bluuebunny/crossref_metadata_2025 huggingface dataset:
Macroscopic photonic single crystals via seeded growth of DNA-coated colloids
Authors: Hensley Alexander , Videbæk Thomas E. , Seyforth Hunter , Jacobs William M. , Rogers W. Benjamin
Published: July 2023

Photonic crystals—a class of materials whose optical properties derive from their structure in addition to their composition—can be created by self-assembling particles whose sizes are comparable to the wavelengths of visible light. Proof-of-principle studies have shown that DNA can be used to guide the self-assembly of micrometer-sized colloidal particles into fully programmable crystal structures with photonic properties in the visible spectrum. However, the extremely temperature-sensitive kinetics of micrometer-sized DNA-functionalized particles has frustrated attempts to grow large, monodisperse crystals that are required for photonic metamaterial applications. Here we describe a robust two-step protocol for self-assembling single-domain crystals that contain millions of optical-scale DNA-functionalized particles: Monodisperse crystals are initially assembled in monodisperse droplets made by microfluidics, after which they are grown to macroscopic dimensions via seeded diffusion-limited growth. We demonstrate the generality of our approach by assembling different macroscopic single-domain photonic crystals with metamaterial properties, like structural coloration, that depend on the underlying crystal structure. By circumventing the fundamental kinetic traps intrinsic to crystallization of optical-scale DNA-coated colloids, we eliminate a key barrier to engineering photonic devices from DNA-programmed materials.
Strong bulk photovoltaic effect in engineered edge-embedded van der Waals structures
Authors: Liang Zihan , Zhou Xin , Zhang Le , Yu Xiang-Long , Lv Yan , Song Xuefen , Zhou Yongheng , Wang Han , Wang Shuo , Wang Taihong , Shum Perry Ping , He Qian , Liu Yanjun , Zhu Chao , Wang Lin , Chen Xiaolong
Published: July 2023

Bulk photovoltaic effect (BPVE), a second-order nonlinear optical effect governed by the quantum geometric properties of materials, offers a promising approach to overcome the Shockley-Quiesser limit of traditional photovoltaic effect and further improve the efficiency of energy harvesting. Here, we propose an effective platform, the nano edges embedded in assembled van der Waals (vdW) homo- or hetero-structures with strong symmetry breaking, low dimensionality and abundant species, for BPVE investigations. The BPVE-induced photocurrents strongly depend on the orientation of edge-embedded structures and polarization of incident light. Reversed photocurrent polarity can be observed at left and right edge-embedded structures. Our work not only visualizes the unique optoelectronic effect in vdW nano edges, but also provides an effective strategy for achieving BPVE in engineered vdW structures.
HIV-1 promotes ubiquitination of the amyloidogenic C-terminal fragment of APP to support viral replication
Authors: Gu Feng , Boisjoli Marie , Naghavi Mojgan H.
Published: July 2023

HIV-1 replication in macrophages and microglia involves intracellular assembly and budding into modified subsets of multivesicular bodies (MVBs), which support both viral persistence and spread. However, the cellular factors that regulate HIV-1’s vesicular replication remain poorly understood. Recently, amyloid precursor protein (APP) was identified as an inhibitor of HIV-1 replication in macrophages and microglia via an unknown mechanism. Here, we show that entry of HIV-1 Gag into MVBs is blocked by the amyloidogenic C-terminal fragment of APP, “C99”, but not by the non-amyloidogenic product, “C83”. To counter this, Gag promotes multi-site ubiquitination of C99 which controls both exocytic sorting of MVBs and further processing of C99 into toxic amyloids. Processing of C99, entry of Gag into MVBs and release of infectious virus could be suppressed by expressing ubiquitination-defective C99 or by γ-secretase inhibitor treatment, suggesting that APP’s amyloidogenic pathway functions to sense and suppress HIV-1 replication in macrophages and microglia.
Location-selective immobilisation of single-atom catalysts on the surface or within the interior of ionic nanocrystals using coordination chemistry
Authors: Endo Kenichi , Saruyama Masaki , Teranishi Toshiharu
Published: July 2023

Single-atom catalysts dispersed on support materials show excellent heterogeneous catalytic properties that can be tuned using the interactions between the single atoms and the support. Such interactions depend on whether the single atoms are located on the surface or within the interior of the support. However, little is known about immobilising single atoms on the surface or within the interior of supports deliberately and selectively. Herein, such location-selective placement of single atoms is achieved through the choice of metal complex precursor, solvent, and workup procedure. Using CdSe nanoplatelets as a support, a cis-[PtCl2(SO(CH3)2)2] precursor in an aprotic solvent exclusively attaches single Pt atoms on the surface of the support. In contrast, a [PtCl4]2− precursor in a protic solvent followed by amine treatment places 60% of the single Pt atoms inside the support by cation substitution. The surface-adsorbed single Pt atoms show higher stability in photocatalytic hydrogen evolution than the substituted ones, and the preclusion of substitution as internal Pt maximises the activity. Thus, this study provides a viable strategy for the structurally precise synthesis and design of single-atom catalysts.
Potential-dependent transition of reaction mechanisms for oxygen evolution on layered double hydroxides
Authors: Wang Zeyu , Goddard William A. , Xiao Hai
Published: July 2023

