bluuebunny/crossref_metadata_2025 huggingface dataset:
Abnormal global signal topography of self modulates emotion dysregulation in major depressive disorder
Authors: Keskin Kaan , Eker Mehmet Çağdaş , Gönül Ali Saffet , Northoff Georg
Published: April 2023

Major depressive disorder (MDD) is a complex mental disorder featured by an increased focus on the self and emotion dysregulation whose interaction remains unclear, though. At the same time, various studies observed abnormal representation of global fMRI brain activity in specifically those regions, e.g., cortical midline structure (CMS) in MDD that are associated with the self. Are the self and its impact on emotion regulation related to global brain activity unevenly represented in CMS relative to non-CMS? Addressing this yet open question is the main goal of our study. We here investigate post-acute treatment responder MDD and healthy controls in fMRI during an emotion task involving both attention and reappraisal of negative and neutral stimuli. We first demonstrate abnormal emotion regulation with increased negative emotion severity on the behavioral level. Next, focusing on a recently established three-layer topography of self, we show increased representation of global fMRI brain activity in specifically those regions mediating the mental (CMS) and exteroceptive (Right temporo-parietal junction and mPFC) self in post-acute MDD during the emotion task. Applying a complex statistical model, namely multinomial regression analyses, we show that increased global infra-slow neural activity in the regions of the mental and exteroceptive self modulates the behavioral measures of specifically negative emotion regulation (emotion attention and reappraisal/suppression). Together, we demonstrate increased representation of global brain activity in regions of the mental and exteroceptive self, including their modulation of negative emotion dysregulation in specifically the infra-slow frequency range (0.01 to 0.1 Hz) of post-acute MDD. These findings support the assumption that the global infra-slow neural basis of the increased self-focus in MDD may take on the role as basic disturbance in that it generates the abnormal regulation of negative emotions.
A new glance at autophagolysosomal-dependent or -independent function of transcriptional factor EB in human cancer
Authors: Wang Ting , Qin Yi , Ye Zeng , Jing De-sheng , Fan Gui-xiong , Liu Meng-qi , Zhuo Qi-feng , Ji Shun-rong , Chen Xue-min , Yu Xian-jun , Xu Xiao-wu , Li Zheng
Published: April 2023

Autophagy-lysosome system plays a variety of roles in human cancers. In addition to being implicated in metabolism, it is also involved in tumor immunity, remodeling the tumor microenvironment, vascular proliferation, and promoting tumor progression and metastasis. Transcriptional factor EB (TFEB) is a major regulator of the autophagy-lysosomal system. With the in-depth studies on TFEB, researchers have found that it promotes various cancer phenotypes by regulating the autophagolysosomal system, and even in an autophagy-independent way. In this review, we summarize the recent findings about TFEB in various types of cancer (melanoma, pancreatic ductal adenocarcinoma, renal cell carcinoma, colorectal cancer, breast cancer, prostate cancer, ovarian cancer and lung cancer), and shed some light on the mechanisms by which it may serve as a potential target for cancer treatment.
Differential effects of CMV infection on the viability of cardiac cells
Authors: Yadav Santosh K. , Gawargi Flobater I. , Hasan Mohammad H. , Tandon Ritesh , Upton Jason W. , Mishra Paras K.
Published: April 2023

Cytomegalovirus (CMV) is a widely prevalent herpesvirus that reaches seroprevalence rates of up to 95% in several parts of the world. The majority of CMV infections are asymptomatic, albeit they have severe detrimental effects on immunocompromised individuals. Congenital CMV infection is a leading cause of developmental abnormalities in the USA. CMV infection is a significant risk factor for cardiovascular diseases in individuals of all ages. Like other herpesviruses, CMV regulates cell death for its replication and establishes and maintains a latent state in the host. Although CMV-mediated regulation of cell death is reported by several groups, it is unknown how CMV infection affects necroptosis and apoptosis in cardiac cells. Here, we infected primary cardiomyocytes, the contractile cells in the heart, and primary cardiac fibroblasts with wild-type and cell-death suppressor deficient mutant CMVs to determine how CMV regulates necroptosis and apoptosis in cardiac cells. Our results reveal that CMV infection prevents TNF-induced necroptosis in cardiomyocytes; however, the opposite phenotype is observed in cardiac fibroblasts. CMV infection also suppresses inflammation, reactive oxygen species (ROS) generation, and apoptosis in cardiomyocytes. Furthermore, CMV infection improves mitochondrial biogenesis and viability in cardiomyocytes. We conclude that CMV infection differentially affects the viability of cardiac cells.
3-sulfonyloxyaryl(mesityl)iodonium triflates as 1,2-benzdiyne precursors with activation via ortho-deprotonative elimination strategy
Authors: Yuan Haoyin , Yin Wenhao , Hu Jili , Li Yang
Published: April 2023

