bluuebunny/crossref_metadata_2025 huggingface dataset:
Green Sample Preparation Applications for Environmental Analysis
Authors: Pacheco-Fernández I. , Faraji H.
Published: June 2023

Environmental contamination is one of the most significant threats to living beings. The main source of contamination is anthropogenic activity, which generates many wastes with a high impact on ecosystems and human life. The monitoring of these toxic substances in the environment (water, soil, sediments, biota, and air) is of special importance to ensure the safety and adequate management of resources and wastes. The analytical methods require a previous sample preparation step in which target compounds are extracted and interferences are eliminated. Paradoxically, conventional sample preparation procedures are characterized by their low sustainability given the large amounts of toxic solvents and reagents required. In this sense, recent efforts have been shifted to the development of greener sample preparation strategies for the analysis of environmental samples following the Green Analytical Chemistry guidelines. This book chapter gives an overview of the advances in this field, with special attention to the use of microextraction techniques and alternative solvents and sorbents that replace traditional extraction phases, including deep eutectic solvents, supramolecular solvents, and natural sorbents, among others. Moreover, emphasis will be placed on strategies for which the greenness aspects have been evaluated.
Current Applications of Green Sample Preparation in Pharmaceutical Analysis
Authors: Manousi N. , Kalogiouri N. P. , Locatelli M. , Samanidou V.
Published: June 2023

In pharmaceutical analysis, sample preparation is undoubtedly the most challenging and demanding step of the whole analytical procedure. Moreover, due to the increased consumption of hazardous chemicals, this step can also be characterized as highly polluting and environmentally harmful. In the last few years, in order to overcome these limitations and fulfill the principles of Green Analytical Chemistry, various green extraction techniques have been developed. Typical examples of novel environmentally friendly extraction techniques that are used in pharmaceutical analysis involve solid-phase microextraction, liquid-phase microextraction, stir bar sorptive extraction, pipette-tip solid-phase extraction, magnetic solid-phase extraction, dispersive solid-phase extraction, and fabric phase sorptive extraction. At the same time, a plethora of novel sorbents, including carbon-based materials, molecularly imprinted polymers, sol–gel materials, metal–organic frameworks, and covalent–organic frameworks, have been developed and used in sample preparation. In this chapter, we present the current applications of green sample preparation in pharmaceutical analysis. Emphasis will be given to novel sorbents and novel miniaturized extraction techniques and microextraction techniques employed for the determination of pharmaceuticals in complex matrices.
Adhesive creases: bifurcation, morphology and their (apparent) self-similarity
Authors: Essink Martin H. , van Limbeek Michiel A. J. , Pandey Anupam , Karpitschka Stefan , Snoeijer Jacco H.
Published: June 2023

An elastic material that experiences strong compression can exhibit sharp surface folds, often seen in growing tissues or swelling gels. We resolve how self-adhesion affects both morphology and bifurcation behavior of the adhesive crease.
An electrochemical immunosensor for an alpha-fetoprotein cancer biomarker on a carbon black/palladium hybrid nanoparticles platform
Authors: Olorundare Foluke O. G. , Sipuka Dimpo S. , Sebokolodi Tsholofelo I. , Kodama Tetsuya , Arotiba Omotayo A. , Nkosi Duduzile
Published: June 2023

An electrochemical immunosensor for alpha-fetoprotein.
Research on transformer fault diagnosis based on an IWHO optimized MS1DCNN algorithm and LIF spectrum
Authors: Yan Pengcheng , Chen Fengxiang , Kan Xuyue , Zhang Heng , Wang Jingbao , Li Guodong
Published: June 2023

Accurate diagnosis of transformer faults can effectively improve the enduring reliability of power grid operation.
A machine learning approach to predict cellular uptake of pBAE polyplexes
Authors: Loecher Aparna , Bruyns-Haylett Michael , Ballester Pedro J. , Borros Salvador , Oliva Nuria
Published: June 2023

Machine Learning (ML) algorithms are ideal in silico tools to find patterns of cellular internalisation of pBAE polyplexes in various cell types, using chemical and biophysical material properties and cellular gene expression as model inputs.
Effect of metal complexation on the radiolytic stability of DOTA
Authors: Mahti Ilyes , Guillaumont Dominique , Berthon Claude , Saint-Louis Georges , Hérès Xavier , Berthon Laurence
Published: June 2023

Complexation of DOTA with zirconium greatly enhances its radiolytic stability under gamma irradiation.
Emerging investigator series: kinetics of diopside reactivity for carbon mineralization in mafic–ultramafic rocks
Authors: Aguila Briana , Hardee Landon , Schaef H. Todd , Zare Siavash , Abdolhosseini Qomi Mohammad Javad , Crum Jarrod V. , Holliman Jr. Jade E. , Rodriguez Elena Tajuelo , Anovitz Lawrence M. , Rosso Kevin M. , Miller Quin R. S.
Published: June 2023

