bluuebunny/crossref_metadata_2025 huggingface dataset:
Attitudes Towards the Development of Good Practices with Augmented Reality in Secondary Education Teachers in Spain
Authors: Marín-Marín José-Antonio , López-Belmonte Jesús , Pozo-Sánchez Santiago , Moreno-Guerrero Antonio-José
Published: August 2023

The attitude of the teaching staff is positioned as a fundamental aspect for the development of good training practices. These good practices are essential when applied within an innovative techno-pedagogical methodology: augmented reality in education. The objectives of this study are to analyze the development of good teaching practices with augmented reality and to discover the factors that influence their quality. A descriptive and correlational design has been carried out. A total of 1490 Spanish Secondary Education teachers have participated. The instrument used was the adaptation to the Spanish context of the questionnaire of the Attitude Scale of Augmented Reality Applications. The results reveal that teachers show a positive attitude towards the use of augmented reality. As for the aspects that influence the good attitude of teachers are age, the number of devices teachers use, the time they dedicate to technological resources and teaching experience. However, ICT training is what determines a direct influence on the attitude of teachers, as well as satisfaction with reliability.
Cytochrome P450 26A1 Contributes to the Maintenance of Neuropathic Pain
Authors: Cao De-Li , Ma Ling-Jie , Jiang Bao-Chun , Gu Qiang , Gao Yong-Jing
Published: August 2023

The cytochrome P450 proteins (CYP450s) have been implicated in catalyzing numerous important biological reactions and contribute to a variety of diseases. CYP26A1, a member of the CYP450 family, carries out the oxidative metabolism of retinoic acid (RA), the active metabolite of vitamin A. Here we report that CYP26A1 was dramatically upregulated in the spinal cord after spinal nerve ligation (SNL). CYP26A1 was mainly expressed in spinal neurons and astrocytes. HPLC analysis displayed that the content of all-trans-RA (at-RA), the substrate of CYP26A1, was reduced in the spinal cord on day 7 after SNL. Inhibition of CYP26A1 by siRNA or inhibition of CYP26A1-mediated at-RA catabolism by talarozole relieved the SNL-induced mechanical allodynia during the maintenance phase of neuropathic pain. Talarozole also reduced SNL-induced glial activation and proinflammatory cytokine production but increased anti-inflammatory cytokine (IL-10) production. The RA receptors RARα, RXRβ, and RXRγ were expressed in spinal neurons and glial cells. The promoter of Il-10 has several binding sites for RA receptors, and at-RA directly increased Il-10 mRNA expression in vitro. Finally, intrathecal IL-10 attenuated SNL-induced neuropathic pain and reduced the activation of astrocytes and microglia. Collectively, the inhibition of CYP26A1-mediated at-RA catabolism alleviates SNL-induced neuropathic pain by promoting the expression of IL-10 and suppressing glial activation. CYP26A1 may be a potential therapeutic target for the treatment of neuropathic pain.
Evolution of Semi-Kantian Preferences in Two-Player Assortative Interactions with Complete and Incomplete Information and Plasticity
Authors: Alger Ingela , Lehmann Laurent
Published: August 2023

We model the evolution of preferences guiding behavior in pairwise interactions in group-structured populations. The model uses long-term evolution theory to examine different interaction scenarios, including conditional preference expression upon recognition of the partner’s type. We apply the model to the evolution of semi-Kantian preferences at the fitness level, which combine self-interest and a Kantian interest evaluating own behavior in terms of consequences for own fitness if the partner also adopted this behavior. We seek the convergence stable and uninvadable value of the Kantian coefficient, i.e., the weight attached to the Kantian interest, a quantitative trait varying between zero and one. We consider three scenarios: (a) incomplete information; (b) complete information and incomplete plasticity; and (c) complete information and complete plasticity, where individuals not only recognize the type of their interaction partner (complete information), but also conditionally express the Kantian coefficient upon it (complete plasticity). For (a), the Kantian coefficient generally evolves to equal the coefficient of neutral relatedness between interacting individuals; for (b), it evolves to a value that depends on demographic and interaction assumptions, while for (c) there are generally multiple uninvadable types, including the type whereby an individual is a pure Kantian when interacting with individuals of the same type and applies the Kantian coefficient that is uninvadable under complete information with zero relatedness when interacting with a different typed individual. Overall, our model connects several concepts for analysing the evolution of behavior rules for strategic interactions that have been emphasized in different and sometimes isolated studies.
Optimal Gagliardo–Nirenberg interpolation inequality for rearrangement invariant spaces
Authors: Leśnik Karol , Roskovec Tomáš , Soudský Filip
Published: August 2023

We prove the optimality of the Gagliardo–Nirenberg inequality: $$\begin{aligned} \Vert \nabla u\Vert _{X}\lesssim \Vert \nabla ^2 u\Vert _Y^{1/2}\Vert u\Vert _Z^{1/2}, \end{aligned}$$

