with data on $gri$ slopes and $i-z$ colors, we detected 409 new possible V-type asteroids. Their orbital distribution is highly consistent with that of other known V-type objects