Benzyne has long captivated the attention of chemists and has gained numerous synthetic achievements. Among typical benzyne generation methods, removal of two vicinal substituents from 1,2-difunctionalized benzenes, i.e., Kobayashi’s protocol, are prevailing, while ortho-deprotonative elimination from mono-substituted benzene lags far behind. Despite the advantages of atom economy and ready achievability of precursors, a bottle neck for ortho-deprotonative elimination strategy resides in the weak acidity of the ortho-hydrogen, which normally demands strong bases as the activating reagents. Here, an efficient aryne generation protocol is developed, where ortho-deprotonative elimination on 3-sulfonyloxyaryl(mesityl)iodonium triflates occurs under mild conditions and the generated 3-sulfonyloxyarynes can serve as efficient 1,2-benzdiyne synthons. This array of 1,2-benzdiyne precursors can be conveniently prepared with high functional group tolerance, and densely substituted scaffolds can be accessed as well. Carbonate and fluoride salts are found to serve as efficient activating reagents, which are the weakest bases used in ortho-deprotonative elimination strategies. Particularly, this scaffold has predictable chemoselective generation of the designated aryne intermediates. The success of this ortho-deprotonative elimination protocol sets up a unique platform with a broad spectrum of synthetic applications.
Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging
Authors: Abu Sammour Denis , Cairns James L. , Boskamp Tobias , Marsching Christian , Kessler Tobias , Ramallo Guevara Carina , Panitz Verena , Sadik Ahmed , Cordes Jonas , Schmidt Stefan , Mohammed Shad A. , Rittel Miriam F. , Friedrich Mirco , Platten Michael , Wolf Ivo , von Deimling Andreas , Opitz Christiane A. , Wick Wolfgang , Hopf Carsten
Published: April 2023

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR (https://github.com/CeMOS-Mannheim/moleculaR) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.
Dynamical latent state computation in the male macaque posterior parietal cortex
Authors: Lakshminarasimhan Kaushik J. , Avila Eric , Pitkow Xaq , Angelaki Dora E.
Published: April 2023

Success in many real-world tasks depends on our ability to dynamically track hidden states of the world. We hypothesized that neural populations estimate these states by processing sensory history through recurrent interactions which reflect the internal model of the world. To test this, we recorded brain activity in posterior parietal cortex (PPC) of monkeys navigating by optic flow to a hidden target location within a virtual environment, without explicit position cues. In addition to sequential neural dynamics and strong interneuronal interactions, we found that the hidden state - monkey’s displacement from the goal - was encoded in single neurons, and could be dynamically decoded from population activity. The decoded estimates predicted navigation performance on individual trials. Task manipulations that perturbed the world model induced substantial changes in neural interactions, and modified the neural representation of the hidden state, while representations of sensory and motor variables remained stable. The findings were recapitulated by a task-optimized recurrent neural network model, suggesting that task demands shape the neural interactions in PPC, leading them to embody a world model that consolidates information and tracks task-relevant hidden states.
Transition-metal-free silylboronate-mediated cross-couplings of organic fluorides with amines
Authors: Zhou Jun , Zhao Zhengyu , Shibata Norio
Published: April 2023

