Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunological Responses of Marine Bivalves to Contaminant Exposure: Contribution of the -Omics Approach

The increasing number of data studies on the biological impact of anthropogenic chemicals in the marine environment, together with the great development of invertebrate immunology, has identified marine bivalves as a key invertebrate group for studies on immunological responses to pollutant exposure. Available data on the effects of contaminants on bivalve immunity, evaluated with different functional and molecular endpoints, underline that individual functional parameters (cellular or humoral) and the expression of selected immune-related genes can distinctly react to different chemicals depending on the conditions of exposure. Therefore, the measurement of a suite of immune biomarkers in hemocytes and hemolymph is needed for the correct evaluation of the overall impact of contaminant exposure on the organism's immunocompetence. Recent advances in -omics technologies are revealing the complexity of the molecular players in the immune response of different bivalve species. Although different -omics represent extremely powerful tools in understanding the impact of pollutants on a key physiological function such as immune defense, the -omics approach has only been utilized in this area of investigation in the last few years. In this work, available information obtained from the application of -omics to evaluate the effects of pollutants on bivalve immunity is summarized. The data shows that the overall knowledge on this subject is still quite limited and that to understand the environmental relevance of any change in immune homeostasis induced by exposure to contaminants, a combination of both functional assays and cutting-edge technology (transcriptomics, proteomics, and metabolomics) is required. In addition, the utilization of metagenomics may explain how the complex interplay between the immune system of bivalves and its associated bacterial communities can be modulated by pollutants, and how this may in turn affect homeostatic processes of the host, host–pathogen interactions, and the increased susceptibility to disease. Integrating different approaches will contribute to knowledge on the mechanism responsible for immune dysfunction induced by pollutants in ecologically and economically relevant bivalve species and further explain their sensitivity to multiple stressors, thus resulting in health or disease.
New Insights Into Mitochondrial DNA Reconstruction and Variant Detection in Ancient Samples

Ancient DNA (aDNA) studies are frequently focused on the analysis of the mitochondrial DNA (mtDNA), which is much more abundant than the nuclear genome, hence can be better retrieved from ancient remains. However, postmortem DNA damage and contamination make the data analysis difficult because of DNA fragmentation and nucleotide alterations. In this regard, the assessment of the heteroplasmic fraction in ancient mtDNA has always been considered an unachievable goal due to the complexity in distinguishing true endogenous variants from artifacts. We implemented and applied a computational pipeline for mtDNA analysis to a dataset of 30 ancient human samples from an Iron Age necropolis in Polizzello (Sicily, Italy). The pipeline includes several modules from well-established tools for aDNA analysis and a recently released variant caller, which was specifically conceived for mtDNA, applied for the first time to aDNA data. Through a fine-tuned filtering on variant allele sequencing features, we were able to accurately reconstruct nearly complete (>88%) mtDNA genome for almost all the analyzed samples (27 out of 30), depending on the degree of preservation and the sequencing throughput, and to get a reliable set of variants allowing haplogroup prediction. Additionally, we provide guidelines to deal with possible artifact sources, including nuclear mitochondrial sequence (NumtS) contamination, an often-neglected issue in ancient mtDNA surveys. Potential heteroplasmy levels were also estimated, although most variants were likely homoplasmic, and validated by data simulations, proving that new sequencing technologies and software are sensitive enough to detect partially mutated sites in ancient genomes and discriminate true variants from artifacts. A thorough functional annotation of detected and filtered mtDNA variants was also performed for a comprehensive evaluation of these ancient samples.
Toward Machine-Learning-Based Decision Support in Diabetes Care: A Risk Stratification Study on Diabetic Foot Ulcer and Amputation