‖
∇
u
‖

X

≲
‖

∇
2

u
‖

Y

1
/
2

‖
u
‖

Z

1
/
2

,

where Y and Z are rearrangement invariant Banach function spaces, and $$X = Y^{1/2}Z^{1/2}$$

X
=

Y

1
/
2

Z

1
/
2

is the Calderón–Lozanovskii space. By optimality, we mean that for a certain pair of spaces on the right-hand side, it is not possible to reduce the space on the left-hand side while remaining in the class of rearrangement invariant spaces. Our result establishes the optimality for Lorentz and Orlicz spaces, surpassing previous findings. Additionally, we discuss the significance of pointwise inequalities and present a counterexample that prohibits further improvements.
A variational theory for integral functionals involving finite-horizon fractional gradients
Authors: Cueto Javier , Kreisbeck Carolin , Schönberger Hidde
Published: August 2023

The center of interest in this work are variational problems with integral functionals depending on nonlocal gradients with finite horizon that correspond to truncated versions of the Riesz fractional gradient. We contribute several new aspects to both the existence theory of these problems and the study of their asymptotic behavior. Our overall proof strategy builds on finding suitable translation operators that allow to switch between the three types of gradients: classical, fractional, and nonlocal. These provide useful technical tools for transferring results from one setting to the other. Based on this approach, we show that quasiconvexity, which is the natural convexity notion in the classical calculus of variations, gives a necessary and sufficient condition for the weak lower semicontinuity of the nonlocal functionals as well. As a consequence of a general$$\varGamma $$Γ-convergence statement, we obtain relaxation and homogenization results. The analysis of the limiting behavior for varying fractional parameters yields, in particular, a rigorous localization with a classical local limit model.
Improved Settling Mechanisms of an Industrial Copper Smelting Slag by CaO Modification
Authors: Isaksson Jenny , Andersson Anton , Vikström Tommy , Lennartsson Andreas , Samuelsson Caisa
Published: August 2023

A significant source of copper losses from pyrometallurgical copper extraction is attributed to dissolved and entrained copper in discarded slag. Entrained copper can be recovered via pyrometallurgical slag cleaning in a settling furnace, where the slag viscosity and copper droplet size distribution (CDSD) are critical parameters. Reduced copper losses suggest improved raw material efficiency, and the slag becomes a more environmentally safe byproduct. In this study, iron silicate slags from a smelting furnace are industrially CaO modified in a fuming furnace to contain a CaO content between 8 and 18 wt.%. The viscosity of slags with and without CaO modifications is evaluated in the temperature range from 1423 to 1723 K. The influences of the CaO modifications on the CDSD, slag matrix copper content, and total copper content were determined. The results show that the slag viscosity decreases with increasing CaO concentrations in the slag. In addition, the copper content decreases in the slag phase, and the CDSD shifts to contain relatively larger droplets. The effect of CaO slag modification reveals a linear relationship between the overall copper recovery and viscosity, which increased from 63 to 88% when the viscosity in the respective batch was 0.51 and 0.25 Pa·s.

Graphical Abstract
Effects of the Digital Intervention StudentPOWR on the Subjective Wellbeing of Students Studying from Home: a Randomized Wait-List Control Trial
Authors: Nixon Louise , Slattery Brian , Cassese Alberto , ten Hoor Gill
Published: August 2023

Since the COVID-19 pandemic, the demand to study and work from home has become of great importance. While recent research has provided evidence for the negative influence of remote studying on the mental and physical health of students, less is known about digital well-being interventions to mitigate these effects. This study had two objectives: 1) to assess the effects of the online well-being intervention, StudentPOWR, on the subjective well-being of students studying from home, and 2) to investigate the influence of engagement with the intervention on subjective well-being. This was a non-blind, 3-arm (full access, limited access, and waitlist control) randomized controlled trial (RCT) and took place in March 2021. University students (N = 99) studying remotely in Ireland and the Netherlands were randomly assigned to the full access (N = 36), partial access (N = 30), or waitlist control (N = 33) group for the four-week intervention period. Measures included the SPANE questionnaire for subjective well-being and the DBCI-ES-Ex for engagement with the intervention. Participants in both the full access and the partial access groups improved in their subjective well-being scores from baseline to week 2 compared to the waitlist control group (p = .004, Hedges g equal to 0.4902 - small effect size - and 0.5698 - medium effect size - for the full intervention and partial intervention, respectively). However, post-intervention, participants in the partial intervention – but not in the full access group - showed significantly greater changes in subjective well-being scores compared to those in the waitlist control group. Possible explanations for these results, comparisons with previous studies, and suggestions for future research are explored.
A primer on the insurability of decentralized finance (DeFi)
Authors: Bekemeier Felix
Published: August 2023

Decentralized finance (DeFi), a blockchain-based form of alternative financial markets, has gained significant public attention in recent months. Despite its relatively short history, DeFi offers a range of opportunities for designing and transferring digital assets. This establishes market structures that bear resemblance to traditional financial markets. Notably, the landscape of DeFi projects has expanded to include insurance protocols that offer DeFi-inherent mechanisms for hedging DeFi-specific risks, particularly those associated with smart contracts. These insurance protocols aim to provide similar value propositions as traditional insurance, namely the minimization and transfer of risks in exchange for a premium. However, it is crucial to acknowledge that most of these risk transfer protocols are strongly dependent on subjective expectations and decentralized governance structures. This article aims to develop a taxonomical understanding of DeFi insurance. Moreover, it seeks to assess the insurability of risks related to smart contracts. By doing so, this study contributes to the emerging body of knowledge surrounding DeFi insurance, paving the way for further research and analysis in this evolving field.
What influences teachers to select their schools? Teachers’ perspectives on strengths and weaknesses of rural and urban area in Taiwan
Authors: Ho Hsuan-Fu , Tsai Chia-Lin
Published: August 2023

The problem of teacher shortages in rural areas are intractable, as schools lack adequate qualified teachers, which inevitably exerts a negative impact on student learning and school development. In Taiwan, the government has implemented relevant policies, but the high teacher turnover rate and the high proportion of nonqualified teachers are issues that are still unsolved. This research investigated the relative importance of the determinants influencing teacher school selection and compared the teachers from rural districts with those from urban. The analytic hierarchy process (AHP) was adopted to analyze the proportion and ranking of the determinants, and a self-developed questionnaire was distributed to teachers from 25 rural and 25 urban schools in Taiwan. Initially, 10 urban and 5 rural schools were selected through the researcher’s social connections, and the remaining schools were recommended by the selected schools. The final 500 samples comprised 50 schools, each contributing 10 teachers to the research. The research results indicate that decent quality of life and professional autonomy are the most valued criteria by the participants, while monetary incentives, including both salary and subsidy, are moderately valued. Moreover, among the comparison between schools from different districts, teachers from rural areas are relatively pessimistic about the working conditions despite holding advantages in the areas of several determinants, which contradicts the stereotype of the unattractive hard-to-staff school. The findings provide suggestions for policymakers regarding the implementation of incentives catered to teachers’ needs to lessen the negative impact of teacher shortages in rural areas.
Reliability of Ensemble Climatological Forecasts
Authors: Huang Zeqing , Zhao Tongtiegang , Tian Yu , Chen Xiaohong , Duan Qingyun , Wang Hao
Published: August 2023

Ensemble climatological forecasts play a critical part in benchmarking the predictive performance of hydroclimatic forecasts. Accounting for the skewness and censoring characteristics of hydroclimatic variables, ensemble climatological forecasts can be generated by the log, Box‐Cox and log‐sinh transformations, by the combinations of the Bernoulli distribution with the Gaussian, Gamma, log‐normal, generalized extreme value, generalized logistic and Pearson type III distributions and by the non‐parametric resampling, empirical cumulative distribution function and kernel density estimation methods. This paper is concentrated on the reliability of the 12 types of ensemble climatological forecasts. Specifically, mathematical formulations are presented and large‐sample tests are devised to verify the forecast reliability for the Multi‐Source Weighted‐Ensemble Precipitation version 2 across the globe. Climatological forecasts of monthly precipitation over 18,425 grid cells are generated for 30 years under leave‐one‐year‐out cross validation, leading to 6,633,000 (12 × 18425 × 30) sets of ensemble climatological forecasts. The results point out that the reliability of climatological forecasts considerably varies across the 12 methods, particularly in regions with high hydroclimatic variability. One observation is that climatological forecasts tend to deviate from the distributions of observations when there is inadequate flexibility to fit precipitation data. Another observation is that ensemble spreads can be overly wide when there exist overfits of sample‐specific noises in cross validation. Through the tests of global precipitation, the robustness of the log‐sinh transformation and the Bernoulli‐Gamma distribution is highlighted. Overall, the investigations can serve as a guidance on the uses of transformations, distributions and non‐parametric methods in generating climatological forecasts.
Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy
Authors: Ning Kefu , Lu Bolin , Wang Xiaojun , Zhang Xiaoyu , Nie Shuo , Jiang Tao , Li Anan , Fan Guoqing , Wang Xiaofeng , Luo Qingming , Gong Hui , Yuan Jing
Published: August 2023

One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 μm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.
Predictors of transition in patients with clinical high risk for psychosis: an umbrella review
Authors: Andreou Christina , Eickhoff Sofia , Heide Marco , de Bock Renate , Obleser Jonas , Borgwardt Stefan
Published: August 2023