Oxygen evolution reaction (OER) is of crucial importance to sustainable energy and environmental engineering, and layered double hydroxides (LDHs) are among the most active catalysts for OER in alkaline conditions, but the reaction mechanism for OER on LDHs remains controversial. Distinctive types of reaction mechanisms have been proposed for the O-O coupling in OER, yet they compose a coupled reaction network with competing kinetics dependent on applied potentials. Herein, we combine grand-canonical methods and micro-kinetic modeling to unravel that the nature of dominant mechanism for OER on LDHs transitions among distinctive types as a function of applied potential, and this arises from the interplay among applied potential and competing kinetics in the coupled reaction network. The theory-predicted overpotentials, Tafel slopes, and findings are in agreement with the observations of experiments including isotope labelling. Thus, we establish a computational methodology to identify and elucidate the potential-dependent mechanisms for electrochemical reactions.
Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells
Authors: Barrena Naroa , Valcárcel Luis V. , Olaverri-Mendizabal Danel , Apaolaza Iñigo , Planes Francisco J.
Published: July 2023

Synthetic lethality (SL) is a promising concept in cancer research. A wide array of computational tools has been developed to predict and exploit synthetic lethality for the identification of tumour-specific vulnerabilities. Previously, we introduced the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to SL developed for genome-scale metabolic networks. The major challenge in our gMCS framework is to go beyond metabolic networks and extend existing algorithms to more complex protein-protein interactions. In this article, we take a step further and incorporate linear regulatory pathways into our gMCS approach. Extensive algorithmic modifications to compute gMCSs in integrated metabolic and regulatory models are presented in detail. Our extended approach is applied to calculate gMCSs in integrated models of human cells. In particular, we integrate the most recent genome-scale metabolic network, Human1, with 3 different regulatory network databases: Omnipath, Dorothea and TRRUST. Based on the computed gMCSs and transcriptomic data, we discovered new essential genes and their associated synthetic lethal for different cancer cell lines. The performance of the different integrated models is assessed with available large-scale in-vitro gene silencing data. Finally, we discuss the most relevant gene essentiality predictions based on published literature in cancer research.
Maternal and neonatal outcomes of COVID-19 vaccination during pregnancy, a systematic review and meta-analysis
Authors: Marchand Greg , Masoud Ahmed Taher , Grover Sandeep , King Alexa , Brazil Giovanna , Ulibarri Hollie , Parise Julia , Arroyo Amanda , Coriell Catherine , Goetz Sydnee , Moir Carmen , Govindan Malini , Moberly Atley , Proctor Anna , Sainz Katelyn , Blumrick Richard
Published: July 2023

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is associated with increased pregnancy complications. Despite effective vaccination strategies for the general population, the evidence on the safety and efficacy of Coronavirus disease 2019 (COVID-19) vaccinations in pregnancy is limited due to a lack of well-powered studies. The present study compares the maternal, neonatal, and immunological outcomes between vaccinated pregnant and unvaccinated pregnant women using a systematic review and meta-analysis approach. We included 37 studies with a total of 141,107 pregnant women (36.8% vaccinated) spread across all outcomes. Our evidence indicates a higher rate of cesarean section in the 1898 vaccinated pregnant women compared to the 6180 women who did not receive vaccination (OR = 1.20, CI = (1.05, 1.38), P = 0.007, I2 = 45%). Regarding immunological outcomes, the risk of SARS-CoV-2 infection during pregnancy or postpartum was significantly reduced in 6820 vaccinated pregnant women compared to 17,010 unvaccinated pregnant women (OR = 0.25, CI = 0.13–0.48, P < 0.0001, I2 = 61%), as evident from qualitative assessment indicating significantly higher postpartum antibody titers compared to that observed in both unvaccinated mothers and mothers who have recently recovered from a SARS-CoV-2 infection. Our analysis represents high quality evidence showing that COVID-19 vaccination effectively raises antibody titers against SARS-CoV-2. This may confer protection against infection during pregnancy and the postpartum period. In addition to being protective against SARS-CoV-2, the vaccine was associated with decreased odds of preterm delivery. Furthermore, COVID-19 vaccination may also be associated with higher odds of cesarean section.
Distribution and abundance of Peleng Tarsier (Tarsius pelengensis) in Banggai Island group, Indonesia
Authors: Syahrullah Fakhri Naufal , Maddus Un , Mustari Abdul Haris , Gursky Sharon , Indrawan Mochamad
Published: July 2023