Diabetes mellitus is associated with serious complications, with foot ulcers and amputation of limbs among the most debilitating consequences of late diagnosis and treatment of foot ulcers. Thus, prediction and on-time treatment of diabetic foot ulcers (DFU) are of great importance for improving and maintaining patients' quality of life and avoiding the consequent socio-economical burden of amputation. In this study, we use Danish national registry data to understand the risk factors of developing diabetic foot ulcers and amputation among patients with diabetes. We analyze the data of 246,705 patients with diabetes to assess some of the main risk factors for developing DFU/amputation. We study the socioeconomic information and past medical history of the patients. Factors, such as low family disposable income, cardiovascular disorders, peripheral artery, neuropathy, and chronic renal complications are among the important risk factors. Mental disorders and depression, albeit not as pronounced, still pose higher risks in comparison to the group of people without these complications. We further use machine learning techniques to assess the practical usefulness of such risk factors for predicting foot ulcers and amputation. Finally, we outline the limitations of working with registry data sources and explain potentials for combining additional public and private data sources in future applications of artificial intelligence (AI) to improve the prediction of diabetic foot ulcers and amputation.
Nicotine Enhances Amplitude and Consistency of Timing of Responses to Acoustic Trains in A1

Systemic nicotine enhances neural processing in primary auditory cortex (A1) as determined using tone-evoked, current-source density (CSD) measurements. For example, nicotine enhances the characteristic frequency (CF)-evoked current sink in layer 4 of A1, increasing amplitude and decreasing latency. However, since presenting auditory stimuli within a stream of stimuli increases the complexity of response dynamics, we sought to determine the effects of nicotine on CSD responses to trains of CF stimuli (one-second trains at 2–40 Hz; each train repeated 25 times). CSD recordings were obtained using a 16-channel multiprobe inserted in A1 of urethane/xylazine-anesthetized mice, and analysis focused on two current sinks in the middle (layer 4) and deep (layers 5/6) layers. CF trains produced adaptation of the layer 4 response that was weak at 2 Hz, stronger at 5–10 Hz and complete at 20–40 Hz. In contrast, the layer 5/6 current sink exhibited less adaptation at 2–10 Hz, and simultaneously recorded auditory brainstem responses (ABRs) showed no adaptation even at 40 Hz. Systemic nicotine (2.1 mg/kg) enhanced layer 4 responses throughout the one-second stimulus train at rates ≤10 Hz. Nicotine enhanced both response amplitude within each train and the consistency of response timing across 25 trials. Nicotine did not alter the degree of adaptation over one-second trials, but its effect to increase amplitudes revealed a novel, slower form of adaptation that developed over multiple trials. Nicotine did not affect responses that were fully adapted (20–40 Hz trains), nor did nicotine affect any aspect of the layer 5/6 current sink or ABRs. The overall effect of nicotine in layer 4 was to enhance all responses within each train, to emphasize earlier trials across multiple trials, and to improve the consistency of timing across all trials. These effects may improve processing of complex acoustic streams, including speech, that contain information in the 2–10 Hz range.
Leveraging Geometry to Enable High-Strength Continuum Robots

Developing high-strength continuum robots can be challenging without compromising on the overall size of the robot, the complexity of design and the range of motion. In this work, we explore how the load capacity of continuum robots can drastically be improved through a combination of backbone design and convergent actuation path routing. We propose a rhombus-patterned backbone structure composed of thin walled-plates that can be easily fabricated via 3D printing and exhibits high shear and torsional stiffness while allowing bending. We then explore the effect of combined parallel and converging actuation path routing and its influence on continuum robot strength. Experimentally determined compliance matrices are generated for straight, translation and bending configurations for analysis and discussion. A robotic actuation platform is constructed to demonstrate the applicability of these design choices.
Vapour‐liquid equilibria: Systems: (1) Acetone‐ethyl acetate; (2) acetone‐n‐propyl acetate

Isobaric vapour-liquid equilibrium data have been determined for the binary systems acetone-ethyl acetate and acetone-n-propyl acetate at 760 mm. total pressure using a modified Colburn still. The vapour-liquid equilibrium data for both the systems are satisfactorily correlated by Wohl's two-suffix equations. The behaviour of both these systems, as well as that of acetone-n-butyl acetate reported earlier is in conformity with Ewell's classification of liquids, in exhibiting positive deviations.
Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists

The explosion of microbiome analyses has helped identify individual microorganisms and microbial communities driving human health and disease, but how these communities function is still an open question. For example, the role for the incredibly complex metabolic interactions among microbial species cannot easily be resolved by current experimental approaches such as 16S rRNA gene sequencing, metagenomics and/or metabolomics. Resolving such metabolic interactions is particularly challenging in the context of polymicrobial communities where metabolite exchange has been reported to impact key bacterial traits such as virulence and antibiotic treatment efficacy. As novel approaches are needed to pinpoint microbial determinants responsible for impacting community function in the context of human health and to facilitate the development of novel anti-infective and antimicrobial drugs, here we review, from the viewpoint of experimentalists, the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems. We use selected examples from the literature to illustrate how metabolic modeling has been utilized, in combination with experiments, to better understand microbial community function. Finally, we propose how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.
Endothelial Progenitor Cell-Derived Microvesicles Promote Angiogenesis in Rat Brain Microvascular Endothelial Cells In vitro

Brain microvascular endothelial cells (BMECs) are a major component of the blood-brain barrier that maintains brain homeostasis. Preserving and restoring the normal biological functions of BMECs can reverse or reduce brain injury. Endothelial progenitor cells (EPCs) may promote brain vascular remodeling and restore normal endothelial function. As a novel vehicle for cell-cell communication, microvesicles (MVs) have varied biological functions. The present study investigated the biological effects of EPC-derived MVs (EPC-MVs) on BMECs in vitro. We isolated MVs from the supernatant of EPCs in a serum-depleted medium. BMECs were cultured alone or in the presence of EPC-MVs. BMEC viability and proliferation were evaluated with the Cell Counting Kit-8 and by flow cytometry, and the proangiogenic effect of EPC-MVs on BMECs was assessed with the transwell migration, wound healing, and tube formation assays. Our results showed that EPC-derived MVs labeled with DiI were internalized by cultured BMECs; this enhanced BMEC viability and promoted their proliferation. EPC-MVs also stimulated migration and tube formation in BMECs. These results demonstrate that EPC-derived MVs exert a proangiogenic effect on BMECs, which has potential applications in cell-free therapy for brain injury.
Brain Ischemia as a Prelude to Alzheimer's Disease

Transient ischemic brain injury causes massive neuronal death in the hippocampus of both humans and animals. This was accompanied by progressive atrophy of the hippocampus, brain cortex, and white matter lesions. Furthermore, it has been noted that neurodegenerative processes after an episode of ischemia-reperfusion in the brain can continue well-beyond the acute stage. Rarefaction of white matter was significantly increased in animals at 2 years following ischemia. Some rats that survived 2 years after ischemia developed severe brain atrophy with dementia. The profile of post-ischemic brain neurodegeneration shares a commonality with neurodegeneration in Alzheimer's disease. Furthermore, post-ischemic brain injury is associated with the deposition of folding proteins, such as amyloid and tau protein, in the intracellular and extracellular space. Recent studies on post-ischemic brain neurodegeneration have revealed the dysregulation of Alzheimer's disease-associated genes such as amyloid protein precursor, α-secretase, β-secretase, presenilin 1, presenilin 2, and tau protein. The latest data demonstrate that Alzheimer's disease-related proteins and their genes play a key role in the development of post-ischemic brain neurodegeneration with full-blown dementia in disease types such as Alzheimer's. Ongoing interest in the study of brain ischemia has provided evidence showing that ischemia may be involved in the development of the genotype and phenotype of Alzheimer's disease, suggesting that brain ischemia can be considered as a useful model for understanding the mechanisms responsible for the initiation of Alzheimer's disease.
The Effects of the Fear of Missing Out on People's Social Networking Sites Use During the COVID-19 Pandemic: The Mediating Role of Online Relational Closeness and Individuals' Online Communication Attitude

