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Abstract Background COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) represents the biggest global health emergency in recent decades. The host immune response to SARS-CoV-2 seems to play a key role in disease pathogenesis and clinical manifestations, with Natural Killer (NK) lymphocytes being among the targets of virus-induced regulation. Methods This study performed a single-cell multi-omics analysis of transcripts and proteins of NK lymphocytes in COVID-19 patients, for the characterization of the innate immunological response to infection. NK cells were isolated from peripheral blood samples collected from adult subjects divided into 3 study groups: (1) non-infected subjects (Naïve group, n = 3), (2) post COVID-19 convalescent subjects (Healed group, n = 3) and (3) patients that were vaccinated against SARS-CoV-2 (Vaccine group, n = 3). Cells were then analysed by the BD Rhapsody System for the single-cell multi-omics investigation of transcriptome and membrane proteins. Results The bioinformatic analysis identified 5 cell clusters which differentially expressed gene/protein markers, defining NK cell subsets as “Active NK cells” and “Mature NK cells”. Calculating the relative proportion of each cluster within patient groups, more than 40% of the Naïve group cell population was found to belong to Mature NKs, whereas more than 75% of the Vaccine group cell population belonged to the cluster of Active NKs. Regarding the Healed group, it seemed to show intermediate phenotype between Active and Mature NK cells. Differential expression of specific genes, proteins and signaling pathways was detected comparing the profile of the 3 experimental groups, revealing a more activated NK cell phenotype in vaccinated patients versus recovered individuals. Conclusions The present study detected differential expression of NK cell markers in relation to SARS-CoV-2 infection and vaccine administration, suggesting the possibility to identify key molecular targets for clinical-diagnostic use of the individual response to viral infection and/or re-infection.

Background:. Recent advances in robotic microsurgery have enabled the application of robotic technology in central lymphatic reconstruction. Although the use of microsurgical robots demands careful consideration of associated costs and potentially prolonged operating times, it may offer improved surgical approaches and enhanced accessibility to deeper anatomical structures such as the thoracic duct (TD). Methods:. We report on successful reconstruction of the central lymphatic system using the Symani Surgical System in four patients with lesions of the central lymphatic system. The patients were of different age (range: 8 mo–60 y) and had variable conditions, including central conducting lymphatic anomaly and other rare anomalies of the central lymphatic pathways. Results:. Depending on the underlying pathology, a cervical access (n = 1) or median laparotomy (n = 3) was chosen to access the TD and perform anastomosis with a nearby vein. In all patients, anastomoses were patent, and chyle leakage decreased postoperatively. From a surgical perspective, the Symani Surgical System improved the precision of the microsurgeon and accessibility to the deep-lying TD. Conclusion:. Considering the high morbidity and rarity of pathologies of the central lymphatic system, robotic-assisted microsurgery holds substantial promise in expanding and improving the microsurgical treatment for central lymphatic anomalies.

Carbon nanotubes (CNT) are promising electroconductive nano-scale materials for neuroregeneration. Herein, we report on a new electroconductive composite scaffold made of the polymer 1% oxidized polyvinyl alcohol (OxPVA) combined with functionalized water soluble multiwalled CNT (OxPVA + MWCNT-S) (diazotization reaction). Preliminarily, MWCNT-S were characterized to evaluate the reaction outcome, the degree of functionalization and the dispersibility in water. Thereafter, OxPVA + MWCNT-S nanocomposite membranes were fabricated and analyzed for physicochemical properties (Raman spectroscopy, thermal decomposition, calorimetric properties, electroconductivity), macroscopic appearance and ultrastructure, mechanical behavior, in vitro cytotoxicity and in vivo biocompatibility. In parallel, OxPVA + MWCNT-S membranes with a linear pattern were also developed and analyzed for interaction with SH-SY5Y cells. Compared to OxPVA, the presence of MWCNT-S (only 0.016 wt%) significantly increased polymer conductivity and imparted a certain porosity without altering mechanical behaviour, as corroborated by uniaxial tensile tests. Neither cytotoxicity nor local signs of inflammation were detected in vitro and after subcutaneous implantation (14 and 42 days), proving composite material biocompatibility. OxPVA + MWCNT-S nanocomposite revealed as promising for future electroconductive conduits free from toxic effects amenable to CNT agglomeration within the polymer. Ideally, nerve lesions with wide gaps, may be effectively supported by those “active” devices, overcoming limitations of the available ones. Despite preliminary data, the presence of a linear pattern confirmed to have a beneficial effect over the scaffold/cells interaction.

Photoexcited triplet states of porphyrins are of great relevance in various applications due to their high yield, long lifetime, and strong electron spin polarization. This study delves into properties and spin dynamics of the triplet state of a series of hypervalent phosphorus(V) porphyrins. Transient Electron Paramagnetic Resonance (TrEPR) measurements, supported by quantum chemical calculations as well as by optical absorption/luminescence experiments, reveal that, unlike singlet states, the lowest triplet state does not exhibit charge-transfer (CT) character upon photoexcitation. However, the presence of excited CT singlet states alters the intersystem crossing in phosphorus(V) porphyrins, leading to a sign change in the initial multiplet polarization of the photoexcited triplet state. TrEPR results further demonstrate that significant net polarization develops in the triplet states of the phosphorus(V) porphyrins due to the dynamic Jahn-Teller effect. Yet, this effect remains largely unaffected by differences in their molecular structures.