The Peleng tarsier (Tarsius pelengensis) is poorly known primate, with a range limited to Banggai island-group, Central Sulawesi, Indonesia. It was classified as “Endangered” by IUCN in 2017 based on extremely limited demographic and distributional data. The aim of this study was to collect and analyze data on the population and distribution of Peleng tarsiers. Surveys were conducted over approximately 5 months in 2017 and 2018 across Peleng and the neighboring islands of Banggai, Labobo, and Bangkurung. We determined that tarsiers only occur on Peleng and Banggai Island. The average population density in Peleng and Banggai was estimated to be 234 individuals/km2. This is comparable to the broad ranges of tarsier densities throughout Sulawesi and offshore islands. Peleng tarsiers were found in all elevations (0–937 m above sea level) and nearly all vegetated habitats in Peleng island. Using the IUCN criteria for determining conservation status, in conjunction with our new data, we believe that the Peleng tarsier population should be classified as “Vulnerable”.
Decoding information about cognitive health from the brainwaves of sleep
Authors: Adra Noor , Dümmer Lisa W. , Paixao Luis , Tesh Ryan A. , Sun Haoqi , Ganglberger Wolfgang , Westmeijer Mike , Da Silva Cardoso Madalena , Kumar Anagha , Ye Elissa , Henry Jonathan , Cash Sydney S. , Kitchener Erin , Leveroni Catherine L. , Au Rhoda , Rosand Jonathan , Salinas Joel , Lam Alice D. , Thomas Robert J. , Westover M. Brandon
Published: July 2023

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the “brain age index” (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed “sleep cognitive indices” (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson’s r = 0.37) and fluid cognition (Pearson’s r = 0.56), while BAI correlated only with crystallized cognition (Pearson’s r = − 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.
A perceptual field test in object experts using gaze-contingent eye tracking
Authors: Hagen Simen , Vuong Quoc C. , Jung Liandra , Chin Michael D. , Scott Lisa S. , Tanaka James W.
Published: July 2023

A hallmark of expert object recognition is rapid and accurate subordinate-category recognition of visually homogenous objects. However, the perceptual strategies by which expert recognition is achieved is less known. The current study investigated whether visual expertise changes observers’ perceptual field (e.g., their ability to use information away from fixation for recognition) for objects in their domain of expertise, using a gaze-contingent eye-tracking paradigm. In the current study, bird experts and novices were presented with two bird images sequentially, and their task was to determine whether the two images were of the same species (e.g., two different song sparrows) or different species (e.g., song sparrow and chipping sparrow). The first study bird image was presented in full view. The second test bird image was presented fully visible (full-view), restricted to a circular window centered on gaze position (central-view), or restricted to image regions beyond a circular mask centered on gaze position (peripheral-view). While experts and novices did not differ in their eye-movement behavior, experts’ performance on the discrimination task for the fastest responses was less impaired than novices in the peripheral-view condition. Thus, the experts used peripheral information to a greater extent than novices, indicating that the experts have a wider perceptual field to support their speeded subordinate recognition.
High-resolution precipitation monitoring with a dense seismic nodal array
Authors: Hua Junlin , Wu Mengxi , Mulholland Jake P. , Neelin J. David , Tsai Victor C. , Trugman Daniel T.
Published: July 2023

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.
Araucaria heterophylla oleogum resin essential oil is a novel aldose reductase and butyryl choline esterase enzymes inhibitor: in vitro and in silico evidence
Authors: Soliman Amal F. , Sabry Mohamed A. , Abdelwahab Gehad
Published: July 2023

The essential oil isolated by hydrodistillation of the oleogum resin of Araucaria heterophylla has been analyzed by GC–MS. Twenty-four components accounting to 99.89% of the total detected constituents of this essential oil were identified. The major ones were: caryophyllene oxide (14.8%), ( +)-sabinene (12.07%), D-limonene (11.22%), caryophyllene (10.36%), α-copaene (8.00%), β-pinene (6.44%), trans-verbenol (5.88%) and α-pinene oxide (5.18%). The in vitro inhibitory activities of this oil against aldose reductase, BuCHE, COX-2 and SARS-CoV-2 Mpro enzymes were evaluated. This revealed promising inhibitory activity of the essential oil against both aldose reductase and BuCHE enzymes. The molecular docking study of the major components of the Araucaria heterophylla essential oil was carried out to correlate their binding modes and affinities for aldose reductase and BuCHE enzymes with the in vitro results. In conclusion, the in vitro inhibitory activity of the essential oil attributed to the synergistic effect between its components and the in silico study suggested that compounds containing epoxide and hydroxyl groups may be responsible for this activity. This study is preliminary screening for the oil to be used as antidiabetic cataract and Alzheimer’s disease therapeutics and further investigations may be required.
Machine learning-based guilt detection in text
Authors: Meque Abdul Gafar Manuel , Hussain Nisar , Sidorov Grigori , Gelbukh Alexander
Published: July 2023

