Design of Magnetic Nanoplatforms for Cancer Theranostics

Cancer is the top cause of death globally. Developing smart nanomedicines that are capable of diagnosis and therapy (theranostics) in one–nanoparticle systems are highly desirable for improving cancer treatment outcomes. The magnetic nanoplatforms are the ideal system for cancer theranostics, because of their diverse physiochemical properties and biological effects. In particular, a biocompatible iron oxide nanoparticle based magnetic nanoplatform can exhibit multiple magnetic–responsive behaviors under an external magnetic field and realize the integration of diagnosis (magnetic resonance imaging, ultrasonic imaging, photoacoustic imaging, etc.) and therapy (magnetic hyperthermia, photothermal therapy, controlled drug delivery and release, etc.) in vivo. Furthermore, due to considerable variation among tumors and individual patients, it is a requirement to design iron oxide nanoplatforms by the coordination of diverse functionalities for efficient and individualized theranostics. In this article, we will present an up–to–date overview on iron oxide nanoplatforms, including both iron oxide nanomaterials and those that can respond to an externally applied magnetic field, with an emphasis on their applications in cancer theranostics.

Food waste generation in a university and the handling efficiency of a university catering facility-scale automatic collection system

Purpose This study aims to evaluate the generation of food waste in a university and the handling efficiency of an automatic waste collection system. Design/methodology/approach The quantity of food waste generated and collected from a university canteen was surveyed. The food waste handling efficiencies using manual collection strategy and automated food waste collection system were determined by the density of food waste. Life-cycle costing analysis was done to evaluate the economic impacts of various food waste collection methods. Findings As compared with the manual collection approach, the automatic system can improve the food waste handling efficiency by 30% (from 0.01 to 0.007 bin kg−1) and reduce the water use by 20% (from 0.512 to 0.406 L kg−1); however, it also consumes 4.4 times more energy (from 0.005 to 0.027 kWh kg−1). Under ideal system operation, the 10-year cost of food waste collection was significantly reduced from $3.45 kg−1 in the manual collection to $1.79 kg−1, and the payback period of the system collection was 1.9 years without discount. Practical implications The outcomes of this study show that an automatic food waste collection system is feasible, and it is recommended for small- and medium-sized catering facilities (e.g. canteens and food courts) to improve food waste handling efficiency. This study also provides useful reference data of automatic food waste collection systems for planning food waste management programs for catering facilities. Originality/value To the best of the authors’ knowledge, this is the first study to evaluate the waste handling efficiency, operational expenditure and life-cycle cost of a small-scale automatic food waste collection system.

Raif-Semantics: A Robust Automated Interlinking Framework for Semantic Web Using MapReduce and Multi-node Data Processing

The era of the web has evolved and the industry strives to work better every day, the constant need for data to be accessible at a random moment is expanding, and with this expansion, the need to create a meaningful query technique in the web is a major concerns. To transmit meaningful data or rich semantics, machines/projects need to have the ability to reach the correct information and make adequate connections, this problem is addressed after the emergence of Web 3.0, the semantic web is developing and being collected an immense. Information to prepare, this passes the giant data management test, to provide an ideal result at any time needed. Accordingly, in this article, we present an ideal system for managing huge information using MapReduce structures that internally help an engine bring information using the strength of fair preparation using smaller map occupations and connection disclosure measures. Calculations for similarity can be challenging, this work performs five similarity detection algorithms and determines the time it takes to address the patterns that has to be a better choice in the calculation decision. The proposed framework is created using the most recent and widespread information design, that is, the JSON design, the HIVE query language to obtain and process the information planned according to the customer’s needs and calculations for the disclosure of the interface. Finally, the results on a web page is made available that helps a user stack json information and make connections somewhere in the range of dataset 1 and dataset 2. The results are examined in 2 different sets, the results show that the proposed approach helps to interconnect significantly faster; Regardless of how large the information is, the time it takes is not radically extended. The results demonstrate the interlinking of the dataset 1 and dataset 2 is most notable using LD and JW, the time required is ideal in both calculations, this paper has mechanized the method involved with interconnecting via a web page, where customers can merge two sets of data that should be associated and used.

