Water-Repellent TiO₂-Organic Dye-Based Air Filters for Efficient Visible-Light-Activated Photochemical Inactivation against Bioaerosols

Recently, bioaerosols, including the 2019 novel coronavirus, pose a serious threat to global public health. Herein, we introduce a visible-light-activated (VLA) antimicrobial air filter functionalized with titanium dioxide (TiO2)–crystal violet (CV) nanocomposites facilitating abandoned visible light from sunlight or indoor lights. The TiO2–CV based VLA antimicrobial air filters exhibit a potent inactivation rate of ∼99.98% and filtration efficiency of ∼99.9% against various bioaerosols. Under visible-light, the CV is involved in overall inactivation by inducing reactive oxygen species production both directly (CV itself) and indirectly (in combination with TiO2). Moreover, the susceptibility of the CV to humidity was significantly improved by forming a hydrophobic molecular layer on the TiO2 surface, highlighting its potential applicability in real environments such as exhaled or humid air. We believe this work can open a new avenue for designing and realizing practical antimicrobial technology using ubiquitous visible-light energy against the threat of infectious bioaerosols

Anomaly mediated SUSY breaking scenarios in the light of cosmology and in the dark (matter)

Anomaly mediation is a popular and well motivated supersymmetry breaking scenario. Different possible detailed realisations of this set-up are studied and actively searched for at colliders. Apart from limits coming from flavour, low energy physics and direct collider searches, these models are usually constrained by the requirement of reproducing the observations on dark matter density in the universe. We reanalyse these bounds and in particular we focus on the dark matter bounds both considering the standard cosmological model and alternative cosmological scenarios. These scenarios do not change the observable cosmology but relic dark matter density bounds strongly depend on them. We consider few benchmark points excluded by standard cosmology dark matter bounds and suggest that loosening the dark matter constraints is necessary in order to avoid a too strong (cosmological) model dependence in the limits that are obtained for these models. We also discuss briefly the implications for phenomenology and in particular at the Large Hadron Collider.Comment: 37 pages, 20 figures, 1 tabl

Grifonin-1: A Small HIV-1 Entry Inhibitor Derived from the Algal Lectin, Griffithsin

Background: Griffithsin, a 121-residue protein isolated from a red algal Griffithsia sp., binds high mannose N-linked glycans of virus surface glycoproteins with extremely high affinity, a property that allows it to prevent the entry of primary isolates and laboratory strains of T- and M-tropic HIV-1. We used the sequence of a portion of griffithsin's sequence as a design template to create smaller peptides with antiviral and carbohydrate-binding properties. Methodology/Results: The new peptides derived from a trio of homologous β-sheet repeats that comprise the motifs responsible for its biological activity. Our most active antiviral peptide, grifonin-1 (GRFN-1), had an EC50 of 190.8±11.0 nM in in vitro TZM-bl assays and an EC50 of 546.6±66.1 nM in p24gag antigen release assays. GRFN-1 showed considerable structural plasticity, assuming different conformations in solvents that differed in polarity and hydrophobicity. Higher concentrations of GRFN-1 formed oligomers, based on intermolecular β-sheet interactions. Like its parent protein, GRFN-1 bound viral glycoproteins gp41 and gp120 via the N-linked glycans on their surface. Conclusion: Its substantial antiviral activity and low toxicity in vitro suggest that GRFN-1 and/or its derivatives may have therapeutic potential as topical and/or systemic agents directed against HIV-1

Circulating Cell-Free DNA in Dogs with Mammary Tumors: Short and Long Fragments and Integrity Index

Circulating cell-free DNA (cfDNA) has been considered an interesting diagnostic/prognostic plasma biomarker in tumor-bearing subjects. In cancer patients, cfDNA can hypothetically derive from tumor necrosis/apoptosis, lysed circulating cells, and some yet unrevealed mechanisms of active release. This study aimed to preliminarily analyze cfDNA in dogs with canine mammary tumors (CMTs). Forty-four neoplastic, 17 non-neoplastic disease-bearing, and 15 healthy dogs were recruited. Necrosis and apoptosis were also assessed as potential source of cfDNA on 78 CMTs diagnosed from the 44 dogs. The cfDNA fragments and integrity index significantly differentiated neoplastic versus non-neoplastic dogs (P<0.05), and allowed the distinction between benign and malignant lesions (P<0.05). Even if without statistical significance, the amount of cfDNA was also affected by tumor necrosis and correlated with tumor size and apoptotic markers expression. A significant (P<0.01) increase of Bcl-2 in malignant tumors was observed, and in metastatic CMTs the evasion of apoptosis was also suggested. This study, therefore, provides evidence that cfDNA could be a diagnostic marker in dogs carrying mammary nodules suggesting that its potential application in early diagnostic procedures should be further investigated

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Initial experience with magnetic resonance imaging-safe pacemakers: A review

Due of its superior soft tissue imaging capabilities, magnetic resonance imaging (MRI) has become the imaging modality of choice in many clinical situations, as illustrated by the tremendous growth in the number of MRIs performed over the past 2 decades. In parallel, the number of patients who require pacemakers or implantable cardiac defibrillators is increasing as indications for these devices broaden and the population ages. Taken together, these phenomena present an important clinical issue, as MR scans are generally contraindicated—except in urgent situations—in patients who have implanted cardiovascular devices. Potentially deleterious interactions between the magnetic fields and radio frequency (RF) energy produced by MR equipment and implantable devices have been identified, including inhibition of pacing, asynchronous/high-rate pacing, lead tip heating, and loss of capture. New devices that incorporate technologies to improve MR safety in patients with pacemakers have recently received approval in Europe and are under evaluation in the United States. Initial data from these devices suggest that these devices are safe in the MRI environment

Controlling spins in adsorbed molecules by a chemical switch

The development of chemical systems with switchable molecular spins could lead to the architecture of materials with controllable magnetic or spintronic properties. Here, we present conclusive evidence that the spin of an organometallic molecule coupled to a ferromagnetic substrate can be switched between magnetic off and on states by a chemical stimulus. This is achieved by nitric oxide (NO) functioning as an axial ligand of cobalt(II)tetraphenylporphyrin (CoTPP) ferromagnetically coupled to nickel thin-film (Ni(001)). On NO addition, the coordination sphere of Co2+ is modified and a NO–CoTPP nitrosyl complex is formed, which corresponds to an off state of the Co spin. Thermal dissociation of NO from the nitrosyl complex restores the on state of the Co spin. The NO-induced reversible off–on switching of surface-adsorbed molecular spins observed here is attributed to a spin trans effect

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods