Photosynthesis regulation in response to fluctuating light in the secondary endosymbiont alga Nannochloropsis gaditana

In nature, photosynthetic organisms are exposed to highly dynamic environmental conditions where the excitation energy and electron flow in the photosynthetic apparatus need to be continuously modulated. Fluctuations in incident light are particularly challenging since they drive oversaturation of photosynthesis, with consequent oxidative stress and photoinhibition. Plants and algae have evolved several mechanisms to modulate their photosynthetic machinery to cope with light dynamics, such as thermal dissipation of excited chlorophyll states (Non-Photochemical Quenching, NPQ) and regulation of electron transport. The regulatory mechanisms involved in the response to light dynamics have adapted during evolution and exploring biodiversity is a valuable strategy for expanding our understanding of their biological roles. In this work, we investigated the response to fluctuating light in Nannochloropsis gaditana, a eukaryotic microalga of the phylum Heterokonta originating from a secondary endosymbiotic event. N. gaditana is negatively affected by light fluctuations, leading to large reductions in growth and photosynthetic electron transport. Exposure to light fluctuations specifically damages photosystem I, likely because of ineffective regulation of electron transport in this species. The role of Non-Photochemical Quenching, also assessed using a mutant strain specifically depleted of this response, was instead found to be minor, especially in responding to the fastest light fluctuations

Atypical Bilateral Femur Fractures in a Long-Term Bisphosphonate Therapy: A Case Report

Atypical Femur Fractures (AFF) are associated with Bisphosphonate Osteoporosis Therapy. Bisphosphonate therapy is widely used as the Gold-Standard Therapy for Osteoporosis: it increases bone density and reduce the risk of vertebral, non-vertebral and hip fractures. However, long-term alendronic acid administration can causes severely suppressed bone turnover and finally non-traumatic stress fractures. Here we present a case of Non-Traumatic stress fractures of bilateral femoral shafts in a Long-Term Alendronic Acid Therapy

Progetto di tirocinio laurea triennale in Fisica: Rilevamento automatico di scariche atmosferiche registrate negli spettrogrammi ‘CALLISTO’ tramite tecniche di machine-learning/deep-learning

Un solar radio burst (SRB) è un’ intensa emissione radio solare spesso correlata a un brillamento solare. Il rilevamento di SRBs puo’ essere effettuato tramite radiometri e spettrometri terrestri. CALLISTO e' uno spettrometro a basso costo progettato presso il Politecnico di Zurigo. Gli strumenti CALLISTO attivi in questo momento sono 67, distribuiti in tutto il mondo e permettono il monitoraggio delle emissioni radio solari 24h/7 tramite la rete e-Callisto http://www.e-callisto.org/. La Stazione Osservativa di Basovizza di INAF – Osservatorio Astronomico di Trieste e’ equipaggiata con tre spettrometri tipo CALLISTO operanti rispettivamente nelle bande VHF, UHF, L. E’ attivo anche un sistema sperimentale di rilevamento automatico di SRBs. I radiospettri acquisiti dagli spettrometri sono purtroppo affetti da disturbi ed interferenze a radio frequenza (RFI) che a volte vengono interpretati dal sistema come burst/falsi positivi. Tra questi le scariche atmosferiche, rilevate dagli spettrometri come emissioni lineari su tutto lo spettro. Il loro riconoscimento ed eliminazione puo’ contribuire in maniera importante a diminuire il numero di falsi positivi rilevati. Tra i vari possibili metodi di riconoscimento, tenuto anche conto del numero di eventi a disposizione per costruire un training set di numerosità adeguata, si e’ pensato di usare un sistema basato sul deep learning. Il lavoro effettuato nell’ambito del tirocinio, dopo l’acquisizione delle necessarie conoscenze di base (solar radio burst, documentazione CALLISTO, reti neurali, deep-learning) ha consentito la costruzione di training/test set di eventi ed una sperimentazione pilota su dati limitati con sviluppo ed esecuzione di modelli Keras su una virtual machine Virtualbox Ubuntu64 18.04 LTS, precedentemente installata ed attrezzata con librerie TensorFlow/Keras, propedeutica ad una sperimentazione completa su una Deep-Learning Machine fisica dedicata (CPU Xeon + GPU NVIDIA Quadro P4000)