Neural correlates of individual odor preference in Drosophila

Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical underpinnings of this individuality. Drosophila olfaction is an ideal system for discovering the origins of behavioral individuality among genetically identical individuals. The fly olfactory circuit is well-characterized and stereotyped, yet stable idiosyncrasies in odor preference, neural coding, and neural wiring are present and may be relevant to behavior. Using paired behavior and two-photon imaging measurements, we show that individual odor preferences in odor-vs-air and odor-vs-odor assays are predicted by idiosyncratic calcium dynamics in Olfactory Receptor Neurons (ORNs) and Projection Neurons (PNs), respectively. This suggests that circuit variation at the sensory periphery determines individual odor preferences. Furthermore, paired behavior and immunohistochemistry measurements reveal that variation in ORN presynaptic density also predicts odor-vs-odor preference. This point in the olfactory circuit appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. To unify these results, we constructed a leaky-integrate-and-fire model of 3,062 neurons in the antennal lobe. In these simulations, stochastic fluctuations at the glomerular level, like those observed in our ORN immunohistochemistry, produce variation in PN calcium responses with the same structure as we observed experimentally, the very structure that predicts idiosyncratic behavior. Thus, our results demonstrate how minute physiological and structural variations in a neural circuit may produce individual behavior, even when genetics and environment are held constant.

Majorana quanta, string scattering, curved spacetimes and the Riemann Hypothesis

The Riemann Hypothesis states that the Riemann zeta function ζ(z) admits a set of “non-trivial” zeros that are complex numbers supposed to have real part 1/2. Their distribution on the complex plane is thought to be the key to determine the number of prime numbers before a given number. Hilbert and Pólya suggested that the Riemann Hypothesis could be solved through the mathematical tools of physics, finding a suitable Hermitian or unitary operator that describe classical or quantum systems, whose eigenvalues distribute like the zeros of ζ(z). A different approach is that of finding a correspondence between the distribution of the ζ(z) zeros and the poles of the scattering matrix S of a physical system. Our contribution is articulated in two parts: in the first we apply the infinite-components Majorana equation in a Rindler spacetime and compare the results with those obtained with a Dirac particle following the Hilbert-Pólya approach showing that the Majorana solution has a behavior similar to that of massless Dirac particles and finding a relationship between the zeros of zeta end the energy states. Then, we focus on the S-matrix approach describing the bosonic open string scattering for tachyonic states with the Majorana equation. Here we find that, thanks to the relationship between the angular momentum and energy/mass eigenvalues of the Majorana solution, one can explain the still unclear point for which the poles and zeros of the S-matrix of an ideal system that can satisfy the Riemann Hypothesis, exist always in pairs and are related via complex conjugation. As claimed in the literature, if this occurs and the claim is correct, then the Riemann Hypothesis could be in principle satisfied, tracing a route to a proof.

Genome instability drives epistatic adaptation in the human pathogen Leishmania

How genome instability is harnessed for fitness gain despite its potential deleterious effects is largely elusive. An ideal system to address this important open question is provided by the protozoan pathogen Leishmania, which exploits frequent variations in chromosome and gene copy number to regulate expression levels. Using ecological genomics and experimental evolution approaches, we provide evidence that Leishmania adaptation relies on epistatic interactions between functionally associated gene copy number variations in pathways driving fitness gain in a given environment. We further uncover posttranscriptional regulation as a key mechanism that compensates for deleterious gene dosage effects and provides phenotypic robustness to genetically heterogenous parasite populations. Finally, we correlate dynamic variations in small nucleolar RNA (snoRNA) gene dosage with changes in ribosomal RNA 2′-O-methylation and pseudouridylation, suggesting translational control as an additional layer of parasite adaptation. Leishmania genome instability is thus harnessed for fitness gain by genome-dependent variations in gene expression and genome-independent compensatory mechanisms. This allows for polyclonal adaptation and maintenance of genetic heterogeneity despite strong selective pressure. The epistatic adaptation described here needs to be considered in Leishmania epidemiology and biomarker discovery and may be relevant to other fast-evolving eukaryotic cells that exploit genome instability for adaptation, such as fungal pathogens or cancer.