Complex carbon mineralization at nanoscale mineral interfaces resolved within situX-ray diffraction and molecular simulations.
Developing tiny-sized particles, different modification behaviors of gold atoms, and nucleating distorted particles
Authors: Ali Mubarak , Lin I.-Nan
Published: June 2023

Magnified HR-TOM image of different tiny-sized particles; distance between the copper capillary and solution surface ∼ 4.0 mm, the concentration of gold precursor ∼ 0.30 mM, and the time of processing solution ∼ 5 min.
Metal-free trifunctionalization of phenylacetylenes: an efficient one-pot two-step synthesis ofgem-bis(dithiocarbamates)
Authors: Mondal Manas , Saha Debajyoti , Saha Amit
Published: June 2023

Synthesis of a series of phenacyl-bis(dithiocarbamate) compounds by molecular bromine-mediated dithiocarbamylation of phenylacetylenes.
Rhodium(iii)-catalysed redox neutral alkylation of 3-arylbenzo[d]isoxazoles: easy access to substituted succinimides
Authors: Yue Xuelin , Zhao Xiang , Huang Junwei , Gao Yijie , Feng Yadong , Cui Xiuling
Published: June 2023

A convenient method for the alkylation of 3-arylbenzo[d]isoxazoles with maleimides under redox-neutral conditions has been developed, giving a series of substituted succinimides in up to 99% yield. It features 100% atom-economy and broad substrate tolerance.
Tacticity control approached by electric-field assisted free radical polymerization – the case of sterically hindered monomers
Authors: Tu Wenkang , Maksym Paulina , Chat Katarzyna , Biela Tadeusz , Zięba Andrzej , Kaminski Kamil , Adrjanowicz Karolina
Published: June 2023

Electric-field assisted free-radical polymerization allows controlling the stereochemistry of the produced polymers.
Transamidation vitrimers enabled by neighbouring fluorine atom activation
Authors: Berne Dimitri , Tanguy Gwendal , Caillol Sylvain , Poli Rinaldo , Ladmiral Vincent , Leclerc Eric
Published: June 2023

The effect of neighbouring fluorine atom activation on transamidation is demonstrated through molecular kinetic/DFT studies and vitrimer applications.
Efficient fluorescence-enhanced probe for cyanide ions based on a tetraphenylethene pyridine coordinated copper-iodide complex
Authors: Luo Fenqiang , Guo Meng , Zheng Liyan , Cai Zhixiong
Published: June 2023

A highly efficient probe with fluorescence enhancement for the detection of cyanide ions is developed using a copper-iodide complex coordinated with tetraphenylethene pyridine.
Industrial lignins as efficient biosorbents for Cr(vi) water remediation: transforming a waste into an added value material
Authors: Vescovi Marianna , Melegari Matteo , Gazzurelli Cristina , Maffini Monica , Mucchino Claudio , Mazzeo Paolo Pio , Carcelli Mauro , Perego Jacopo , Migliori Andrea , Leonardi Giuliano , Pietarinen Suvi , Pelagatti Paolo , Rogolino Dominga
Published: June 2023

Effective Cr(vi) water remediation can be obtained by using industrial lignins and lignin-based materials from a circular economy perspective.
Superior low-temperature tolerant, self-adhesive and antibacterial hydrogels for wearable sensors and communication devices
Authors: Feng Enke , Li Xiaoqin , Zhang Mengzhen , Ma Xinxian , Cao Linan , Wu Zhiqiang
Published: June 2023

A multipurpose hydrogel with superior low-temperature tolerance towards human motion monitoring and information transmission.
New X-ray detections of magnetic period-bounce cataclysmic variables from XMM-Newton and SRG/eROSITA
Authors: Muñoz-Giraldo Daniela , Stelzer Beate , de Martino Domitilla , Schwope Axel
Published: June 2023

Context. A great portion of the cataclysmic variable population, between 40% and 70%, is predicted to be made up of period-bouncers, systems with degenerate donors that have evolved past the period minimum. However, due to their intrinsic faintness, only a few of these systems have been observed and confidently identified so far.

Aims. We have searched for X-ray emission as proof of accretion in order to confirm period-bounce cataclysmic variables.

Methods. In this study, we used data from XMM-Newton and eROSITA on a pilot sample of three period-bounce candidates with a magnetic white dwarf, which are expected to exhibit stronger X-ray emission than non-magnetic systems due to more efficient conversion of matter accretion onto the white dwarf.

Results. In a dedicated XMM-Newton observation of the period-bounce candidate SDSS J151415.65+074446.5 we discovered X-ray modulation at the binary orbital period confirming it as an accreting system. The X-ray light curve and the X-ray spectrum display characteristics of magnetic Polar-type systems, allowing us for the first time to determine the X-ray luminosity and mass accretion rate for this system. Catalog data from eROSITA on the Spektrum-Roentgen-Gamma satellite for V379 Vir and SDSS J125044.42+154957.4 enabled a first look into the X-ray behavior of period-bounce candidates with this new all-sky instrument. From the eROSITA measurements, the X-ray luminosity and mass accretion rate were determined for the first time for SDSS J125044.42+154957.4, and the earlier result for V379 Vir from XMM-Newton was confirmed.

