28 research outputs found
Coping with tissue sampling in suboptimal conditions: Comparison of different tissue preservation methods for histological and molecular analysis
Evaluation of the effect of oxidative stress in blood serum and endometrial cells in cows with metritis
ADVANCED DEEP LEARNING COMPARISONS FOR NON-INVASIVE TUNNEL LINING ASSESSMENT FROM GROUND PENETRATING RADAR PROFILES
Innovative, automated, and non-invasive techniques have been developed by scientific community to indirectly assess structural conditions and support the decision-making process for a worthwhile maintenance schedule. Nowadays, machine learning tools are in the spotlight because of their outstanding capabilities to deal with data coming from even heterogeneous sources and their ability to extract information from the structural systems, providing highly effective, reliable, and efficient damage classification tools. In the current study, a supervised multi-level damage classification strategy has been developed regarding Ground Penetrating Radar (GPR) profiles for the assessment of tunnel lining conditions. In previous research, the authors firstly considered a convolutional neural network (CNN), adopting the quite popular ResNet-50, initialized through transfer learning. In the present work, further enhancements have been attempted by adopting two configurations of the newest state-of-art advanced neural architectures: the neural transformers. The foremost is the original Vision Transformer (ViT), whose core is an encoder entirely based on the innovative self-attention mechanism and does not rely on convolution at all. The second is an improvement of ViT which merges convolution and self-attention, the Compact Convolution Transformer (CCT). In conclusion, a critical discussion of the different pros and cons of adopting the above-mentioned different architectures is finally provided, highlighting the actual powerfulness of these technologies in the future civil engineering paradigm nevertheless
In the lycophyte Selaginella martensii is the "extra-qT" related to energy spillover? Insights into photoprotection in ancestral vascular plants
Lycophytes are early diverging vascular plants, representing a minor
group as compared to the dominating euphyllophytes, mostly angiosperms.
Having maximally developed in a CO2-rich atmosphere, extant
lycophytes are characterized by a low carbon fixing capacity, which is
compensated by a marked ability to induce the non-photochemical
quenching of chlorophyll fluorescence (NPQ). Different kinetic
components contribute to NPQ, in particular the fast relaxing
high-energy quenching qE, the middle relaxing qT, and the slowly
relaxing qI. Unlike angiosperms, lycophytes enhance the qT component
under high light, originating from an "extra-qT". In this research, we
analyze whether in Selaginella martensii the extra-qT can reflect a
photosystem (PS) I-based quenching mechanism activated upon saturation
of qE capacity. From comparative analyses of fluorescence quenching
parameters, carbon fixation, in vivo low- and room-temperature
fluorescence spectroscopy, and thylakoid protein phosphorylation, it is
proposed that the extra-qT is not mechanistically separate from the
ordinary qT. The results suggest a relationship between qT and
photoprotective energy spillover to PSI, which is activated upon sensing
the excitation energy pressure inside PSII and is possibly facilitated
by phosphorylation of Lhcb6, a minor antenna protein of PSII. Energy
spillover emphasizes 77K fluorescence emission from PSI core (F714) and
becomes more relevant at irradiance levels corresponding to the CO2-limited,
potentially photoinhibiting phase of photosynthesis. At the highest
irradiances, when Lhcb6 phosphorylation potential has been saturated,
the major LHCII increases in turn its phosphorylation level, probably
leading to the full exploitation of PSI as a safe excitation sink. It is
suggested that the low photosynthetic capacity of lycophytes could
allow an easier experimental access to the use of PSI as a safe
excitation quencher for PSII, a debated, emerging issue about thylakoid
photoprotection in angiosperms.</p
Expression of corticosteroid hormone receptors, prereceptors, and molecular chaperones in hypothalamic-pituitary-adrenal axis and adipose tissue after the administration of growth promoters in veal calves
Effects of feeding Spodoptera littoralis on lima bean leaves. III. Membrane depolarization and involvement of hydrogen peroxide
Prevalence of avian haemosporida lineages in hooded crows (Corvus cornix) from Piedmont region
Morphometric characterization of necrosis induced by perfused and non-perfused radiofrequency thermal ablation needles in liver on a swine in vivo model
Application of RNA-sequencing to identify biomarkers in broiler chickens prophylactic administered with antimicrobial agents
Antimicrobial (AM) resistance is largely acknowledged as one of the biggest global health and food safety challenges and the overuse of AMs is known to generate resistance in bacteria that may affect both animals and humans. Poultry meat is the second most-produced meat in the European Union and in recent years consumers are becoming more concerned about food safety, traceability, and animal welfare in poultry rearing system, increasingly requiring meats from broilers reared without AMs. In the present study, we performed RNA sequencing to analyze 64 liver and 54 muscle transcriptomic profiles in broilers reared without treatment or treated with different classes of AMs. Moreover, we validated the most differentially expressed genes among the treated groups to detect putative novel biomarkers able to discriminate meats of broilers reared without AMs. The PDK4, IGFBP1, and RHOB genes were identified as putative novel hepatic biomarkers, discriminating broilers treated with AMs compared to broilers reared without treatments. The whole transcriptome changes revealed the liver as a valuable target organ for AM administration screening. In addition, our results suggest a leading effect of the coccidiostat when associated with AMs, influencing several biological processes. Our study showed that RNA sequencing is a powerful and valuable method to detect aberrant regulated genes and to identify biomarker candidates for AM misuse detection in farm animals. Further validation on larger sample size and a wider spectrum of AMs are needed to confirm the viability of the aforementioned biomarkers in poultry population