Babesia duncani as a model organism to study the development, virulence and drug susceptibility of intraerythrocytic parasites in vitro and in vivo

Hematozoa are a subclass of protozoan parasites that invade and develop within vertebrate red blood cells to cause the pathological symptoms associated with diseases of both medical and veterinary importance such as malaria and babesiosis. A major limitation in the study of the most prominent hematozoa, Plasmodium spp, the causative agents of malaria, is the lack of a broadly accessible mouse model to evaluate parasite infection in vivo as is the case for P. falciparum or altogether the lack of an in vitro culture and mouse models as is the case for P. vivax, P. malariae and P. ovale. Similarly, no in vitro culture system exists for Babesia microti, the predominant agent of human babesiosis. In this study, we show that human red blood cells infected with the human pathogen Babesia duncani continuously propagated in culture, as well as merozoites purified from parasite cultures, can cause lethal infection in immunocompetent C3H/HeJ mice. Furthermore, highly reproducible parasitemia and survival outcomes were established using specific parasite loads and different mouse genetic backgrounds. Using the combined in culturein mouse (ICIM) model of B. duncani infection, we demonstrate that current recommended combination therapies for the treatment of human babesiosis, while synergistic in cell culture, have weak potency in vitro and failed to clear infection or prevent death in mice. Interestingly, using the ICIM model, we identified two new endochin-like quinolone prodrugs, ELQ-331 and ELQ468, that alone or in combination with atovaquone are highly efficacious against B. duncani and B. microti. The novelty, ease of use and scalability of the B. duncani ICIM dual model make it an ideal system to study intraerythrocytic parasitism by protozoa, unravel the molecular mechanisms underlying parasite virulence and pathogenesis, and accelerate the development of innovative therapeutic strategies that could be translated to unculturable parasites and important pathogens for which an animal model is lacking.

Intra- and inter-observer reproducibility of r-ASRM endometriosis classification system and its components, using edited videotaped laparoscopic procedures

Several classification systems have been proposed for endometriosis but the search for the ideal system is ongoing. While the most commonly used system has historically been r-ASRM, this system is not fit for purpose, particularly for deep endometriosis. In order to explore strategies to devise a new system and learn from problems with the existing ones, this study was designed to assess the reproducibility of each component in r-ASRM and its total score using videotaped laparoscopic procedures. Two surgeons independently scored 64 edited videos of laparoscopic endometriosis procedure, twice. Using the Kappa statistic, the agreement of the scores given was analyzed. r-ASRM showed a moderate inter-observer agreement (ƙ = 0.503) and good intra-observer agreement (ƙ = 0.774 and 0.682 for scorer 1 and 2 respectively) for overall disease staging. The agreement for each component of the system, however, was highly variable. The least agreement was observed for the peritoneum with ƙ = 0.157 and ƙ = 0.362 respectively for inter-observer and intra-observer. The lowest intra-observer agreement was seen for cul-de-sac for scorer 2 (ƙ = 0.382). Whilst the overall rASRM shows acceptable agreement between two scorers, this agreement seems to be the product of inconsistent scoring for each component.

Geometric characterization of anomalous Landau levels of isolated flat bands

According to the Onsager’s semiclassical quantization rule, the Landau levels of a band are bounded by its upper and lower band edges at zero magnetic field. However, there are two notable systems where the Landau level spectra violate this expectation, including topological bands and flat bands with singular band crossings, whose wave functions possess some singularities. Here, we introduce a distinct class of flat band systems where anomalous Landau level spreading (LLS) appears outside the zero-field energy bounds, although the relevant wave function is nonsingular. The anomalous LLS of isolated flat bands are governed by the cross-gap Berry connection that measures the wave-function geometry of multi bands. We also find that symmetry puts strong constraints on the LLS of flat bands. Our work demonstrates that an isolated flat band is an ideal system for studying the fundamental role of wave-function geometry in describing magnetic responses of solids.

Mouse models of aneuploidy to understand chromosome disorders

An organism or cell carrying a number of chromosomes that is not a multiple of the haploid count is in a state of aneuploidy. This condition results in significant changes in the level of expression of genes that are gained or lost from the aneuploid chromosome(s) and most cases in humans are not compatible with life. However, a few aneuploidies can lead to live births, typically associated with deleterious phenotypes. We do not understand why phenotypes arise from aneuploid syndromes in humans. Animal models have the potential to provide great insight, but less than a handful of mouse models of aneuploidy have been made, and no ideal system exists in which to study the effects of aneuploidy per se versus those of raised gene dosage. Here, we give an overview of human aneuploid syndromes, the effects on physiology of having an altered number of chromosomes and we present the currently available mouse models of aneuploidy, focusing on models of trisomy 21 (which causes Down syndrome) because this is the most common, and therefore, the most studied autosomal aneuploidy. Finally, we discuss the potential role of carrying an extra chromosome on aneuploid phenotypes, independent of changes in gene dosage, and methods by which this could be investigated further.