The objectives of this work were to establish a biostratigraphic framework for the 1-UN-24-PI well, to suggest a new biostratigraphic approach to the study of the upper Aptian, Lower Cretaceous, and ...also to provide new paleoecological inferences based on ostracods for the Codó Formation in the Parnaíba Basin, NE Brazil. The described ostracod assemblages were recovered from 24 core samples, and are mainly represented by species of Harbinia. The identified species allowed recognition of the Harbinia spp. 201-218 Biozone. The last occurrences of Harbinia crepata and Harbinia micropapillosa are suggested as potential chronostratigraphic markers. A lagoon with brackish permanent waters and with permanent hydrologic connection (saline groundwaters) but intermittent direct connection to the sea is newly proposed as a paleoenvironmental model for the Codó Formation in the studied area.
•Quantitative analysis of Codó Formation ostracods.•Harbinia spp. 201-218 Biozone.•Brackish lagoonal paleoenvironments.
Rice is a major staple food across the globe. Its growth and productivity is highly dependent on the rhizobiome where crosstalk takes place between plant and the microbial community. Such ...interactions lead to selective enrichment of plant beneficial microbes which ultimately defines the crop health and productivity. In this study, rhizobiome modulation is documented throughout the development of rice plant. Based on 16S rRNA gene affiliation at genus level, abundance, and diversity of plant growth promoting bacteria increased during the growth stages. The observed α diversity and rhizobiome complexity increased significantly (
p
< 0.05) during plantation. PCoA indicates that different geographical locations shared similar rhizobiome diversity but exerted differential enrichment (
p
< 0.001). Diversity of enriched genera represented a sigmoid curve and subsequently declined after harvest. A major proportion of dominant enriched genera (
p
< 0.05, abundance > 0.1%), based on 16S rRNA gene, were plant growth promoting bacteria that produces siderophore, indole-3-acetic acid, aminocyclopropane-1-carboxylic acid, and antimicrobials. Hydrogenotrophic methanogens dominated throughout cultivation. Type I methanotrophs (
n
= 12) had higher diversity than type II methanotrophs (
n
= 6). However, the later had significantly higher abundance (
p
= 0.003). Strong enrichment pattern was also observed in type I methanotrophs being enriched during water logged stages. Ammonia oxidizing Archaea were several folds more abundant than ammonia oxidizing bacteria. K-strategists
Nitrosospira
and
Nitrospira
dominated ammonia and nitrite oxidizing bacteria, respectively. The study clarifies the modulation of rhizobiome according to the rice developmental stages, thereby opening up the possibilities of bio-fertilizer treatment based on each cultivation stages.
Background: The International Prognostic Scoring System (IPSS) for MDS has recently been revised (IPSS-R). However both scoring systems were developed after exclusion of therapy-related cases and ...data on its usefulness in treatment-related MDS (tMDS) is limited.
Aims and Methods: We analyzed 1837 pts from Spanish, German, Swiss, Austrian, US, Italian, and Dutch centers diagnosed 1975-2015. Complete data to calculate the IPSS/-R was available in 1511 pts. The impact of prognostic features was analyzed by uni- and multivariable models and estimated by a measure of concordance for censored data (Dxy).
Results: Median age was 68 years. 1% of pts had 5q-syndrome, 13% RCUD, 4% RARS, 27% RCMD/-RS, 18% RAEB 1, 18% RAEB 2, 4% CMML 1, 2% CMML 2, 3% MDS-U, and 7% AML (RAEB-T) according to WHO-classification. Regarding cytogenetics 38% exhibited good, 14% intermediate, and 48% poor-risk according to IPSS, and 2% very good, 36% good, 17% intermediate, 15% poor, and 31% very poor according to IPSS-R. Prognostic risk groups were 12% IPSS low, 34% int 1, 36% int 2, and 18% high, while the IPSS-R was very low in 8%, low in 20%, intermediate in 17%, high in 23%, and very high in 32%.
The most frequent primary diseases were NHL 28%, breast cancer 16%, myeloma 6%, prostate cancer 6%, Hodgkins disease 5%, and 4% gastrointestinal tumors. Patients received chemotherapy in 75% and radiotherapy in 47%. Regarding chemotherapeutic drugs, most pts received combination regimens containing alkylating agents in 65%, topoisomerase inhibitors in 44%, antitubulin agents in 26%, and antimetabolites in 26%.