Diagnosis of a clinical high-risk (CHR) state enables timely treatment of individuals at risk for a psychotic disorder, thereby contributing to improving illness outcomes. However, only a minority of patients diagnosed with CHR will make the transition to overt psychosis. To identify patients most likely to benefit from early intervention, several studies have investigated characteristics that distinguish CHR patients who will later develop a psychotic disorder from those who will not. We aimed to summarize evidence from systematic reviews and meta-analyses on predictors of transition to psychosis in CHR patients, among characteristics and biomarkers assessed at baseline. A systematic search was conducted in Pubmed, Scopus, PsychInfo and Cochrane databases to identify reviews and meta-analyses of studies that investigated specific baseline predictors or biomarkers for transition to psychosis in CHR patients using a cross-sectional or longitudinal design. Non-peer-reviewed publications, gray literature, narrative reviews and publications not written in English were excluded from analyses. We provide a narrative synthesis of results from all included reviews and meta-analyses. For each included publication, we indicate the number of studies cited in each domain and its quality rating. A total of 40 publications (21 systematic reviews and 19 meta-analyses) that reviewed a total of 272 original studies qualified for inclusion. Baseline predictors most consistently associated with later transition included clinical characteristics such as attenuated psychotic and negative symptoms and functioning, verbal memory deficits and the electrophysiological marker of mismatch negativity. Few predictors reached a level of evidence sufficient to inform clinical practice, reflecting generalizability issues in a field characterized by studies with small, heterogeneous samples and relatively few transition events. Sample pooling and harmonization of methods across sites and projects are necessary to overcome these limitations.
Accelerated evolution of SARS-CoV-2 in free-ranging white-tailed deer
Authors: McBride Dillon S. , Garushyants Sofya K. , Franks John , Magee Andrew F. , Overend Steven H. , Huey Devra , Williams Amanda M. , Faith Seth A. , Kandeil Ahmed , Trifkovic Sanja , Miller Lance , Jeevan Trushar , Patel Anami , Nolting Jacqueline M. , Tonkovich Michael J. , Genders J. Tyler , Montoney Andrew J. , Kasnyik Kevin , Linder Timothy J. , Bevins Sarah N. , Lenoch Julianna B. , Chandler Jeffrey C. , DeLiberto Thomas J. , Koonin Eugene V. , Suchard Marc A. , Lemey Philippe , Webby Richard J. , Nelson Martha I. , Bowman Andrew S.
Published: August 2023

The zoonotic origin of the COVID-19 pandemic virus highlights the need to fill the vast gaps in our knowledge of SARS-CoV-2 ecology and evolution in non-human hosts. Here, we detected that SARS-CoV-2 was introduced from humans into white-tailed deer more than 30 times in Ohio, USA during November 2021-March 2022. Subsequently, deer-to-deer transmission persisted for 2–8 months, disseminating across hundreds of kilometers. Newly developed Bayesian phylogenetic methods quantified how SARS-CoV-2 evolution is not only three-times faster in white-tailed deer compared to the rate observed in humans but also driven by different mutational biases and selection pressures. The long-term effect of this accelerated evolutionary rate remains to be seen as no critical phenotypic changes were observed in our animal models using white-tailed deer origin viruses. Still, SARS-CoV-2 has transmitted in white-tailed deer populations for a relatively short duration, and the risk of future changes may have serious consequences for humans and livestock.
Kinetic resolution of substituted amido[2.2]paracyclophanes via asymmetric electrophilic amination
Authors: Yu Shaoze , Bao Hanyang , Zhang Dekun , Yang Xiaoyu
Published: August 2023

Planar chiral [2.2]paracyclophane derivatives are a type of structurally intriguing and practically useful chiral molecules, which have found a range of important applications in the field of asymmetric catalysis and material science. However, access to enantioenriched [2.2]paracyclophanes represents a longstanding challenge in organic synthesis due to their unique structures, which are still highly dependent on the chiral chromatography separation technique and classical chemical resolution strategy to date. In this work, we report on an efficient and versatile kinetic resolution protocol for various substituted amido[2.2]paracyclophanes, including those with pseudo-geminal, pseudo-ortho, pseudo-meta and pseudo-para disubstitutions, using chiral phosphoric acid (CPA)-catalyzed asymmetric amination reaction, which was also applicable to the enantioselective desymmetrization of an achiral diamido[2.2]paracyclophane. Detailed experimental studies shed light on a new reaction mechanism for the electrophilic aromatic C-H amination, which proceeded through sequential triazane formation and N[1,5]-rearrangement. The facile large-scale kinetic resolution reaction and diverse derivatizations of both the recovered chiral starting materials and the C-H amination products showcased the potential of this method.
Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors
Authors: Derbyshire Mark C. , Raffaele Sylvain
Published: August 2023

Pathogens secrete effector proteins to subvert host physiology and cause disease. Effectors are engaged in a molecular arms race with the host resulting in conflicting evolutionary constraints to manipulate host cells without triggering immune responses. The molecular mechanisms allowing effectors to be at the same time robust and evolvable remain largely enigmatic. Here, we show that 62 conserved structure-related families encompass the majority of fungal orphan effector candidates in the Pezizomycotina subphylum. These effectors diversified through changes in patterns of thermodynamic frustration at surface residues. The underlying mutations tended to increase the robustness of the overall effector protein structure while switching potential binding interfaces. This mechanism could explain how conserved effector families maintained biological activity over long evolutionary timespans in different host environments and provides a model for the emergence of sequence-unrelated effector families with conserved structures.
Structural basis of HIV-1 Vif-mediated E3 ligase targeting of host APOBEC3H
Authors: Ito Fumiaki , Alvarez-Cabrera Ana L. , Kim Kyumin , Zhou Z. Hong , Chen Xiaojiang S.
Published: August 2023