We introduce a novel Natural Language Processing (NLP) task called guilt detection, which focuses on detecting guilt in text. We identify guilt as a complex and vital emotion that has not been previously studied in NLP, and we aim to provide a more fine-grained analysis of it. To address the lack of publicly available corpora for guilt detection, we created VIC, a dataset containing 4622 texts from three existing emotion detection datasets that we binarized into guilt and no-guilt classes. We experimented with traditional machine learning methods using bag-of-words and term frequency-inverse document frequency features, achieving a 72% f1 score with the highest-performing model. Our study provides a first step towards understanding guilt in text and opens the door for future research in this area.
Noradrenergic projections regulate the acquisition of classically conditioned eyelid responses in wild-type and are impaired in kreisler mice
Authors: Porras-García Elena , Mas-Nieto Magdalena , Delgado-García José María , Domínguez-del-Toro Eduardo
Published: July 2023

During embryonic development, heterozygous mutant kreisler mice undergo ectopic expression of the Hoxa3 gene in the rostral hindbrain, affecting the opioid and noradrenergic systems. In this model, we have investigated behavioral and cognitive processes in their adulthood. We confirmed that pontine and locus coeruleus neuronal projections are impaired, by using startle and pain tests and by analyzing immunohistochemical localization of tyrosine hydroxylase. Our results showed that, even if kreisler mice are able to generate eyelid reflex responses, there are differences with wild-types in the first component of the response (R1), modulated by the noradrenergic system. The acquisition of conditioned motor responses is impaired in kreisler mice when using the trace but not the delay paradigm, suggesting a functional impairment in the hippocampus, subsequently confirmed by reduced quantification of alpha2a receptor mRNA expression in this area but not in the cerebellum. Moreover, we demonstrate the involvement of adrenergic projection in eyelid classical conditioning, as clonidine prevents the appearance of eyelid conditioned responses in wild-type mice. In addition, hippocampal motor learning ability was restored in kreisler mice by administration of adrenergic antagonist drugs, and a synergistic effect was observed following simultaneous administration of idazoxan and naloxone.
COVID-19 infection inference with graph neural networks
Authors: Song Kyungwoo , Park Hojun , Lee Junggu , Kim Arim , Jung Jaehun
Published: July 2023

Infectious diseases spread rapidly, and epidemiological surveys are vital to detect high-risk transmitters and reduce transmission rates. To enhance efficiency and reduce the burden on epidemiologists, an automatic tool to assist with epidemiological surveys is necessary. This study aims to develop an automatic epidemiological survey to predict the influence of COVID-19-infected patients on future additional infections. To achieve this, the study utilized a dataset containing interaction information between confirmed cases, including contact order, contact times, and movement routes, as well as individual properties such as symptoms. Graph neural networks (GNNs) were used to incorporate interaction information and individual properties. Two variants of GNNs, graph convolutional and graph attention networks, were utilized, and the results showed that the graph-based models outperformed traditional machine learning models. For the area under the curve, the 2nd, 3rd, and 4th order spreading predictions showed higher performance by 0.200, 0.269, and 0.190, respectively. The results show that the contact information of an infected person is crucial data that can help predict whether that person will affect future infections. Our findings suggest that incorporating the relationships between an infected person and others can improve the effectiveness of an automatic epidemiological survey.
Diacerein ameliorates cholestasis-induced liver fibrosis in rat via modulating HMGB1/RAGE/NF-κB/JNK pathway and endoplasmic reticulum stress
Authors: Abdelfattah Amira Mohammed , Mahmoud Shireen Sami , EL-wafaey Dalia Ibrahim , Abdelgeleel Heba Mahmoud , Abdelhamid Amira Mohamed
Published: July 2023

Diacerein is an interleukin (IL)-1β inhibitor approved for osteoarthritis. This study aimed to investigate the potential anti-fibrotic effect of diacerein against bile duct ligation (BDL)-induced liver fibrosis. Forty male Wistar rats were divided into: sham-operated group, BDL group, and BDL groups treated with diacerein at 10, 30, and 50 mg/kg/day starting two days before surgery and continued for 4 weeks. Diacerein decreased the hepatic injury markers and alleviated oxidative stress triggered by BDL by reducing hepatic malondialdehyde (MDA) and increasing hepatic superoxide dismutase (SOD) levels. Diacerein mitigated BDL-induced inflammation via lowering hepatic levels and mRNA expression of high mobility group box 1 (HMGB1), nuclear factor-κB (NF-κB), and IL-1β. The hepatic gene expression of Advanced Glycation End products Receptor (RAGE) gene and immunohistochemical expression of some ER stress markers, e.g., glucose-regulated protein 78 (GRP78), inositol-requiring enzyme 1 (IRE1α), protein kinase RNA-like endoplasmic reticulum kinase (PERK), CCAAT/enhancer-binding protein homologous protein (CHOP), and phosphorylated c-Jun N-terminal kinase protein contents were lowered by diacerein. Furthermore, diacerein suppressed the hepatic levels of fibrogenic mediators, e.g., Transforming growth factor β1 (TGF˗β1), α- smooth muscle actin (α-SMA), collagen 1, and hydroxyproline, as well as the apoptotic caspase 3 and BAX immunostaining in BDL rats. The histopathological abnormalities induced by BDL significantly improved. Our study demonstrated that diacerein exhibited an antifibrotic effect by inhibiting HMGB1/RAGE/NF-κB/JNK pathway, and ER stress. Better protection was observed with increasing the dose.
Reverse transcription-quantitative PCR (RT-qPCR) without the need for prior removal of DNA
Authors: Đermić Damir , Ljubić Sven , Matulić Maja , Procino Alfredo , Feliciello Maria Chiara , Ugarković Đurđica , Feliciello Isidoro
Published: July 2023