Conclusions. The three cataclysmic variables with a magnetic white dwarf and very low-mass donor studied in this work present evidence for X-ray emission at a similar level of LX [erg s−1] ≈ 1029, which, together with the detection of X-ray orbital modulation in two of them (i.e., V379 Vir and SDSS J151415.65+074446.5), unambiguously proves the presence of accretion in these systems. The detection of these period-bouncers at faint X-ray luminosity levels with the all-sky X-ray survey eROSITA offers new prospects for the identification of additional period-bouncers, providing impetus for theoretical studies of binary evolution.
Bases neurales de la mémoire et de la navigation spatiale
Authors: Tran Trung-Hieu , EL Mahzoum Réda , Fricker Desdemona , Cohen Ivan , Bonnot Agnès
Published: June 2023

La carte cognitive est un concept introduit pour la première fois par Edward Tolman en 1948 pour décrire la carte de l’environnement stockée dans le cerveau. Dans cette revue, après une brève évocation de l’histoire de ce concept, nous explorerons les contributions des cellules de lieu et des cellules de grille aux bases neurales de la création et de l’archivage de cette cartographie spatiale. Nous discuterons enfin de la façon dont cette carte est consolidée et stockée dans le cerveau. L’exploration toujours plus poussée des mécanismes de notre mémoire demeure essentielle pour espérer soutenir les adaptations naturelles qui sous-tendent la flexibilité de la cognition au cours de la vie.
X-Linked Hypophosphatemia at the European Society of Pediatric Endocrinology Meeting 2022
Authors: Alsaffar Hussain , Dauleh Hajar , Ali Khadija
Published: June 2023

Rickets, a growth plate disorder, is classified into calcipenic and phosphopenic types based on the etiology. Phosphopenic rickets can be further classified into fibroblast growth factor 23 (FGF23) mediated and non-FGF23 mediated. FGF-23 has a phosphaturic effect which results in hypophosphatemia and, therefore, the accumulation of hypertrophied chondrocytes, leading to rachitic changes in the bones. One of the most common causes of inherited hypophosphatemic rickets is X-linked hypophosphatemia (XLH), mainly due to a mutation in the PHEX gene that ends in the extended release of FGF-23. During the 60th annual meeting of the European Society for Pediatric Endocrinology, held in Rome between September 15 and 19, 2022, approximately 15 presentations were made either as free communication or poster. In addition, there was a dedicated satellite symposium focusing on XLH. This article has been prepared mainly to share knowledge and updates discussed during the meeting about hypophosphatemic rickets, as we feel this disease is still to be focused on in the MENA region, since there are some gaps in the recognition and management of FGF23 hypophosphatemic rickets and osteomalacia.
Timing specification of Chinese tones
Authors: Li Ya
Published: June 2023

Previous research has long been divided on the issues of Chinese tone bearing unit and lexical stress. To help
address these issues, the present study proposes a tonal timing framework based on two types of timing units, specified μ and
unspecified X. It uses Mandarin third tone sandhi and Shanghai Wu tone split and spread processes to illustrate that the proposed
framework can provide a unified account of different tone sandhi processes from the temporal dimension. It also discusses the
implications of the framework for the TBU size, default tone type, tonal prominence, tonal foot, word-level prominence, and
tone-syllable association.
Microstructure and properties of refractory high entropy alloys containing Si and Cr
Authors: Li Rui , Zhang Song , Xu Yonggang
Published: June 2023

Mo0.5NbHf0.5ZrTiAl, Mo0.5NbHf0.5ZrTiSi0.5Al and Mo0.5NbHf0.5CrZrTiAl (molar ratio) refractory high entropy alloys (RHEA) were prepared by vacuum arc melting. The influences of Si and Cr on microstructure and properties of RHEA were investigated. Three RHEA all contain BCC1 phase. Si addition promotes the formation of M5Si3 intermetallic compound, and the microstructure of Si0.5Cr0 RHEA consists of M5Si3 blocks and BCC1 + M5Si3 eutectics. Cr addition leads to the formation of Cr2Nb type Laves phase, and two BCC dendrites exist in Si0Cr RHEA. The compressive strength of Si0.5Cr0 and Si0Cr RHEA increased by about 102% and 85%, respectively, compared to Si0Cr0 one. The oxidation resistance of RHEA is improved by adding Si while dramatically degraded by adding Cr.
Effect of processing route on ballistic performance of Ti-6Al-4V armour plate
Authors: Fernández Silva Beatriz , Levano Blanch Oliver , Sagoo Kam , Jackson Martin
Published: June 2023

Titanium alloys are a key part of an armour designer's toolset due to their high ballistic mass efficiency. However, titanium's high cost has restricted its use in military land-based vehicles. In this study, the effect of different processing routes on the microstructure, texture, ballistic performance V50 and deformation modes of Ti-6Al-4V armour plate is investigated. Plates were fabricated via conventional hot rolling and the powder metallurgy techniques of HIP and FAST. The plate failure modes varied significantly with the microstructure while the formation of adiabatic shear bands seems to be influenced by crystallographic texture. The rolled plate exhibited the best performance due to a strong transverse-type texture perpendicular to the projectile direction.
The Hole Argument and Beyond: Part I: The Story so Far
Authors: Gomes Henrique , Butterfield Jeremy
Published: June 2023

In this two-part paper, we review, and then develop, the assessment of the hole argument for general relativity. This first Part reviews the literature hitherto, focussing on the philosophical aspects. It also introduces two main ideas we will need in Part II: which will propose a framework for making comparisons of non-isomorphic spacetimes.