Human APOBEC3 (A3) cytidine deaminases are antiviral factors that are particularly potent against retroviruses. As a countermeasure, HIV-1 uses a viral infectivity factor (Vif) to target specific human A3s for proteasomal degradation. Vif recruits cellular transcription cofactor CBF-β and Cullin-5 (CUL5) RING E3 ubiquitin ligase to bind different A3s distinctively, but how this is accomplished remains unclear in the absence of the atomic structure of the complex. Here, we present the cryo-EM structures of HIV-1 Vif in complex with human A3H, CBF-β and components of CUL5 ubiquitin ligase (CUL5, ELOB, and ELOC). Vif nucleates the entire complex by directly binding four human proteins, A3H, CBF-β, CUL5, and ELOC. The structures reveal a large interface area between A3H and Vif, primarily mediated by an α-helical side of A3H and a five-stranded β-sheet of Vif. This A3H-Vif interface unveils the basis for sensitivity-modulating polymorphism of both proteins, including a previously reported gain-of-function mutation in Vif isolated from HIV/AIDS patients. Our structural and functional results provide insights into the remarkable interplay between HIV and humans and would inform development efforts for anti-HIV therapeutics.
Pan-cancer atlas of somatic core and linker histone mutations
Authors: Bonner Erin R. , Dawood Adam , Gordish-Dressman Heather , Eze Augustine , Bhattacharya Surajit , Yadavilli Sridevi , Mueller Sabine , Waszak Sebastian M. , Nazarian Javad
Published: August 2023

Recent genomic data points to a growing role for somatic mutations altering core histone and linker histone-encoding genes in cancer. However, the prevalence and the clinical and biological implications of histone gene mutations in malignant tumors remain incompletely defined. To address these knowledge gaps, we analyzed somatic mutations in 88 linker and core histone genes across 12,743 tumors from pediatric, adolescent and young adult (AYA), and adult cancer patients. We established a pan-cancer histone mutation atlas contextualized by patient age, survival outcome, and tumor location. Overall, 11% of tumors harbored somatic histone mutations, with the highest rates observed among chondrosarcoma (67%), pediatric high-grade glioma (pHGG, >60%), and lymphoma (>30%). Previously unreported histone mutations were discovered in pHGG and other pediatric brain tumors, extending the spectrum of histone gene alterations associated with these cancers. Histone mutation status predicted patient survival outcome in tumor entities including adrenocortical carcinoma. Recurrent pan-cancer histone mutation hotspots were defined and shown to converge on evolutionarily conserved and functional residues. Moreover, we studied histone gene mutations in 1700 pan-cancer cell lines to validate the prevalence and spectrum of histone mutations seen in primary tumors and derived histone-associated drug response profiles, revealing candidate drugs targeting histone mutant cancer cells. This study presents the first-of-its-kind atlas of both core and linker histone mutations across pediatric, AYA, and adult cancers, providing a framework by which specific cancers may be redefined in the context of histone and chromatin alterations.
Increased hydraulic risk in assemblages of woody plant species predicts spatial patterns of drought-induced mortality
Authors: Sanchez-Martinez Pablo , Mencuccini Maurizio , García-Valdés Raúl , Hammond William M. , Serra-Diaz Josep M. , Guo Wen-Yong , Segovia Ricardo A. , Dexter Kyle G. , Svenning Jens-Christian , Allen Craig , Martínez-Vilalta Jordi
Published: August 2023

Predicting drought-induced mortality (DIM) of woody plants remains a key research challenge under climate change. Here, we integrate information on the edaphoclimatic niches, phylogeny and hydraulic traits of species to model the hydraulic risk of woody plants globally. We combine these models with species distribution records to estimate the hydraulic risk faced by local woody plant species assemblages. Thus, we produce global maps of hydraulic risk and test for its relationship with observed DIM. Our results show that local assemblages modelled as having higher hydraulic risk present a higher probability of DIM. Metrics characterizing this hydraulic risk improve DIM predictions globally, relative to models accounting only for edaphoclimatic predictors or broad functional groupings. The methodology we present here allows mapping of functional trait distributions and elucidation of global macro-evolutionary and biogeographical patterns, improving our ability to predict potential global change impacts on vegetation.
Single-molecule mid-infrared spectroscopy and detection through vibrationally assisted luminescence
Authors: Chikkaraddy Rohit , Arul Rakesh , Jakob Lukas A. , Baumberg Jeremy J.
Published: August 2023