The procedure illustrated in this paper represents a new method for transcriptome analysis by PCR (Polymerase Chain Reaction), which circumvents the need for elimination of potential DNA contamination. Compared to the existing methodologies, our method is more precise, simpler and more reproducible because it preserves the RNA’s integrity, does not require materials and/or reagents that are used for elimination of DNA and it also reduces the number of samples that should be set up as negative controls. This novel procedure involves the use of a specifically modified primer during reverse transcription step, which contains mismatched bases, thus producing cDNA molecules that differ from genomic DNA. By using the same modified primer in PCR amplification, only cDNA template is amplified since genomic DNA template is partially heterologous to the primer. In this way, amplification by PCR is unaffected by any potential DNA contamination since it is specific only for the cDNA template. Furthermore, it accurately reflects the initial RNA concentration of the sample, which is prone to changes due to various physical or enzymatic treatments commonly used by the current methodologies for DNA elimination. The method is particularly suitable for quantification of highly repetitive DNA transcripts, such as satellite DNA.
Aesthetics and neural network image representations
Authors: Janik Romuald A.
Published: July 2023

We analyze the spaces of images encoded by generative neural networks of the BigGAN architecture. We find that generic multiplicative perturbations of neural network parameters away from the photo-realistic point often lead to networks generating images which appear as “artistic renditions” of the corresponding objects. This demonstrates an emergence of aesthetic properties directly from the structure of the photo-realistic visual environment as encoded in its neural network parametrization. Moreover, modifying a deep semantic part of the neural network leads to the appearance of symbolic visual representations. None of the considered networks had any access to images of human-made art.
Analysis of macerated ticks using Boolean logic gating colorimetric isothermal nucleic acid assays for Lyme Borrelia and Ixodes scapularis ticks
Authors: Bhadra Sanchita , Esteve-Gasent Maria D. , Ellington Andrew D.
Published: July 2023

Lyme disease, one of the most common tickborne diseases, has been rapidly spreading in parallel with the expansion of the range of its tick vector. Better tick surveillance efforts are needed to accurately estimate disease risk and to guide public health and clinical management. We have developed two multiplex loop-mediated isothermal amplification (LAMP) reactions coupled with oligonucleotide strand displacement (OSD) probes to identify the tick host, Ixodes scapularis, and the Lyme disease pathogen, Borrelia burgdorferi, they carry. In each multiplex LAMP-OSD assay the co-presence of two target sequences is computed at the DNA level by linking the two corresponding amplicons and detecting the co-product on colorimetric lateral flow dipsticks. In tests with synthetic DNA, the co-presence of as few as four copies of input DNA could be detected, without producing spurious signals. Most importantly, though, the LAMP-OSD assay is amenable to being carried out directly with macerated tick samples, without any sample preparation. In such field conditions, assays performed robustly and demonstrated 97–100% sensitivity and 100% specificity with both field-collected and lab-raised artificially infected ticks. Such easy-to-use, arthropod and pathogen-specific assays would be well suited to field and near patient use without relying on complex instrumentation or infrastructure.
Green nanocoating-based polysaccharides decorated with ZnONPs doped Egyptian kaolinite for antimicrobial coating paper
Authors: Hasanin Mohamed S. , El Saied Houssni , Morsy Fatma A. , Hassan Abdel Latif Rokbaa Hanaa
Published: July 2023

Paper coating plays an important role in the paper properties, printability and application. The nanocoating is a multifunction layer that provides the paper with unique features. In this work, nanocoating formulas were prepared using a green method and component. The nanocoating formulas were based on biopolymers nanostarch NSt and nanochitosan NCh (NCS) decorated with Egyptian kaolinite Ka doped with zinc nanoparticles NCS@xka/ZnONPs (x represents different ratios) support for multifunctional uses. The nanocoating formulas were characterized using a physiochemical analysis as well as a topographical study. FTIR, XRD, SEM and TEM techniques were used. Additionally, the antimicrobial activity of the tested samples was assessed against six microorganisms including Gram-negative and Gram-positive bacteria. The prepared nanocoating formulas affirmed excellent antimicrobial activity as a broad-spectrum antimicrobial active agent with excellent activity against all representative microbial communities. The nanocoating with the highest ratio of Ka/ZnONPs (NCS@40 ka/ZnONPs) showed excellent antimicrobial activity with an inhibition percentage of more than 70% versus all microorganisms presented. The paper was coated with the prepared suspensions and characterized concerning optical, mechanical and physical properties. When Ka/ZnONPs were loaded into NCS in a variety of ratios, the characteristics of coated paper were enhanced compared to blank paper. The sample NCS@40 ka/ZnONPs increased tensile strength by 11%, reduced light scattering by 12%, and improved brightness and whiteness by 1%. Paper coated with NCh suspension had 35.32% less roughness and 188.6% less porosity. When coated with the sample NCS@10 ka/ZnONPs, the coated paper's porosity was reduced by 94% and its roughness was reduced by 10.85%. The greatest reduction in water absorptivity was attained by coating with the same sample, with a reduction percentage of 132%.
Visual experience shapes the Bouba-Kiki effect and the size-weight illusion upon sight restoration from congenital blindness
Authors: Piller Sophia , Senna Irene , Ernst Marc O.
Published: July 2023