In Section 1 of this paper, we recall Einstein’s original argument. Section 2 recalls the argument’s revival by philosophers in the 1980s and 1990s. This includes the first main idea we will need in Part II: namely, that two spacetime points in different possible situations are never strictly identical—they are merely counterparts.

In Section 3, we report—and rebut—more recent claims to “dissolve” the argument. Our rebuttal is based on the fact that in differential geometry, and its applications in physics such as general relativity, points are in some cases identified, or correspond with each other, between one context and another, by means other than isometry (or isomorphism). We call such a correspondence a threading of points. This is the second main idea we shall use in Part II.
Relics of the quantum spacetime: from Synge’s world function as the fundamental probe of spacetime architecture to the emergent description of gravity
Authors: Kothawala Dawood
Published: June 2023

All our observations that characterise space and time are expressed in terms of non-local, bi-tensorial objects such as geodesic intervals between events and two-point (Green) functions. In this contribution, I highlight the importance of characterising spacetime geome-try in terms of such non-local objects, focusing particularly on two important bi-tensors that play a particular fundamental role – Synge’s World function and the van Vleck determinant. I will first discuss how these bi-tensors help capture information about spacetime geometry, and then describe their role in characterising quantum spacetime endowed with a lower bound, say ℓ
0, on spacetime intervals. Incorporating such a length scale in a Lorentz covariant manner necessitates a description of spacetime geometry in terms of above bi-tensors, and naturally replaces the conventional description based on the metric tensor gab
(x) with a description in terms of a non-local bi-tensor qab
(x, y). The non-analytic structure of qab
(x, y) which renders a perturbative expansion in ℓ
0 meaningless, also generically leaves a non-trivial “relic” in the limit ℓ
0 → 0. I present some results where such a relic term is manifest; specifically, I will discuss how this: (i) suggests a description of gravitational dynamics different from the one based on Einstein-Hilbert lagrangian, (ii) implies dimensional reduction to 2 at small scales, (iii) connects with the notion of cosmological constant itself being a non-local vestige of the small scale structure of spacetime, (iv) helps address the issues of spacetime singularities. I will conclude by discussing the ramifications of these ideas for quantum gravity.
Quantum physics and biology: the local wavefunction approach
Authors: Ellis George F R
Published: June 2023

Is there a single linearly evolving Wave Function of the Universe that is able to lead to all the nonlinearities we see around us? This proposal seems a priori highly implausible. I claim that instead, in the real Universe, generically only local wave functions exist. Non-local wave functions occur for carefully engineered contexts such as Bell experiments, but there is no single wave function for a cat or macroscopic object such as a brain, let alone for the Universe as a whole. Contextual wave function collapse leads to a defensible version of the Copenhagen interpretation of quantum theory, where classical macro levels provide the context for quantum events and biological emergence. Complexity arises via multiscale adaptive modular hierarchical structures that enable logical branching to emerge from the underlying linear physics. Each emergent level is causally effective because of the meshing of upwards and downwards causation that takes place consistently with that physics. Quantum chemistry approaches in biological contexts fit this local wavefunction picture.
Can the Schrödinger dynamics explain measurement?
Authors: Kryukov Alexey A
Published: June 2023

The motion of a ball through an appropriate lattice of round obstacles models the behavior of a Brownian particle and can be used to describe measurement on a macro system. On another hand, such motion is chaotic and a known conjecture asserts that the Hamiltonian of the corresponding quantum system must follow the random matrix statistics of an appropriate ensemble. We use the Hamiltonian represented by a random matrix in the Gaussian unitary ensemble to study the Schrödinger evolution of non-stationary states. For Gaussian states representing a classical system, the Brownian motion that describes the behavior of the system under measurement is obtained. For general quantum states, the Born rule for the probability of transition between states is derived. It is then shown that the Schrödinger evolution with such a Hamiltonian models measurement on macroscopic and microscopic systems, provides an explanation for the classical behavior of macroscopic bodies and for irreversibility of a measurement, and identifies the boundary between micro and macro worlds.
What quantum matter tells about quantisation of gravity in a statistical mechanics context
Authors: Mandrin Pierre A
Published: June 2023