Relationship between hospital volume and short-term outcomes: A nationwide population-based study including 75,280 rectal cancer surgical procedures

There is growing interest on the potential relationship between hospital volume (HV) and outcomes as it might justify the centralization of care for rectal cancer surgery. From the National Italian Hospital Discharge Dataset, data on 75,280 rectal cancer patients who underwent elective major surgery between 2002 and 2014 were retrieved and analyzed. HV was grouped into tertiles: low-volume performed 1-12, while high-volume hospitals performed 33+ procedures/year. The impact of HV on in-hospital mortality, abdominoperineal resection (APR), 30-day readmission, and length of stay (LOS) was assessed. Risk factors were calculated using multivariate logistic regression. The proportion of procedures performed in low-volume hospitals decreased by 6.7 percent (p<0.001). The rate of in-hospital mortality, APR and 30-day readmission was 1.3%, 16.3%, and 7.2%, respectively, and the median LOS was 13 days. The adjusted risk of in-hospital mortality (OR = 1.49, 95% CI = 1.25-1.78), APR (OR 1.10, 95%CI 1.02-1.19), 30-day readmission (OR 1.49, 95%CI 1.38-1.61), and prolonged LOS (OR 2.29, 95%CI 2.05-2.55) were greater for low-volume hospitals than for high-volume hospitals. This study shows an independent impact of HV procedures on all short-term outcome measures, justifying a policy of centralization for rectal cancer surgery, a process which is underwa

Dissecting the effect of soil on plant phenology and berry transcriptional plasticity in two Italian grapevine varieties (Vitis vinifera L.)

Grapevine embodies a fascinating species as regards phenotypic plasticity and genotype-per-environment interactions. The terroir, namely the set of agri-environmental factors to which a variety is subjected, can influence the phenotype at the physiological, molecular, and biochemical level, representing an important phenomenon connected to the typicality of productions. We investigated the determinants of plasticity by conducting a field-experiment where all terroir variables, except soil, were kept as constant as possible. We isolated the effect of soils collected from different areas, on phenology, physiology, and transcriptional responses of skin and flesh of a red and a white variety of great economic value: Corvina and Glera. Molecular results, together with physio-phenological parameters, suggest a specific effect of soil on grapevine plastic response, highlighting a higher transcriptional plasticity of Glera in respect to Corvina and a marked response of skin compared to flesh. Using a novel statistical approach, we identified clusters of plastic genes subjected to the specific influence of soil. These findings could represent an issue of applicative value, posing the basis for targeted agricultural practices to enhance the desired characteristics for any soil/cultivar combination, to improve vineyards management for a better resource usage and to valorize vineyards uniqueness maximizing the terroir-effect

SoK: Methods for Sampling Random Permutations in Post-Quantum Cryptography

In post-quantum cryptography, permutations are frequently employed to construct cryptographic primitives. Careful design and implementation of sampling random unbiased permutations is essential for efficiency and protection against side-channel attacks. Nevertheless, there is a lack of systematic research on this topic. Our work seeks to fill this gap by studying the most prominent permutation sampling algorithms and assessing their advantages and limitations. We combine theoretical and experimental comparisons and provide a C library with the implementations of the algorithms discussed. Furthermore, we introduce a new sampling algorithm tailored for cryptographic applications

Enabling PERK on Resource-Constrained Devices

PERK is a digital signature scheme submitted to the recent NIST Post-Quantum Cryptography Standardization Process for Additional Digital Signature Schemes. For NIST security level I, PERK features sizes ranging from 6kB to 8.5kB, encompassing both the signature and public key, depending on the parameter set. Given its inherent characteristics, PERK\u27s signing and verification algorithms involve the computation of numerous large objects, resulting in substantial stack-memory consumption ranging from 300kB to 1.5MB for NIST security level I and from 1.1MB to 5.7MB for NIST security level V. In this paper, we present a memory-versus-performance trade-off strategy that significantly reduces PERK\u27s memory consumption to a maximum of approximately 82kB for any security level, enabling PERK to be executed on resource-constrained devices. Additionally, we explore various optimizations tailored to the Cortex M4 and introduce the first implementation of PERK designed for this platform