The Bouba-Kiki effect is the systematic mapping between round/spiky shapes and speech sounds (“Bouba”/“Kiki”). In the size-weight illusion, participants judge the smaller of two equally-weighted objects as being heavier. Here we investigated the contribution of visual experience to the development of these phenomena. We compared three groups: early blind individuals (no visual experience), individuals treated for congenital cataracts years after birth (late visual experience), and typically sighted controls (visual experience from birth). We found that, in cataract-treated participants (tested visually/visuo-haptically), both phenomena are absent shortly after sight onset, just like in blind individuals (tested haptically). However, they emerge within months following surgery, becoming statistically indistinguishable from the sighted controls. This suggests a pivotal role of visual experience and refutes the existence of an early sensitive period: A short period of experience, even when gained only years after birth, is sufficient for participants to visually pick-up regularities in the environment, contributing to the development of these phenomena.
Identifying oscillatory brain networks with hidden Gaussian graphical spectral models of MEEG
Authors: Paz-Linares Deirel , Gonzalez-Moreira Eduardo , Areces-Gonzalez Ariosky , Wang Ying , Li Min , Martinez-Montes Eduardo , Bosch-Bayard Jorge , Bringas-Vega Maria L. , Valdes-Sosa Mitchell , Valdes-Sosa Pedro A.
Published: July 2023

Identifying the functional networks underpinning indirectly observed processes poses an inverse problem for neurosciences or other fields. A solution of such inverse problems estimates as a first step the activity emerging within functional networks from EEG or MEG data. These EEG or MEG estimates are a direct reflection of functional brain network activity with a temporal resolution that no other in vivo neuroimage may provide. A second step estimating functional connectivity from such activity pseudodata unveil the oscillatory brain networks that strongly correlate with all cognition and behavior. Simulations of such MEG or EEG inverse problem also reveal estimation errors of the functional connectivity determined by any of the state-of-the-art inverse solutions. We disclose a significant cause of estimation errors originating from misspecification of the functional network model incorporated into either inverse solution steps. We introduce the Bayesian identification of a Hidden Gaussian Graphical Spectral (HIGGS) model specifying such oscillatory brain networks model. In human EEG alpha rhythm simulations, the estimation errors measured as ROC performance do not surpass 2% in our HIGGS inverse solution and reach 20% in state-of-the-art methods. Macaque simultaneous EEG/ECoG recordings provide experimental confirmation for our results with 1/3 times larger congruence according to Riemannian distances than state-of-the-art methods.
Novel Zn metal–organic framework with the thiazole sites for fast and efficient removal of heavy metal ions from water
Authors: Karbalaee Hosseini Akram , Tadjarodi Azadeh
Published: July 2023

Pollution of water by heavy metal ions such as Pb2+ and Hg2+ is considered as an important issue, because of the potential toxic effects these ions impose on environmental ecosystems and human health. A new Zn-based metal–organic framework, [Zn2(DPTTZ) (OBA)2] (IUST-2), was synthesized through a solvothermal method by the reaction of 2, 5-di (4- pyridyl) thiazolo [5, 4-d] thiazole ligand (DPTTZ), the “V-shape” 4,4'-oxybis (benzoic acid) ligand (OBA) and zinc nitrate (Zn(NO3)2·6H2O). This novel MOF has been characterized by several analysis techniques such as fourier transform infrared spectroscopy (FT-IR), elemental analysis (EA), powder x-ray diffraction (PXRD), thermogravimetry analysis (TGA), differential thermal analysis (DTA), field emission scanning electron microscopy (FE-SEM), Brunauer–Emmett–Teller (BET) surface area analysis and single-crystal X-ray diffraction (SXRD). This 3D MOF was tested for removing Pb2+ and Hg2+ ions from water. The factors that were investigated on the elimination of Pb2+ and Hg2+ ions were of pH, adsorption time, and the effect of initial ions concentration. According to the results, this particular Zn-MOF had significant performance in eliminating Pb2+ and Hg2+ ions from water with a removal efficiency of more than 97% and 87% within 3 min, respectively.
Efficient machine learning of solute segregation energy based on physics-informed features
Authors: Ma Zongyi , Pan Zhiliang
Published: July 2023