Room-temperature detection of molecular vibrations in the mid-infrared (MIR, λ = 3–30 µm) has numerous applications, including real-time gas sensing, medical imaging and quantum communication. However, existing technologies rely on cooled semiconductor detectors because of thermal noise limitations. One way to overcome this challenge is to upconvert the low-energy MIR photons into high-energy visible wavelengths (λ = 500–800 nm) where detection of single photons is easily achieved using silicon technologies. This process suffers from weak cross-sections and the MIR-to-visible wavelength mismatch, limiting its efficiency. Here we exploit molecular emitters possessing both MIR and visible transitions from molecular vibrations and electronic states, coupled through Franck–Condon factors. By assembling molecules into a plasmonic nanocavity resonant at both MIR and visible wavelengths, and optically pumping them below the electronic absorption band, we show transduction of MIR light. The upconverted signal is observed as enhanced visible luminescence. Combining Purcell-enhanced visible luminescence with enhanced rates of vibrational pumping gives transduction efficiencies of >10%. MIR frequency-dependent upconversion gives the vibrational signatures of molecules assembled in the nanocavity. Transient picocavity formation further confines MIR light down to the single-molecule level. This allows us to demonstrate single-molecule MIR detection and spectroscopy that is inaccessible to any previous detector.
Excited-state observation of active K-Ras reveals differential structural dynamics of wild-type versus oncogenic G12D and G12C mutants
Authors: Hansen Alexandar L. , Xiang Xinyao , Yuan Chunhua , Bruschweiler-Li Lei , Brüschweiler Rafael
Published: August 2023

Despite the prominent role of the K-Ras protein in many different types of human cancer, major gaps in atomic-level information severely limit our understanding of its functions in health and disease. Here, we report the quantitative backbone structural dynamics of K-Ras by solution nuclear magnetic resonance spectroscopy of the active state of wild-type K-Ras bound to guanosine triphosphate (GTP) nucleotide and two of its oncogenic P-loop mutants, G12D and G12C, using a new nanoparticle-assisted spin relaxation method, relaxation dispersion and chemical exchange saturation transfer experiments covering the entire range of timescales from picoseconds to milliseconds. Our combined experiments allow detection and analysis of the functionally critical Switch I and Switch II regions, which have previously remained largely unobservable by X-ray crystallography and nuclear magnetic resonance spectroscopy. Our data reveal cooperative transitions of K-Ras·GTP to a highly dynamic excited state that closely resembles the partially disordered K-Ras·GDP state. These results advance our understanding of differential GTPase activities and signaling properties of the wild type versus mutants and may thus guide new strategies for the development of therapeutics.
Treatment of antibiotic-resistant bacteria colonizing diabetic foot ulcers by OLED induced antimicrobial photodynamic therapy
Authors: Piksa Marta , Fortuna Wojciech , Lian Cheng , Gacka Małgorzata , Samuel Ifor D. W. , Matczyszyn Katarzyna , Pawlik Krzysztof J.
Published: August 2023

We evaluate the efficacy of antimicrobial Photodynamic Therapy (APDT) for inactivating a variety of antibiotic-resistant clinical strains from diabetic foot ulcers. Here we are focused on APDT based on organic light-emitting diodes (OLED). The wound swabs from ten patients diagnosed with diabetic foot ulcers were collected and 32 clinical strains comprising 22 bacterial species were obtained. The isolated strains were identified with the use of mass spectrometry coupled with a protein profile database and tested for antibiotic susceptibility. 74% of isolated bacterial strains exhibited adaptive antibiotic resistance to at least one antibiotic. All strains were subjected to the APDT procedure using an OLED as a light source and 16 µM methylene blue as a photosensitizer. APDT using the OLED led to a large reduction in all cases. For pathogenic bacteria, the reduction ranged from 1.1-log to > 8 log (Klebsiella aerogenes, Enterobacter cloaca, Staphylococcus hominis) even for high antibiotic resistance (MRSA 5-log reduction). Opportunistic bacteria showed a range from 0.4-log reduction for Citrobacter koseri to > 8 log reduction for Kocuria rhizophila. These results show that OLED-driven APDT is effective against pathogens and opportunistic bacteria regardless of drug resistance.
Comparative performances of machine learning algorithms in radiomics and impacting factors
Authors: Decoux Antoine , Duron Loic , Habert Paul , Roblot Victoire , Arsovic Emina , Chassagnon Guillaume , Arnoux Armelle , Fournier Laure
Published: August 2023

There are no current recommendations on which machine learning (ML) algorithms should be used in radiomics. The objective was to compare performances of ML algorithms in radiomics when applied to different clinical questions to determine whether some strategies could give the best and most stable performances regardless of datasets. This study compares the performances of nine feature selection algorithms combined with fourteen binary classification algorithms on ten datasets. These datasets included radiomics features and clinical diagnosis for binary clinical classifications including COVID-19 pneumonia or sarcopenia on CT, head and neck, orbital or uterine lesions on MRI. For each dataset, a train-test split was created. Each of the 126 (9 × 14) combinations of feature selection algorithms and classification algorithms was trained and tuned using a ten-fold cross validation, then AUC was computed. This procedure was repeated three times per dataset. Best overall performances were obtained with JMI and JMIM as feature selection algorithms and random forest and linear regression models as classification algorithms. The choice of the classification algorithm was the factor explaining most of the performance variation (10% of total variance). The choice of the feature selection algorithm explained only 2% of variation, while the train-test split explained 9%.
Nature-inspired spider web shaped UHF RFID reader antenna for IoT and healthcare applications
Authors: Sharif Abubakar , kumar Rajesh , Arshad Kamran , Assaleh Khaled , Chattha Hassan Tariq , Imran Muhammad Ali , Abbasi Qammer Hussain
Published: August 2023