Forced isolation induced by COVID-19 pandemic dramatically impacted individuals' well-being, reducing the opportunities for social encounters, consequently resulting in a greater use of social media in order to maintain social relationships. Although the range of friend-related activities appeared to be severely constrained during quarantine, the Fear of Missing Out (FoMO) needs to be carefully examined, especially in relation to problematic social networking site use (PSNSU). Indeed, FoMO might enhance individuals' need to stay connected and communicate with other people, leading to PSNSU, in order to face the fear of being invisible in the world of social media in circumstances of physical isolation. The present study sought to evaluate the predictive role of FoMO on PSNSU during the COVID-19 pandemic, testing the mediating effect of online relational closeness and online communication attitude. A total of 487 Italian adults (59.3% women), aged between 18 and 70 years (mean age = 29.85 years; SD = 9.76), responded to an online survey during the period of COVID-19 pandemic lockdown in Italy. The survey included self-report measures assessing perceived FoMO, online communication attitude, relational closeness with online friends, and PSNSU. Participants declared they spent significantly more time social networking during the pandemic, particularly women. The total model accounted for a significant amount of variance in participants' PSNSU [R2 = 0.54; F(9, 447) = 58.285, p < 0.001). Despite the other people's social rewarding experiences had been drastically reduced by the lockdown, findings showed a direct effect of FoMO on PSNSU. Moreover, FoMO had an effect on online communication attitude and online relational closeness, although only online communication attitude predicted, in turn, PSNSU. Conversely, relational closeness on social networking sites did not predict PSNSU. The present study suggests that, during COVID-19 lockdown, FoMO levels may have strengthened attitudes toward online communication, which, in turn, may have put some individuals at risk of PSNSU.
TLR7 Is Critical for Anti-Viral Humoral Immunity to EV71 Infection in the Spinal Cord

Enterovirus 71 (EV71) is a positive single-stranded RNA (ssRNA) virus from the enterovirus genus of Picornaviridae family and causes diseases ranged from the mild disease of hand, foot and mouth disease (HFMD) to the severe disease of neurological involvement in young children. TLR7 is an intracellular pattern recognition receptor (PRR) recognizing viral ssRNA. In this study, we investigated the role of TLR7 in EV71 infection in mouse pups (10-12 days old) and found that wild-type (WT) and TLR7 knock-out (TLR7KO) mice infected with EV71 showed similar limb paralysis at the onset and peak of the disease, comparable loss of motor neurons, and similar levels of antiviral molecules in the spinal cord. These results suggest that TLR7 is not the absolute PRR for EV71 in the spinal cord. Interestingly, TLR7KO mice infected with EV71 exhibited significantly delayed recovery from limb paralysis compared with WT mice. TLR7KO mice infected with EV71 showed significantly decreased levels of IgM and IgG2, important antibodies for antiviral humoral immunity. Furthermore, TLR7KO mice infected with EV71 showed a decrease of germinal center B cells in the spleen compared with WT mice. Altogether, our study suggests that TLR7 plays a critical role in anti-viral humoral immunity rather than in being a PRR in the spinal cord during EV71 infection in young mice.
A Neuromechanical Model of Multiple Network Rhythmic Pattern Generators for Forward Locomotion in C. elegans

Multiple mechanisms contribute to the generation, propagation, and coordination of the rhythmic patterns necessary for locomotion in Caenorhabditis elegans. Current experiments have focused on two possibilities: pacemaker neurons and stretch-receptor feedback. Here, we focus on whether it is possible that a chain of multiple network rhythmic pattern generators in the ventral nerve cord also contribute to locomotion. We use a simulation model to search for parameters of the anatomically constrained ventral nerve cord circuit that, when embodied and situated, can drive forward locomotion on agar, in the absence of pacemaker neurons or stretch-receptor feedback. Systematic exploration of the space of possible solutions reveals that there are multiple configurations that result in locomotion that is consistent with certain aspects of the kinematics of worm locomotion on agar. Analysis of the best solutions reveals that gap junctions between different classes of motorneurons in the ventral nerve cord can play key roles in coordinating the multiple rhythmic pattern generators.
Bilateral Repetitive Transcranial Magnetic Stimulation With the H-Coil in Parkinson's Disease: A Randomized, Sham-Controlled Study