We propose a “guide” towards quantisation of gravity based on quantum matter in a statistical mechanics context. On one hand, a statistical mechanics model naturally arises from the thermodynamic interpretation of horizons in Rindler space. On the other hand, the path integral formulation of quantum field theory can be interpreted from the point of view of statistical mechanics. From these perspectives, gravity and matter are related to each other in the same way as a gas and its chemical potential are. This statistical mechanics interpretation of gravity and matter suggests that gravity should be quantised in a precise way which is determined by the quantisation of matter. Although, in a first step, quantisation of gravity applies for small perturbations of the metric with respect to the vacuum, the most central and general features of quantisation (quantisation prescription, quantum space dimensions) are supported from statistical mechanics and remain valid non-perturbatively.
Dynamical atom-wall Casimir-Polder effect after a sudden change of the atomic position
Authors: Noto Antonio , Passante Roberto , Rizzuto Lucia , Spagnolo Salvatore
Published: June 2023

We investigate the dynamical Casimir-Polder force between an atom and a conducting wall during the time evolution of the system from a partially dressed state. This state is obtained by a sudden change of the atomic position with respect to the plate. To evaluate the time-dependent atom-plate Casimir-Polder force we solve the Heisenberg equations for the field and atomic operators by an iterative technique. We find that the dynamical atom-plate Casimir-Polder interaction exhibits oscillation in time, and can be attractive or repulsive depending on time and the atom-wall distance. We also investigate the time dependence of global observables, such as the field and atomic Hamiltonians, and discuss some interesting features of the dynamical process bringing the interaction energy to the equilibrium configuration.
Field observables near a fluctuating boundary
Authors: Armata Federico , Butera Salvatore , Montalbano Federico , Passante Roberto , Rizzuto Lucia
Published: June 2023

We review several aspects related to the confinement of a massless scalar field in a cavity with a movable conducting wall of finite mass, free to move around its equilibrium position to which it is bound by a harmonic potential, and whose mechanical degrees of freedom are described quantum mechanically. This system, for small displacements of the movable wall from its equilibrium position, can be described by an effective interaction Hamiltonian between the field and the mirror, quadratic in the field operators and linear in the mirror operators. In the interacting, i.e. dressed, ground state, we first consider local field observables such as the field energy density: we evaluate changes of the field energy density in the cavity with the movable wall with respect to the case of a fixed wall, and corrections to the usual Casimir forces between the two walls. We then investigate the case of two one-dimensional cavities separated by a movable wall of finite mass, with two massless scalar fields defined in the two cavities. We show that in this case correlations between the squared fields in the two cavities exist, mediated by the movable wall, at variance with the fixed-wall case.
A QFT based on Einstein-Hilbert action and hidden dimensions as consistent theory of measurement, dark energy, dark matter and McGaugh’s universal law for rotating galaxies
Authors: Doyen G , Drakova D
Published: June 2023

We present a quantum field theory of gravity in 11 dimensional spacetime, based on Einstein-Hilbert action and expanded up to 4th order in the metric. In the theory the deviation of the local metric from Minkowski metric is a quantum field, called gravonon field. It is responsible for the localization of a matter particle on a definite position in four dimensional spacetime (warp resonance, beable). This is the solution of the measurament problem of Quantum Mechanics coming out as result of the deterministic Schrödinger equation. The quantum gravonon field is also decisive for calculating the expansion of the universe. In lowest order of the metric the interaction of the matter field with the gravonon field is the cause for the expansion of the universe and is the quantum analogue of the often mentioned dark energy. In higher orders of the metric the interaction of ordinary matter and gravonons becomes attractive. The gravonon field then assumes the role of dark matter. McGaugh’s universal radial acceleration relation in rotationally supported galaxies is obtained using this quantum gravitational appoach. The concept of dark matter emerges as do the results of Milgrom’s MOND analysis.
Fermion mixing in curved spacetime
Authors: Capolupo Antonio , Lambiase Gaetano , Quaranta Aniello
Published: June 2023

We develop the quantum field theory of fermion mixing in curved spacetime and discuss the role of unitarily inequivalent representations in the particle interpretation of the theory. We derive general oscillation formulae and apply them to specific spcetimes of interest, such as spatially flat FRW metrics and the Schwarzschild spacetime. We exhibit the main deviations from the usual quantum mechanical approach.
Development of a low-cost monitoring system for the measurement of DC and AC electrical parameters in grid-connected photovoltaic systems based on IEC standards
Authors: Zamudio M A , Carhuavilca A M , Conde L A , García M A , Berastain A E , Montes-Romero J , De la Casa J , Töfflinger J A , Cataño M A
Published: June 2023

The rapid development of renewable energy sources, such as photovoltaic solar energy, makes it possible to sustainably cover part of the energy demand in different parts of the world. Thus, higher efficiency of photovoltaic systems is sought to provide higher yields, security, and stability in their operation and energy production. Therefore, it is crucial to monitor the variables of interest and verify the correct operation of photovoltaic systems. This article presents the development of a monitoring system that allows the acquisition and recording of the main electrical parameters, both in direct and alternating current, enabling the evaluation of the array and final yield of grid-connected photovoltaic systems. The developed monitoring system follows the concept of the Internet of Things for remote data analysis. In addition, it allows local data logging in a computer for data acquisition over a long period. The measurements of the developed monitoring system comply with the International Electrotechnical Commission standards specified in IEC 61724-1. This validation is performed after contrasting the measurements obtained by the developed system with those obtained by the high-precision WT5000 power analyzer, where the relative differences of each electrical parameter analysed are less than 2%. Finally, the system developed is characterised by its low cost, which is less than US$ 140.
A Bootstrap Approach for Evaluating Uncertainty in the Number of Groups Identified by Latent Class Growth Models
Authors: Mésidor Miceline , Sirois Caroline , Simard Marc , Talbot Denis
Published: June 2023