Machine learning models solute segregation energy based on appropriate features of segregation sites. Lumping many features together can give a decent accuracy but may suffer the curse of dimensionality. Here, we modeled the segregation energy with efficient machine learning using physics-informed features identified based on solid physical understanding. The features outperform the many features used in the literature work and the spectral neighbor analysis potential features by giving the best balance between accuracy and feature dimension, with the extent depending on machine learning algorithms and alloy systems. The excellence is attributed to the strong relevance to segregation energies and the mutual independence ensured by physics. In addition, the physics-informed features contain much less redundant information originating from the energy-only-concerned calculations in equilibrium states. This work showcases the merit of integrating physics in machine learning from the perspective of feature identification other than that of physics-informed machine learning algorithms.
Establishing and testing a robot-based platform to enable the automated production of nanoparticles in a flexible and modular way
Authors: Dembski Sofia , Schwarz Thomas , Oppmann Maximilian , Bandesha Shahbaz Tareq , Schmid Jörn , Wenderoth Sarah , Mandel Karl , Hansmann Jan
Published: July 2023

Robotic systems facilitate relatively simple human–robot interaction for non-robot experts, providing the flexibility to implement different processes. In this context, shorter process times, as well as an increased product and process quality could be achieved. Robots short time-consuming processes, take over ergonomically unfavorable tasks and work efficiently all the time. In addition, flexible production is possible while maintaining or even increasing safety. This study describes the successful development of a dual-arm robot-based modular infrastructure and the establishment of an automated process for the reproducible production of nanoparticles. As proof of concept, a manual synthesis protocol for silica nanoparticle preparation with a diameter of about 200 nm as building blocks for photonic crystals was translated into a fully automated process. All devices and components of the automated system were optimized and adapted according to the synthesis requirements. To demonstrate the benefit of the automated nanoparticle production, manual (synthesis done by lab technicians) and automated syntheses were benchmarked. To this end, different processing parameters (time of synthesis procedure, accuracy of dosage etc.) and the properties of the produced nanoparticles were compared. We demonstrate that the use of the robot not only increased the synthesis accuracy and reproducibility but reduced the personnel time and costs up to 75%.
Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics
Authors: Solar Peter , Valekova Hana , Marcon Petr , Mikulka Jan , Barak Martin , Hendrych Michal , Stransky Matyas , Siruckova Katerina , Kostial Martin , Holikova Klara , Brychta Jindrich , Jancalek Radim
Published: July 2023

Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image. For this purpose, the line of interest (LOI) was marked on each ADC map to cross all of the RELs’ compartments. Using a machine learning approach, we analyzed the LOI between two representatives of the RELs, namely, brain abscess and glioblastoma (GBM). The diagnostic ability of the selected parameters as predictors for the machine learning algorithms was assessed using two models, the k-NN model and the SVM model with a Gaussian kernel. With the k-NN machine learning method, 80% of the abscesses and 100% of the GBM were classified correctly at high accuracy. Similar results were obtained via the SVM method. The proposed assessment of the LOI offers a new approach for evaluating ADC maps obtained from different RELs and contributing to the standardization of the ADC map assessment.
Modulation of toxicity effects of CuSO4 by sulfated polysaccharides extracted from brown algae (Sargassum tenerrimum) in Danio rerio as a model
Authors: Zargari Ashkan , Nejatian Mohammad , Abbaszadeh Sepideh , Jahanbin Kambiz , Bagheri Tahereh , Hedayati Aliakbar , Sheykhi Monireh
Published: July 2023

Copper is widely used in agriculture and aquaculture due to its high disinfection properties and relatively low cost. However, the increase in copper concentration due to evaporation can lead to water reservoir pollution, which can harm the health of consumers. The present study aimed to determine the role of sulfated polysaccharides (SPs) extracted from Sargassum tenerimum algae in reducing lesions caused by the heavy metal copper. Zebrafish (Danio rerio) were used as a human model in five treatments. The negative and positive control groups were fed a diet containing zero percent of SPs, while the experimental groups were fed 0.5%, 1%, and 1.5% of SPs in three treatments for 56 days, finally CuSO4 was exposed only to the positive control group and the groups fed with SPs. Results showed a significant decrease in the activity level of ALT enzymes (39–16 U/mL), AST (67–46 U/mL), and ALP (485–237 U/mL), confirming the results obtained from histopathological studies in CuSO4 exposed groups. The addition of SPs to the diet resulted in a significant reduction (sig < 0.05) of mortalities due to the decrease of tissue damage. Additionally, due to the anti-inflammatory properties and the protective effect of SPs, a significant decrease (sig < 0.05) was observed in the relative expression of Il-1β and Tnf-α genes.
Spinal cord tethering and syringomyelia after trauma: impact of age and surgical outcome
Authors: Bratelj Denis , Stalder Susanne , Capone Crescenzo , Jaszczuk Phillip , Dragalina Cristian , Pötzel Tobias , Gebhard Catherine , Fiechter Michael
Published: July 2023