Background: Pilot open-label application of high-frequency repetitive transcranial magnetic stimulation (rTMS) with H-coil in Parkinson's Disease (PD) have shown promising results. Objective: To evaluate safety and efficacy of high-frequency rTMS with H-coil in PD in a double-blind, placebo-controlled, randomized study. Methods: Sixty patients with PD were randomized into 3 groups: M1-PFC (real stimulation on primary motor-M1 and pre-frontal cortices-PFC), M1 (real rTMS on M1, sham on PFC), Sham (apparent stimulation). Primary outcome was baseline-normalized percent improvement in UPDRS part III OFF-therapy at the end of treatment (12 rTMS sessions, 4 weeks). Secondary outcomes were improvement in UPDRS part III sub-scores, timed tests, and neuropsychological tests. Statistical analysis compared improvement following real and sham stimulation at the end of the protocol using either a t-test or a Mann-Whitney test. Results: All patients tolerated the treatment and concluded the study. One patient from M1-PFC group was excluded from the analysis due to newly discovered uncontrolled diabetes mellitus. No serious adverse effect was recorded. At the end of treatment, patients receiving real rTMS (M1-PFC and M1 combined) showed significantly greater improvement compared to sham in UPDRS part III total score (p = 0.007), tremor subscore (p = 0.011), and lateralized sub-scores (p = 0.042 for the more affected side; p = 0.012 for the less affected side). No significant differences have been oserved in safety and efficacy outcomes between the two real rTMS groups. Notably, mild, not-distressing and transient dyskinesias occurred in 3 patients after real rTMS in OFF state. Conclusions: The present findings suggest that high-frequency rTMS with H-coil is a safe and potentially effective procedure and prompt larger studies for validation as add-on treatment in PD.
Advances for the Hepatitis A Virus Antigen Production Using a Virus Strain With Codon Frequency Optimization Adjustments in Specific Locations

The available cell-adapted hepatitis A virus (HAV) strains show a very slow replication phenotype hampering the affordable production of antigen. A fast-growing strain characterized by the occurrence of mutations in the internal ribosome entry site (IRES), combined with changes in the codon composition has been selected in our laboratory. A characterization of the IRES activity of this fast-growing strain (HM175-HP; HP) vs. its parental strain (HM175; L0) was assessed in two cell substrates used in vaccine production (MRC-5 and Vero cells) compared with the FRhK-4 cell line in which its selection was performed. The HP-derived IRES was significantly more active than the L0-derived IRES in all cells tested and both IRES were more active in the FRhK-4 cells. The translation efficiency of the HP-derived IRES was also much higher than the L0-derived IRES, particularly, in genes with a HP codon usage background. These results correlated with a higher virus production in a shorter time for the HP strain compared to the L0 strain in any of the three cell lines tested, and of both strains in the FRhK-4 cells compared to Vero and MRC-5 cells. The addition of wortmannin resulted in the increase of infectious viruses and antigen in the supernatant of FRhK-4 infected cells, independently of the strain. Finally, the replication of both strains in a clone of FRhK-4 cells adapted to grow with synthetic sera was optimal and again the HP strain showed higher yields.
Phase Behavior of Styrene−Isoprene Diblock Copolymers in Strongly Selective Solvents

The phase behavior of polystyrene−polyisoprene diblock copolymers diluted with solvents strongly selective for polyisoprene was investigated using variable-temperature small-angle X-ray scattering. Tetradecane was employed as a model selective solvent; its addition induced lyotropic order−order transitions, with as many as five ordered phases found in solutions of one diblock as tetradecane content was varied. The mesophases observed for tetradecane solutions of 10 different diblocks can be partially collapsed into a single two-dimensional map of segregation strength vs overall polystyrene content, as if the selective solvent simply alters the volume fraction of the soluble block. Among strongly selective solvents (tetradecane, tributylamine, squalane), measurable and even large differences in diblock−solvent phase behavior are revealed, in both the locations of lyotropic order−order transitions and the thermotropic order−disorder transition. The addition of squalane to polystyrene-rich diblocks actually .