C–N bond cross-couplings are fundamental in the field of organic chemistry. Herein, silylboronate-mediated selective defluorinative cross-coupling of organic fluorides with secondary amines via a transition-metal-free strategy is disclosed. The cooperation of silylboronate and potassium tert-butoxide enables the room-temperature cross-coupling of C–F and N–H bonds, effectively avoiding the high barriers associated with thermally induced SN2 or SN1 amination. The significant advantage of this transformation is the selective activation of the C–F bond of the organic fluoride by silylboronate without affecting potentially cleavable C–O, C–Cl, heteroaryl C–H, or C–N bonds and CF3 groups. Tertiary amines with aromatic, heteroaromatic, and/or aliphatic groups were efficiently synthesized in a single step using electronically and sterically varying organic fluorides and N-alkylanilines or secondary amines. The protocol is extended to the late-stage syntheses of drug candidates, including their deuterium-labeled analogs.
The Trypanosoma cruzi Antigen and Epitope Atlas: antibody specificities in Chagas disease patients across the Americas
Authors: Ricci Alejandro D. , Bracco Leonel , Salas-Sarduy Emir , Ramsey Janine M. , Nolan Melissa S. , Lynn M. Katie , Altcheh Jaime , Ballering Griselda E. , Torrico Faustino , Kesper Norival , Villar Juan C. , Marcipar Iván S. , Marco Jorge D. , Agüero Fernán
Published: April 2023

During an infection the immune system produces pathogen-specific antibodies. These antibody repertoires become specific to the history of infections and represent a rich source of diagnostic markers. However, the specificities of these antibodies are mostly unknown. Here, using high-density peptide arrays we examined the human antibody repertoires of Chagas disease patients. Chagas disease is a neglected disease caused by Trypanosoma cruzi, a protozoan parasite that evades immune mediated elimination and mounts long-lasting chronic infections. We describe a proteome-wide search for antigens, characterised their linear epitopes, and show their reactivity on 71 individuals from diverse human populations. Using single-residue mutagenesis we revealed the core functional residues for 232 of these epitopes. Finally, we show the diagnostic performance of identified antigens on challenging samples. These datasets enable the study of the Chagas antibody repertoire at an unprecedented depth and granularity, while also providing a rich source of serological biomarkers.
Interfacial assembly of binary atomic metal-Nx sites for high-performance energy devices
Authors: Jiang Zhe , Liu Xuerui , Liu Xiao-Zhi , Huang Shuang , Liu Ying , Yao Ze-Cheng , Zhang Yun , Zhang Qing-Hua , Gu Lin , Zheng Li-Rong , Li Li , Zhang Jianan , Fan Youjun , Tang Tang , Zhuang Zhongbin , Hu Jin-Song
Published: April 2023

Anion-exchange membrane fuel cells and Zn–air batteries based on non-Pt group metal catalysts typically suffer from sluggish cathodic oxygen reduction. Designing advanced catalyst architectures to improve the catalyst’s oxygen reduction activity and boosting the accessible site density by increasing metal loading and site utilization are potential ways to achieve high device performances. Herein, we report an interfacial assembly strategy to achieve binary single-atomic Fe/Co-Nx with high mass loadings through constructing a nanocage structure and concentrating high-density accessible binary single-atomic Fe/Co–Nx sites in a porous shell. The prepared FeCo-NCH features metal loading with a single-atomic distribution as high as 7.9 wt% and an accessible site density of around 7.6 × 1019 sites g−1, surpassing most reported M–Nx catalysts. In anion exchange membrane fuel cells and zinc–air batteries, the FeCo-NCH material delivers peak power densities of 569.0 or 414.5 mW cm−2, 3.4 or 2.8 times higher than control devices assembled with FeCo-NC. These results suggest that the present strategy for promoting catalytic site utilization offers new possibilities for exploring efficient low-cost electrocatalysts to boost the performance of various energy devices.
Current-driven writing process in antiferromagnetic Mn2Au for memory applications
Authors: Reimers S. , Lytvynenko Y. , Niu Y. R. , Golias E. , Sarpi B. , Veiga L. S. I. , Denneulin T. , Kovács A. , Dunin-Borkowski R. E. , Bläßer J. , Kläui M. , Jourdan M.
Published: April 2023

Current pulse driven Néel vector rotation in metallic antiferromagnets is one of the most promising concepts in antiferromagnetic spintronics. We show microscopically that the Néel vector of epitaxial thin films of the prototypical compound Mn2Au can be reoriented reversibly in the complete area of cross shaped device structures using single current pulses. The resulting domain pattern with aligned staggered magnetization is long term stable enabling memory applications. We achieve this switching with low heating of ≈20 K, which is promising regarding fast and efficient devices without the need for thermal activation. Current polarity dependent reversible domain wall motion demonstrates a Néel spin-orbit torque acting on the domain walls.
Ecological change of the gut microbiota during pregnancy and progression to dyslipidemia
Authors: Yang Xu , Zhang Mingzhi , Zhang Yuqing , Wei Hongcheng , Guan Quanquan , Dong Chao , Deng Siting , Tun Hein Min , Xia Yankai
Published: April 2023