The use of longitudinal finite mixture models such as group-based trajectory modeling has seen a sharp increase during the last few decades in the medical literature. However, these methods have been criticized, especially because of the data-driven modeling process, which involves statistical decision-making. In this paper, we propose an approach that uses the bootstrap to sample observations with replacement from the original data to validate the number of groups identified and to quantify the uncertainty in the number of groups. The method allows investigation of the statistical validity and uncertainty of the groups identified in the original data by checking to see whether the same solution is also found across the bootstrap samples. In a simulation study, we examined whether the bootstrap-estimated variability in the number of groups reflected the replicationwise variability. We evaluated the ability of 3 commonly used adequacy criteria (average posterior probability, odds of correct classification, and relative entropy) to identify uncertainty in the number of groups. Finally, we illustrate the proposed approach using data from the Quebec Integrated Chronic Disease Surveillance System to identify longitudinal medication patterns between 2015 and 2018 in older adults with diabetes.
Elucidation of the mechanism by which the internal structure of food controls the quality
Authors: Ogawa Takenobu
Published: June 2023

Several of the existing food manufacturing processes are based on empirical knowledge, and not many are rationally designed and operated based on a sufficient understanding of the underlying phenomena. Drying and rehydration processes are one such example of this, and a new method for measuring the moisture distribution was developed, focusing on the fact that the brightness of food varies depending on its moisture content. Using this method, new mechanisms of water transfer inside food were proposed based on the rehydration process of noodles. In addition, as a new analysis method for understanding of extremely complex phenomena, we suggest the “artificial intelligence comprehensive and reverse analysis methods”. As a future prospect, we discussed the possibility that this method could contribute to elucidating various unknown complex phenomena.
RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families
Authors: Rahaman Md Mahfuzur , Khan Nabila Shahnaz , Zhang Shaojie
Published: June 2023

Motivation

The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology.

Results

In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family.

Availability and implementation

Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity.
TSignal: a transformer model for signal peptide prediction
Authors: Dumitrescu Alexandru , Jokinen Emmi , Paatero Anja , Kellosalo Juho , Paavilainen Ville O , Lähdesmäki Harri
Published: June 2023

Motivation

Signal peptides (SPs) are short amino acid segments present at the N-terminus of newly synthesized proteins that facilitate protein translocation into the lumen of the endoplasmic reticulum, after which they are cleaved off. Specific regions of SPs influence the efficiency of protein translocation, and small changes in their primary structure can abolish protein secretion altogether. The lack of conserved motifs across SPs, sensitivity to mutations, and variability in the length of the peptides make SP prediction a challenging task that has been extensively pursued over the years.

Results

We introduce TSignal, a deep transformer-based neural network architecture that utilizes BERT language models and dot-product attention techniques. TSignal predicts the presence of SPs and the cleavage site between the SP and the translocated mature protein. We use common benchmark datasets and show competitive accuracy in terms of SP presence prediction and state-of-the-art accuracy in terms of cleavage site prediction for most of the SP types and organism groups. We further illustrate that our fully data-driven trained model identifies useful biological information on heterogeneous test sequences.

Availability and implementation

TSignal is available at: https://github.com/Dumitrescu-Alexandru/TSignal.
Transfer learning for drug–target interaction prediction
Authors: Dalkıran Alperen , Atakan Ahmet , Rifaioğlu Ahmet S , Martin Maria J , Atalay Rengül Çetin , Acar Aybar C , Doğan Tunca , Atalay Volkan
Published: June 2023

Motivation

Utilizing AI-driven approaches for drug–target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the use of deep transfer learning for the prediction of interactions between drug candidate compounds and understudied target proteins with scarce training data. The idea here is to first train a deep neural network classifier with a generalized source training dataset of large size and then to reuse this pre-trained neural network as an initial configuration for re-training/fine-tuning purposes with a small-sized specialized target training dataset. To explore this idea, we selected six protein families that have critical importance in biomedicine: kinases, G-protein-coupled receptors (GPCRs), ion channels, nuclear receptors, proteases, and transporters. In two independent experiments, the protein families of transporters and nuclear receptors were individually set as the target datasets, while the remaining five families were used as the source datasets. Several size-based target family training datasets were formed in a controlled manner to assess the benefit provided by the transfer learning approach.