This paper proposes a nature-inspired spider web-shaped ultra-high frequency (UHF) radio frequency identification (RFID) reader antenna and battery-free sensor-based system for healthcare applications. This antenna design consists of eight concentric decagons of various sizes and five straight microstrip lines.These lines are connected to the ground using 50$$\Omega $$Ωresistors from both ends, except for one microstrip line that is reserved for connecting a feeding port. The reader antenna design features fairly strong and uniform electric and magnetic field characteristics. It also exhibits wideband characteristics, covering whole UHF RFID band (860–960 MHz) and providing a tag reading volume of 200$$\times $$×200$$\times $$×20 mm$${^3}$$3. Additionally, it has low gain characteristics, which are necessary for the majority of nearfield applications to prevent the misreading of other tags. Moreover, the current distribution in this design is symmetric throughout the structure, effectively resolving orientation sensitivity issues commonly encountered in low-cost linearly polarized tag antennas. The measurement results show that the reader antenna can read medicine pills tagged using low-cost passive/battery-free RFID tags, tagged expensive jewelry, intervenes solution, and blood bags positioned in various orientations. As a result, the proposed reader antenna-based system is a strong contender for near-field RFID, healthcare, and IoT applications.
Developmental genetic underpinnings of a symbiosis-associated organ in the fungus-farming ambrosia beetle Euwallacea validus
Authors: Spahr Ellie J. , Wasef Fady , Kasson Matt T. , Kijimoto Teiya
Published: August 2023

Mutualistic interactions between organisms often mediate the innovation of traits essential to maintain the relationship. Yet our understanding of these interactions has been stymied due to various hurdles in studying the genetics of non-model animals. To understand the genetic mechanisms by which such traits develop, we examined the function of genes breathless (btl), trachealess (trh), and doublesex in the development of a novel fungus-carrying organ (mycangium) that facilitates an obligate relationship between fungus-farming ambrosia beetles and specific fungal partners. Gene knockdown by RNA interference and subsequent micro-computed tomography visualization suggest btl and trh are required for initiation of mycangia and that tubulogenesis may have been co-opted for early mycangial development.
Lymphocyte detection for cancer analysis using a novel fusion block based channel boosted CNN
Authors: Rauf Zunaira , Khan Abdul Rehman , Sohail Anabia , Alquhayz Hani , Gwak Jeonghwan , Khan Asifullah
Published: August 2023

Tumor-infiltrating lymphocytes, specialized immune cells, are considered an important biomarker in cancer analysis. Automated lymphocyte detection is challenging due to its heterogeneous morphology, variable distribution, and presence of artifacts. In this work, we propose a novel Boosted Channels Fusion-based CNN “BCF-Lym-Detector” for lymphocyte detection in multiple cancer histology images. The proposed network initially selects candidate lymphocytic regions at the tissue level and then detects lymphocytes at the cellular level. The proposed “BCF-Lym-Detector” generates diverse boosted channels by utilizing the feature learning capability of different CNN architectures. In this connection, a new adaptive fusion block is developed to combine and select the most relevant lymphocyte-specific features from the generated enriched feature space. Multi-level feature learning is used to retain lymphocytic spatial information and detect lymphocytes with variable appearances. The assessment of the proposed “BCF-Lym-Detector” show substantial improvement in terms of F-score (0.93 and 0.84 on LYSTO and NuClick, respectively), which suggests that the diverse feature extraction and dynamic feature selection enhanced the feature learning capacity of the proposed network. Moreover, the proposed technique’s generalization on unseen test sets with a good recall (0.75) and F-score (0.73) shows its potential use for pathologists’ assistance.
LAMP1 as a novel molecular biomarker to predict the prognosis of the children with autism spectrum disorder using bioinformatics approaches
Authors: Deng Sisi , Feng Xiang , Yang Miao , Yu Wenjing , Wu Zixuan , Zhu Xu , Song Zhenyan , Cheng Shaowu
Published: August 2023