The composition of the gut microbiome was previously found to be associated with clinical responses to dyslipidemia, but there is limited consensus on the dynamic change of the gut microbiota during pregnancy and the specific microbiome characteristics linked to dyslipidemia in pregnant women. We collected fecal samples from 513 pregnant women at multiple time points during pregnancy in a prospective cohort. Taxonomic composition and functional annotations were determined by 16S rRNA amplicon sequencing and shotgun metagenomic sequencing. The predictive potential of gut microbiota on the risk of dyslipidemia was determined. The gut microbiome underwent dynamic changes during pregnancy, with significantly lower alpha diversity observed in dyslipidemic patients compared to their healthy counterparts. Several genera, including Bacteroides, Paraprevotella, Alistipes, Christensenellaceae R7 group, Clostridia UCG-014, and UCG-002 were negatively associated with lipid profiles and dyslipidemia. Further metagenomic analysis recognized a common set of pathways involved in gastrointestinal inflammation, where disease-specific microbes played an important role. Machine learning analysis confirmed the link between the microbiome and its progression to dyslipidemia, with a micro-averaged AUC of 0.824 (95% CI: 0.782-0.855) combined with blood biochemical data. Overall, the human gut microbiome, including Alistipes and Bacteroides, was associated with the lipid profile and maternal dyslipidemia during pregnancy by perturbing inflammatory functional pathways. Gut microbiota combined with blood biochemical data at the mid-pregnancy stage could predict the risk of dyslipidemia in late pregnancy. Therefore, the gut microbiota may represent a potential noninvasive diagnostic and therapeutic strategy for preventing dyslipidemia in pregnancy.
Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing
Authors: Giam Amanda , Chen Fan , Cai Jiaxiang , Yan Wentao
Published: April 2023

A bottleneck in Laser Powder Bed Fusion (L-PBF) metal additive manufacturing (AM) is the quality inconsistency of its products. To address this issue without costly experimentation, computational multi-physics modeling has been used, but the effectiveness is limited by parameter uncertainties and their interactions. We propose a full factorial design and variable selection approach for the analytics of main and interaction effects arising from material parameter uncertainties in multi-physics models. Data is collected from high-fidelity thermal-fluid simulations based on a 2-level full factorial design for 5 selected material parameters. Crucial physical phenomena of the L-PBF process are analyzed to extract physics-based domain knowledge, which are used to establish a validation checkpoint for our study. Initial data visualization with half-normal probability plots, interaction plots and standard deviation plots, is used to assess if the checkpoint is being met. We then apply the combination of best subset selection and the LASSO method on multiple linear regression models for comprehensive variable selection. Analytics yield statistically and phyiscally validated findings with practical implications, emphasizing the importance of parameter interactions under uncertainty, and their relation to the underlying physics of L-PBF.
Synthesizing efficient circuits for Hamiltonian simulation
Authors: Mukhopadhyay Priyanka , Wiebe Nathan , Zhang Hong Tao
Published: April 2023

We provide an approach for compiling quantum simulation circuits that appear in Trotter, qDRIFT and multi-product formulas to Clifford and non-Clifford operations that can reduce the number of non-Clifford operations. The total number of gates, especially CNOT, reduce in many cases. We show that it is possible to implement an exponentiated sum of commuting Paulis with at most m (controlled)-rotation gates, where m is the number of distinct non-zero eigenvalues (ignoring sign). Thus we can collect mutually commuting Hamiltonian terms into groups satisfying one of several symmetries identified in this work. This allows an inexpensive simulation of the entire group of terms. We further show that the cost can in some cases be reduced by partially allocating Hamiltonian terms to several groups and provide a polynomial time classical algorithm that can greedily allocate the terms to appropriate groupings.
Recurrent Respiratory Papillomatosis (RRP)—Meta-analyses on the use of the HPV vaccine as adjuvant therapy
Authors: Goon Peter , Sauzet Odile , Schuermann Matthias , Oppel Felix , Shao SenYao , Scholtz Lars-Uwe , Sudhoff Holger , Goerner Martin
Published: April 2023