Posttraumatic spinal cord tethering and syringomyelia frequently lead to progressive neurological loss. Although several studies demonstrated favourable outcome following spinal cord detethering with/without shunting, additional research is required as no clear consensus exists over the ideal treatment strategy and knowledge about prognostic demographic determinants is currently limited. In this investigation, we retrospectively investigated 67 patients (56 men, 11 women) who were surgically treated and followed for symptomatic spinal cord tethering and syringomyelia from 2012 to 2022 at our center. Age (B-coefficient 0.396) and severity of trauma to the spinal cord (B-coefficient − 0.462) have been identified as independent predictors for the rate of development of symptomatic spinal cord tethering and syringomyelia (p < 0.001). Following untethering surgery including expansion duraplasty with/without shunting, 65.9% of patients demonstrated an improvement of neurological loss (p < 0.001) whereas 50.0% of patients displayed amelioration of spasticity and/or neuropathic pain (p < 0.001). Conclusively, active screening for symptomatic spinal cord tethering and syringomyelia, particularly in younger patients with severe spinal trauma, is crucial as surgical untethering with/without shunting is able to achieve favourable clinical outcomes. This knowledge may enable clinicians to tailor treatment strategies in spinal cord injury patients suffering from progressive neurological loss towards a more optimal and personalized patient care.
Carvacrol attenuated lipopolysaccharide-induced intestinal injury by down-regulating TLRs gene expression and regulating the gut microbiota in rabbit
Authors: Wu Diange , Xia Miao , Yan An , Jiang Haotian , Fan Jiaqi , Zhou Siyuan , Wei Xu , Liu Shudong , Chen Baojiang
Published: July 2023

Carvacrol (CAR) is a plant extract that has been reported to enhance antioxidant activity in animals. However, the effect of CAR on the intestinal health of rabbits is poorly understood. Here, we investigated whether CAR exerts protective effects on the intestinal health of rabbits following lipopolysaccharide (LPS) challenge and whether these effects were mediated via the reduction of intestinal inflammation and the regulation of the intestinal flora. Intestinal damage was assessed in LPS-challenged rabbits treated or not with CAR. The serum levels of inflammatory factors were assessed by enzyme-linked immunosorbent assay. Histopathological changes in the ileum and cecum were examined using hematoxylin and eosin staining. The relative gene expression levels of inflammatory factors and tight junction proteins in the rabbit cecum were determined by qRT-PCR. High-throughput sequencing analysis of the microbial 16S rRNA gene was performed using the Illumina NovaSeq Platform. The results showed that CAR can prevent intestinal inflammation and damage as well as mitigate gut dysbiosis in rabbits following LPS challenge. Our study provides a theoretical reference for the application of dietary CAR in rabbit production.
Complexity synchronization: a measure of interaction between the brain, heart and lungs
Authors: Mahmoodi Korosh , Kerick Scott E. , Grigolini Paolo , Franaszczuk Piotr J. , West Bruce J.
Published: July 2023

Herein we address the measurable consequences of the network effect (NE) on time series generated by different parts of the brain, heart, and lung organ-networks (ONs), which are directly related to their inter-network and intra-network interactions. Moreover, these same physiologic ONs have been shown to generate crucial event (CE) time series, and herein are shown, using modified diffusion entropy analysis (MDEA) to have scaling indices with quasiperiodic changes in complexity, as measured by scaling indices, over time. Such time series are generated by different parts of the brain, heart, and lung ONs, and the results do not depend on the underlying coherence properties of the associated time series but demonstrate a generalized synchronization of complexity. This high-order synchrony among the scaling indices of EEG (brain), ECG (heart), and respiratory time series is governed by the quantitative interdependence of the multifractal behavior of the various physiological ONs’ dynamics. This consequence of the NE opens the door for an entirely general characterization of the dynamics of complex networks in terms of complexity synchronization (CS) independently of the scientific, engineering, or technological context. CS is truly a transdisciplinary effect.
A two-sample mendelian randomization analysis investigates associations between gut microbiota and infertility
Authors: Li Taozhi , Shao Wenbo , Wang Yukun , Zhou Rui , Yun Zhangjun , He Yalin , Wu Yu
Published: July 2023

Observational studies have provided evidence of a correlation between alterations in gut microbiota composition and infertility. However, concrete proof supporting the causal relationship is still lacking. We performed a Mendelian randomization study to assess whether genetically gut microbiota composition influences the risk of infertility. The genetic data pertaining to gut microbiota were obtained from a genome-wide association study meta-analysis, which was conducted among 24 cohorts (18,340 participants) from the international MiBioGen consortium. By the primary method of assessing causality, we have identified 2 family taxa, 2 genus taxa, and 1 order taxa that were linked to a low risk of male infertility, while 1 genus taxa were associated with a high risk of male infertility. Furthermore, we have discovered 6 genus taxa, 1 phylum taxa, 1 class taxa, 1 order taxa, and 1 family taxa that were associated with a low risk of female infertility, while 1 genus taxa were linked to a high risk of female infertility. This study successfully confirmed that there was a causal link between gut microbiota and infertility. The identification of these specific strains through genetic prediction offers a valuable insight for early diagnosis, prevention, and treatment of infertility.