Results

Here, we present a systematic evaluation of our approach by pre-training a feed-forward neural network with source training datasets and applying different modes of transfer learning from the pre-trained source network to a target dataset. The performance of deep transfer learning is evaluated and compared with that of training the same deep neural network from scratch. We found that when the training dataset contains fewer than 100 compounds, transfer learning outperforms the conventional strategy of training the system from scratch, suggesting that transfer learning is advantageous for predicting binders to under-studied targets.

Availability and implementation

The source code and datasets are available at https://github.com/cansyl/TransferLearning4DTI. Our web-based service containing the ready-to-use pre-trained models is accessible at https://tl4dti.kansil.org.
Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis
Authors: Dayao Monica T , Trevino Alexandro , Kim Honesty , Ruffalo Matthew , D’Angio H Blaize , Preska Ryan , Duvvuri Umamaheswar , Mayer Aaron T , Bar-Joseph Ziv
Published: June 2023

Motivation

Spatial proteomics data have been used to map cell states and improve our understanding of tissue organization. More recently, these methods have been extended to study the impact of such organization on disease progression and patient survival. However, to date, the majority of supervised learning methods utilizing these data types did not take full advantage of the spatial information, impacting their performance and utilization.

Results

Taking inspiration from ecology and epidemiology, we developed novel spatial feature extraction methods for use with spatial proteomics data. We used these features to learn prediction models for cancer patient survival. As we show, using the spatial features led to consistent improvement over prior methods that used the spatial proteomics data for the same task. In addition, feature importance analysis revealed new insights about the cell interactions that contribute to patient survival.

Availability and implementation

The code for this work can be found at gitlab.com/enable-medicine-public/spatsurv.
Getting ‘ϕψχal’ with proteins: minimum message length inference of joint distributions of backbone and sidechain dihedral angles
Authors: Amarasinghe Piyumi R , Allison Lloyd , Stuckey Peter J , Garcia de la Banda Maria , Lesk Arthur M , Konagurthu Arun S
Published: June 2023

The tendency of an amino acid to adopt certain configurations in folded proteins is treated here as a statistical estimation problem. We model the joint distribution of the observed mainchain and sidechain dihedral angles (〈ϕ,ψ,χ1,χ2,…〉) of any amino acid by a mixture of a product of von Mises probability distributions. This mixture model maps any vector of dihedral angles to a point on a multi-dimensional torus. The continuous space it uses to specify the dihedral angles provides an alternative to the commonly used rotamer libraries. These rotamer libraries discretize the space of dihedral angles into coarse angular bins, and cluster combinations of sidechain dihedral angles (〈χ1,χ2,…〉) as a function of backbone 〈ϕ,ψ〉 conformations. A ‘good’ model is one that is both concise and explains (compresses) observed data. Competing models can be compared directly and in particular our model is shown to outperform the Dunbrack rotamer library in terms of model complexity (by three orders of magnitude) and its fidelity (on average 20% more compression) when losslessly explaining the observed dihedral angle data across experimental resolutions of structures. Our method is unsupervised (with parameters estimated automatically) and uses information theory to determine the optimal complexity of the statistical model, thus avoiding under/over-fitting, a common pitfall in model selection problems. Our models are computationally inexpensive to sample from and are geared to support a number of downstream studies, ranging from experimental structure refinement, de novo protein design, and protein structure prediction. We call our collection of mixture models as PhiSiCal (ϕψχal).

Availability and implementation

PhiSiCal mixture models and programs to sample from them are available for download at http://lcb.infotech.monash.edu.au/phisical.
Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale
Authors: Mendelevich Asia , Gupta Saumya , Pakharev Aleksei , Teodosiadis Athanasios , Mironov Andrey A , Gimelbrant Alexander A
Published: June 2023

Motivation

Analysis of allele-specific expression is strongly affected by the technical noise present in RNA-seq experiments. Previously, we showed that technical replicates can be used for precise estimates of this noise, and we provided a tool for correction of technical noise in allele-specific expression analysis. This approach is very accurate but costly due to the need for two or more replicates of each library. Here, we develop a spike-in approach which is highly accurate at only a small fraction of the cost.

Results

We show that a distinct RNA added as a spike-in before library preparation reflects technical noise of the whole library and can be used in large batches of samples. We experimentally demonstrate the effectiveness of this approach using combinations of RNA from species distinguishable by alignment, namely, mouse, human, and Caenorhabditis elegans. Our new approach, controlFreq, enables highly accurate and computationally efficient analysis of allele-specific expression in (and between) arbitrarily large studies at an overall cost increase of ∼5%.