The liver is an essential organ of the body that performs several vital functions, including the metabolism of biomolecules, foreign substances, and toxins, and the production of plasma proteins, such as coagulation factors. There are hundreds of genetic disorders affecting liver functions and, for many of them, the only curative option is orthotopic liver transplantation, which nevertheless entails many risks and long-term complications. Some peculiar features of the liver, such as its large blood flow supply and the tolerogenic immune environment, make it an attractive target for in vivo gene therapy approaches. In recent years, several genome-editing tools mainly based on the clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR-Cas9) system have been successfully exploited in the context of liver-directed preclinical or clinical therapeutic applications. These include gene knock-out, knock-in, activation, interference, or base and prime editing approaches. Despite many achievements, important challenges still need to be addressed to broaden clinical applications, such as the optimization of the delivery methods, the improvement of the editing efficiency, and the risk of on-target or off-target unwanted effects and chromosomal rearrangements. In this review, we highlight the latest progress in the development of in vivo liver-targeted genome editing approaches for the treatment of genetic disorders. We describe the technological advancements that are currently under investigation, the challenges to overcome for clinical applicability, and the future perspectives of this technology.

Introduction Insomnia is highly prevalent among individuals with Attention-Deficit/Hyperactivity Disorder (ADHD). However, the biological mechanisms shared between both conditions is still elusive. We aimed to investigate whether insomnia's genomic component is able to predict ADHD in childhood and adolescence.

Concept drifts can occur due to various factors such as changes in the environment or sensor degradation, posing significant challenges to machine learning systems by potentially skewing decision-making processes. Therefore, detecting drifts is essential to maintain the integrity and functionality of these systems. Automatic detectors based on statistical information are usually used to accomplish this task. Optimizing drift detectors through tuning is crucial for effective concept drift analysis. However, relying on user expertise or labeled data for supervised tuning can be challenging. In such cases, the use of unsupervised tuning methods becomes a suitable alternative to adapt detectors to evolving data distributions. To address this gap in the literature an unsupervised tuning method was proposed, leveraging a time series segmentation method. This innovative approach aims to alleviate the reliance on labeled data or user expertise traditionally associated with supervised methods, offering a more adaptive and automated means of tuning detectors. Our results demonstrate that our proposed approach outperforms the default configuration in most evaluated cases. Furthermore, we show that our approach can improve the hyperparameter tuning process when the type of drift is known including supervised methods such as Random Search tuning. By adopting our approach, we can achieve better performance in drift detection and improve the accuracy and reliability of systems that rely on this critical task.

Machine learning models are routinely integrated into process mining pipelines to carry out tasks like data transformation, noise reduction, anomaly detection, classification, and prediction. Often, the design of such models is based on some ad-hoc assumptions about the corresponding data distributions, which are not necessarily in accordance with the non-parametric distributions typically observed with process data. Moreover, mainstream machine-learning approaches tend to ignore the challenges posed by concurrency in operational processes. Data encoding is a key element to smooth the mismatch between these assumptions but its potential is poorly exploited. In this paper, we argue that a deeper understanding of the challenges associated with training machine learning models on process data is essential for establishing a robust integration of process mining and machine learning. Our analysis aims to lay the groundwork for a methodology that aligns machine learning with process mining requirements. We encourage further research in this direction to advance the field and effectively address these critical issues.

The nectarivorous common sunbird asity (Neodrepanis coruscans) is phylogenetically closely related to the frugivorous velvet asity (Philepitta castanea), yet it shares similar habitat and foraging behaviour as the Malagasy sunbirds (Cinnyris spp.). As ecological factors have been shown to influence blood parasite prevalence, it should be tested whether parasite abundance, prevalence and diversity of N. coruscans are more similar to the sunbirds than to its relative. Therefore, blood samples (n = 156) and smears (n = 60) were tested for different blood parasites (Haemosporida, trypanosomes, filarioid nematodes) using molecular and microscopic methods. High prevalence of haemosporidian parasites was observed in all bird taxa, with rates ranging from 23% in N. coruscans to 84.6% in C. notatus. The Malagasy Cinnyris spp. exhibited a high occurrence of mixed haemosporidian infections (>76%) with various specialized lineages. Within the Philepittidae family, no Haemoproteus infection was detected and just a few cases of mixed infections. Nectariniidae species predominantly had specialized haemosporidian lineages, while Philepittidae had infections mainly caused by generalist lineages. These findings emphasize the diverse range of blood parasites in Nectariniidae, while additionally highlighting the high diversity of trypanosomes and filarioid nematodes in Philepittidae. Additionally, several newly discovered haemosporidian lineages, Trypanosoma isolates and filarioid nematode isolates were identified. Notably, Philepittidae exhibited a lower prevalence of avian haemosporidian parasites compared to Nectariniidae, possibly due to potential resistance mechanisms. Despite N. coruscans sharing similar habitat and behavioural ecology with both Cinnyris spp., it closely resembles its relative, P. castanea, in all aspects of haemosporidian parasitism.