Median follow-up from MDS diagnosis was 59 months, median survival 16 months. Since a disease altering treatment is, at least in higher risk disease, which is overrepresented in tMDS, standard of care, we decided to analyze treated as well as untreated pts to avoid a selection bias. This included stem cell transplantation in 16% with a median survival of 24 months.
Features with influence on survival and time to AML in univariable analysis included FAB, WHO, IPSS, IPSS-R, cytogenetics, hb, platelets, marrow and peripheral blasts, ferritin, LDH, fibrosis, ß2-microglobulin, and use of alkylating agents for the treatment of primary disease. For hemoglobin, platelets, LDH, fibrosis, and ß2-microglobulin the influence was stronger on survival. Year of diagnosis, age, gender, neutrophil count, WBC, use of chemo or radiotherapy as well as other chemotherapeutic agents had no marked influence on both outcomes.
According to our results, both the IPSS (Dxy 0.29 for survival, 0.32 for AML) and IPSS-R (Dxy 0.34, 0.32 for AML) perform moderately in tMDS, but not as well as in primary MDS (pMDS). Therefore, existing prognostic models need to be adjusted to tMDS. However, this appears to be not without difficulties. The scores tested, as well as most prognostic variables themselves perform inferior compared to pMDS. It becomes even more complicated since tMDS in itself is even more heterogeneous than pMDS. Scores and variables perform differently depending on the primary disease or therapy. The IPSS/-R and its variables perform for example better in pts with solid tumors compared to hematologic diseases or in pts who have received radio- instead of chemotherapy, but also in pts after prostate compared to breast cancer.
In addition to the integration of further variables, new cutoffs, or the weighting of existing variables, we are currently testing the possibility of separate score versions for different tMDS subgroups. Separate score versions for survival and time to AML would also give differing weights to most features. Hemoglobin, platelets and cytogenetics would get more weight for survival, while marrow blasts would be more important regarding AML.
Conclusion: In contrast to early descriptions of tMDS, with poor risk cytogenetics in the vast majority of pts and a uniformly poor prognosis, surprisingly we find good risk karyotypes in a relatively large number of pts. Although, poor risk cytogenetics are still overrepresented, this indicates, different types of tMDS exist. Our analysis shows that many variables exhibit prognostic influence in tMDS and the IPSS or preferably IPSS-R can be applied in these pts. However, the prognostic power of both scores is inferior compared to pMDS, making an optimized tMDS score reasonable. Currently data from further IWG centers is integrated in our database and further analyses are performed to propose a tMDS specific score.
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Komrokji:Novartis: Research Funding, Speakers Bureau; Pharmacylics: Speakers Bureau; Incyte: Consultancy; Celgene: Consultancy, Research Funding. Sekeres:TetraLogic: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Steensma:Celgene: Consultancy; Incyte: Consultancy; Amgen: Consultancy; Onconova: Consultancy. Valent:Novartis: Consultancy, Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Celgene: Honoraria. Platzbecker:Boehringer: Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Esteve:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.
Polyporus dictyopus, with a large number of heterotypic synonyms, has been traditionally considered a species complex, characterized by wide morphological variation and geographic distribution. Thus, ...neotropical specimens previously identified as P. dictyopus from Amazonia, Cerrado and Atlantic Forest biomes were studied based on detailed macro- and micromorphological examination and phylogenetic analyses, using distinct ribosomal and protein-coding genomic regions: the nuclear ribosomal internal transcribed spacer (nrITS), nuclear ribosomal large subunit (nrLSU), and RNA polymerase II second subunit (RPB2). Two unrelated generic lineages, each one represented by different species, are reported: Atroporus is recovered and re-circumscribed to include A. diabolicus and A. rufoatratus comb. nov.; Neodictyopus gen. nov. is proposed to accommodate N. dictyopus comb. nov. and two new species, N. atlanticae and N. gugliottae. Our study showed that at least five distinct species were hidden under the name P. dictyopus. Detailed descriptions, pictures, illustrations, and a key are provided for Atroporus and Neodictyopus species.