Availability and implementation

Analysis pipeline for this approach is available at GitHub as R package controlFreq (github.com/gimelbrantlab/controlFreq).
RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes
Authors: Firtina Can , Mansouri Ghiasi Nika , Lindegger Joel , Singh Gagandeep , Cavlak Meryem Banu , Mao Haiyu , Mutlu Onur
Published: June 2023

Summary: Nanopore sequencers generate electrical raw signals in real-time while sequencing long genomic strands. These raw signals can be analyzed as they are generated, providing an opportunity for real-time genome analysis. An important feature of nanopore sequencing, Read Until, can eject strands from sequencers without fully sequencing them, which provides opportunities to computationally reduce the sequencing time and cost. However, existing works utilizing Read Until either (i) require powerful computational resources that may not be available for portable sequencers or (ii) lack scalability for large genomes, rendering them inaccurate or ineffective. We propose RawHash, the first mechanism that can accurately and efficiently perform real-time analysis of nanopore raw signals for large genomes using a hash-based similarity search. To enable this, RawHash ensures the signals corresponding to the same DNA content lead to the same hash value, regardless of the slight variations in these signals. RawHash achieves an accurate hash-based similarity search via an effective quantization of the raw signals such that signals corresponding to the same DNA content have the same quantized value and, subsequently, the same hash value. We evaluate RawHash on three applications: (i) read mapping, (ii) relative abundance estimation, and (iii) contamination analysis. Our evaluations show that RawHash is the only tool that can provide high accuracy and high throughput for analyzing large genomes in real-time. When compared to the state-of-the-art techniques, UNCALLED and Sigmap, RawHash provides (i) 25.8× and 3.4× better average throughput and (ii) significantly better accuracy for large genomes, respectively. Source code is available at https://github.com/CMU-SAFARI/RawHash.
ADAD1 is required for normal translation of nuclear pore and transport protein transcripts in spermatids ofMus musculus
Authors: Potgieter Sarah , Eddy Christopher , Badrinath Aditi , Chukrallah Lauren , Lo Toby , Mohanty Gayatri , Visconti Pablo E , Snyder Elizabeth M
Published: June 2023

ADAD1 is a testis-specific RNA-binding protein expressed in post-meiotic spermatids whose loss leads to defective sperm and male infertility. However, the drivers of the Adad1 phenotype remain unclear. Morphological and functional analysis of Adad1 mutant sperm showed defective DNA compaction, abnormal head shaping, and reduced motility. Mutant testes demonstrated minimal transcriptome changes; however, ribosome association of many transcripts was reduced, suggesting ADAD1 may be required for their translational activation. Further, immunofluorescence of proteins encoded by select transcripts showed delayed protein accumulation. Additional analyses demonstrated impaired subcellular localization of multiple proteins, suggesting protein transport is also abnormal in Adad1 mutants. To clarify the mechanism giving rise to this, the manchette, a protein transport microtubule network, and the LINC (linker of nucleoskeleton and cytoskeleton) complex, which connects the manchette to the nuclear lamin, were assessed across spermatid development. Proteins of both displayed delayed translation and/or localization in mutant spermatids implicating ADAD1 in their regulation, even in the absence of altered ribosome association. Finally, ADAD1’s impact on the NPC (nuclear pore complex), a regulator of both the manchette and the LINC complex, was examined. Reduced ribosome association of NPC encoding transcripts and reduced NPC protein abundance along with abnormal localization in Adad1 mutants confirmed ADAD1's impact on translation is required for a NPC in post-meiotic germ cells. Together, these studies lead to a model whereby ADAD1’s influence on nuclear transport leads to deregulation of the LINC complex and the manchette, ultimately generating the range of physiological defects observed in the Adad1 phenotype.
O018 A virtual reality training platform for surgeons, anaesthetists, and obstetricians in low and middle-income countries
Authors: Bolton WS , Aruparayil NK , Please H , Patel R , Dalton J , Agery B , Mwachiro M , Ndizeye O , Daya L , Bains L , Mishra A , Jani P , Culmer PR , Gnanaraj J , Jayne DG , Dhanda J
Published: June 2023

Introduction

Many surgeons, anaesthetists, and obstetricians in low and middle-income countries (LMICs) lack access to training opportunities. The purpose of this study was to evaluate the feasibility of VR procedural training at scale for these specialties.

Methods

An online, free to participant, single-day event programme was designed to cover operative anatomy and procedural steps for Bellwether procedures including Laparotomy and Caesarean section, use of a novel gasless laparoscopic surgery device, administration of spinal anaesthetic and basic trauma principles. Demonstration was performed using fresh frozen cadavers and virtual presentations. Faculty comprised of an equal split between UK and LMIC surgeons from a range of countries virtually connected. The 4K live 360°VR broadcast was achieved via vMix virtual video switcher. vMix Call remote broadcast contributor links and additional angles via NDI IP system.

Results

A total of 236 unique live views were generated. Participants were from 43 countries (n=17 high income countries: n=26 LMICs). In addition, fifty cardboard headsets were transported to two sites for dissemination to local trainees and students: Nairobi, Kenya, and Delhi, India. The mean per-user engagement time for the group was 132 minutes. Nine LMICs had an average per country user engagement of >140 minutes.

Conclusion

It is feasible to live stream surgical training videos in VR and achieve significant user engagement for participants from LMICs. This technology allowed resources and faculty in a HIC setting to collaborate in real-time with faculty input from LMIC via virtual reality, facilitating multi-directional learning.

Take-home message

Live virtual reality surgical training courses are feasible and can provide scalable learning environments, achieving significant engagement from surgeons, obstetricians and anaesthetists across the world, including several low and middle-income countries.