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that usually manifests in childhood and is thought to be caused by a complex interaction of genetic, environmental, and immune factors. The majority of current ASD diagnostic methods rely on subjective behavioral observation and scale assessment, making early detection difficult. In this study, we confirmed that lysosomal-associated membrane protein 1 (LAMP1), a functional marker of immune cell activation and cytotoxic degranulation, was upregulated in ASD blood, brain cortex, and various genetic animal models or cells using bioinformatics approaches. The prognostic value of LAMP1 was investigated by correlating its expression with clinical ASD rating scales, and the receiver operating characteristic (ROC) curve analysis in ASD also revealed that it has a favorable diagnostic ability in distinguishing ASD from control cohort. According to gene set enrichment analysis (GSEA) results, LAMP1 correlated with genes that were enriched in natural kill and T cell immune function. Taking all of the evidence into account, we discovered that abnormal elevations of LAMP1 mRNA and protein in the blood of ASD children, may influence the development of ASD through its involvement in immune cell activity regulation. This report highlights a novel marker for ASD early detection as well as potential therapeutic targets.
Using domain adaptation for classification of healthy and disease conditions from mobile-captured images of standard 12-lead electrocardiograms
Authors: Gliner Vadim , Makarov Vladimir , Avetisyan Arutyun I. , Schuster Assaf , Yaniv Yael
Published: August 2023

12-lead electrocardiogram (ECG) recordings can be collected in any clinic and the interpretation is performed by a clinician. Modern machine learning tools may make them automatable. However, a large fraction of 12-lead ECG data is still available in printed paper or image only and comes in various formats. To digitize the data, smartphone cameras can be used. Nevertheless, this approach may introduce various artifacts and occlusions into the obtained images. Here we overcome the challenges of automating 12-lead ECG analysis using mobile-captured images and a deep neural network that is trained using a domain adversarial approach. The net achieved an average 0.91 receiver operating characteristic curve on tested images captured by a mobile device. Assessment on image from unseen 12-lead ECG formats that the network was not trained on achieved high accuracy. We further show that the network accuracy can be improved by including a small number of unlabeled samples from unknown formats in the training data. Finally, our models also achieve high accuracy using signals as input rather than images. Using a domain adaptation approach, we successfully classified cardiac conditions on images acquired by a mobile device and showed the generalizability of the classification using various unseen image formats.
Pollution of the Niger Delta with total petroleum hydrocarbons, heavy metals and nutrients in relation to seasonal dynamics
Authors: Anyanwu Ihuoma N. , Beggel Sebastian , Sikoki Francis D. , Okuku Eric O. , Unyimadu John-Paul , Geist Juergen
Published: August 2023

The African Niger Delta is among the world’s most important wetlands in which the ecological effects of intensive oil exploitation and global change are not well documented. We characterized the seasonal dynamics and pollution with total-petroleum-hydrocarbons (TPHs), heavy-metals (HMs) and nutrient-loads in relation to climate-driven variables. High TPH concentrations up to 889 mg/L and HMs up to 13.119 mg/L were found in water samples, with pronounced spatio-temporal variation throughout the year. HM pollution index and contamination factor indicate serious ecological and human health hazards, especially for Cd, Cu, Hg, and Ni. Significant differences in TPHs/HMs were observed between sites and seasons, with correlations between TPHs-HMs, and climate-variables and TPHs-HMs. Nutrient levels, turbidity, salinity, temperature, and SO42- were high and interlinked with the variability of TPHs/HMs being greatest during wet season. These findings suggest an urgent need for improved pollution control in the Niger Delta taking into account the observed spatio-temporal variation and the exacerbation of effects in light of climate change. Given the high levels of contamination, further assessments of exposure effects and bioaccumulation in biota should include future climate change scenarios and effects on humans who intensively depend on the system for drinking water, food supply and livelihood.
RNA-Seq reveals ACTH-induced steroid hormone pathway participating in goat adrenal gland response to castration
Authors: Jing Haijing , Ding Yi , Jiang Xunping , Liu Guiqiong , Sha Yiyu
Published: August 2023

The content of androgen from adrenal is elevated under castration, and the mechanisms of compensatory secretion of adrenal androgen remain unknown. This study was designed to compare the transcript profiles between adrenals from noncastrated, orchiectomized and immunocastrated Yiling goats. Fifteen goats were randomly divided into three groups: pVAX-asd injection (control) group, pVAX-B2L-(G4S)3-kisspeptin-54-asd immunization (PBK-asd) group, and surgical castration (SC) group. Subsequently, serum was collected every two weeks after the initial immunization for hormone assays. At week 14 after immunization, adrenal glands were collected for transcriptome sequencing and qPCR. Serum testosterone concentration was significantly reduced in PBK-asd and SC group, demonstrating the effectiveness of castration. Both surgical and immunized castration resulted in adrenal hyperplasia, and thickness of adrenal cortex elevated. The specific genes involving castration were enriched in many pathways, including Steroid hormone biosynthesis pathway. The adrenocorticotropic hormone (ACTH), which promotes the production of adrenal steroids, and dehydroepiandrosterone (DHEA), a steroid hormone secreted by adrenal glands, both increased after castration. Further construction of co-expression network for transcription genes and traits (including adrenal weight and cortex thickness, ACTH and DHEA concentration) showed that the trait-related genes were enriched in multiple steroid-related pathways. These results showed that adrenal compensatory hyperplasia and androgen secretion caused by castration may involve in ACTH-induced steroid hormone synthesis.