A steer-by-wire (SBW) control system is presented with emphasis on safety issues. The applications are in articulated vehicles such as the wheel type loaders, articulated trucks, and others. The ...electro-hydraulic (EH) power circuit is controlled by two embedded electronic control modules (ECM), the primary ECM and backup ECM. The two ECMs monitor each others condition. If one detects fault in the other, it takes over the control functions. There are two main control algorithms that run in the ECMs in real-time: the steering valve control algorithm and the failure detection algorithm. The valve control algorithm basically generates command signal to the steering valve based on operator steering column signal as well as other machine condition sensors.
The failure detection algorithm implements a fault detection logic for both input sensors and output drivers, and flags the corresponding warning for to the operator, and take a predefined action depending on the type of the failure detected. A unique fault strategy organization is implemented by inspecting the failure behavior on both the component and the system levels. The failure detection algorithm also determines the most likely “good” sensor signal from a set of redundant sensors for each critical measurement. Based on these good sensors data, the steering control algorithm sends two output signals: the control signal to the steering EH circuit valve and the control signal to the steering wheel force feedback device (i.e. a brake or a motor) to give operator feedback about the steering conditions.
Finite state machine (FSM) concept is used to design the fault handling algorithms for both the component level and the system level failure. The probability of the system being at normal steering state or at any other steering failure state is determined. Failure mode probabilities of steering system components are also determined.
Colorectal cancer (CRC) commonly arises in individuals with premalignant colon lesions known as polyps, with both conditions being influenced by gut microbiota. Host-related factors and inherent ...characteristics of polyps and tumors may contribute to microbiome variability, potentially acting as confounding factors in the discovery of taxonomic biomarkers for both conditions. In this study we employed shotgun metagenomics to analyze the taxonomic diversity of bacteria present in fecal samples of 90 clinical subjects (comprising 30 CRC patients, 30 with polyps and 30 controls). Our findings revealed a decrease in taxonomic richness among individuals with polyps and CRC, with significant dissimilarities observed among the study groups. We identified significant alterations in the abundance of specific taxa associated with polyps (Streptococcaceae,
, and
) and CRC (Lactobacillales, Clostridiaceae,
, SFB,
, and
). Clostridiaceae exhibited significantly lower abundance in the early stages of CRC. Additionally, our study revealed a positive co-occurrence among underrepresented genera in CRC, while demonstrating a negative co-occurrence between
and
, suggesting potential antagonistic relationships. Moreover, we observed variations in taxonomic richness and/or abundance within the polyp and CRC bacteriome linked to polyp size, tumor stage, dyslipidemia, diabetes with metformin use, sex, age, and family history of CRC. These findings provide potential new biomarkers to enhance early CRC diagnosis while also demonstrating how intrinsic host factors contribute to establishing a heterogeneous microbiome in patients with CRC and polyps.
‘Dirty lesions’ on the neck and abdomen Rosmaninho, Aristóteles; Carvalho, Sandrina
Journal of paediatrics and child health,
January 2017, 2017-Jan, 2017-01-00, 20170101, Letnik:
53, Številka:
1
Journal Article
Monofluoroacetate (MFA) is considered one of the most toxic substances known. It is found naturally in plants, and causes sudden death syndrome in ruminants. Due to hyperacute evolution of poisoning ...and the absence of effective treatment, induction of resistance in animals might be the best tool to control MFA poisoning in ruminants. The objective of this study was to promote resistance in cattle against the toxic effects of MFA through its degradation by the ruminal microbiota after the administration of sodium trifluoroacetate (TFA). Ten calves were distributed into two groups: control group (n = 3) and treated group (n = 7). The calves in the treated group received 0.1 mg/kg live weight of TFA, whereas, those in the control group received water; both for 28 consecutive days. The calves were subjected to daily clinical evaluation and weekly blood biochemical determination to identify any signs of poisoning. After 28 d of administration of TFA or water, 2.0 g/kg body weight of Palicourea marcgravii leaves (containing 0.15% MFA) were administered using a stomach tube to determine the occurrence of resistance. The administration of TFA did not induce any clinical or biochemical changes in blood. The administration of P. marcgravii induced clinical changes in the calves of control group, but there was no change in the calves of the treated group. In conclusion, the administration of TFA to cattle can induce effective resistance against MFA poisoning.
•Monofluoroacetate (MFA) is considered one of the most toxic substances known.•Plants containing MFA cause lethal poisoning in animals.•MFA degradation by the ruminal microbiota was induced by sodium trifluoroacetate (TFA) in calves.•The administration of TFA to cattle can induce effective resistance against MFA poisoning.
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