Recurrent Respiratory Papillomatosis(RRP) is a rare disease with severe morbidity. Treatment is surgical. Prevailing viewpoint is that prophylactic HPV vaccines do not have therapeutic benefit due to their modus operandi. Studies on HPV vaccination alongside surgery were meta-analysed to test effect on burden of disease. Databases were accessed Nov and Dec 2021 [PubMed, Cochrane, Embase and Web of Science]. Main outcome measured was: Mean paired differences in the number of surgeries or recurrences per month. Analyses was performed using: Random effect maximal likelihood estimation model using the Stata module Mataan(StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX:StataCorp LLC.) Our results found n = 38 patients, suitable for syntheses with one previous meta-analyses (4 published, 2 unpublished studies) n = 63, total of n = 101 patients. Analyses rendered an overall reduction of 0.123 recurrences or surgeries per month (95% confidence interval [0.064, 0.183]). Our meta-analyses concludes that HPV vaccine is a beneficial adjunct therapy alongside surgery
Coherent radio bursts from known M-dwarf planet-host YZ Ceti
Authors: Pineda J. Sebastian , Villadsen Jackie
Published: April 2023

Observing magnetic star–planet interactions (SPIs) offers promise for determining the magnetic fields of exoplanets. Models of sub-Alfvénic SPIs predict that terrestrial planets in close-in orbits around M dwarfs can induce detectable stellar radio emission, manifesting as bursts of strongly polarized coherent radiation observable at specific planet orbital positions. Here we present 2–4 GHz detections of coherent radio bursts on the slowly rotating M dwarf YZ Ceti, which hosts a compact system of terrestrial planets, the innermost of which orbits with a two-day period. Two coherent bursts occur at similar orbital phases of YZ Ceti b, suggestive of an enhanced probability of bursts near that orbital phase. We model the system’s magnetospheric environment in the context of sub-Alfvénic SPIs and determine that YZ Ceti b can plausibly power the observed flux densities of the radio detections. However, we cannot rule out stellar magnetic activity without a well-characterized rate of non-planet-induced coherent radio bursts on slow rotators. YZ Ceti is therefore a candidate radio SPI system, with unique promise as a target for long-term monitoring.
A social niche breadth score reveals niche range strategies of generalists and specialists
Authors: von Meijenfeldt F. A. Bastiaan , Hogeweg Paulien , Dutilh Bas E.
Published: April 2023

Generalists can survive in many environments, whereas specialists are restricted to a single environment. Although a classical concept in ecology, niche breadth has remained challenging to quantify for microorganisms because it depends on an objective definition of the environment. Here, by defining the environment of a microorganism as the community it resides in, we integrated information from over 22,000 environmental sequencing samples to derive a quantitative measure of the niche, which we call social niche breadth. At the level of genera, we explored niche range strategies throughout the prokaryotic tree of life. We found that social generalists include opportunists that stochastically dominate local communities, whereas social specialists are stable but low in abundance. Social generalists have a more diverse and open pan-genome than social specialists, but we found no global correlation between social niche breadth and genome size. Instead, we observed two distinct evolutionary strategies, whereby specialists have relatively small genomes in habitats with low local diversity, but relatively large genomes in habitats with high local diversity. Together, our analysis shines data-driven light on microbial niche range strategies.
Probe-based bacterial single-cell RNA sequencing predicts toxin regulation
Authors: McNulty Ryan , Sritharan Duluxan , Pahng Seong Ho , Meisch Jeffrey P. , Liu Shichen , Brennan Melanie A. , Saxer Gerda , Hormoz Sahand , Rosenthal Adam Z.
Published: April 2023

Clonal bacterial populations rely on transcriptional variation across individual cells to produce specialized states that increase fitness. Understanding all cell states requires studying isogenic bacterial populations at the single-cell level. Here we developed probe-based bacterial sequencing (ProBac-seq), a method that uses libraries of DNA probes and an existing commercial microfluidic platform to conduct bacterial single-cell RNA sequencing. We sequenced the transcriptome of thousands of individual bacterial cells per experiment, detecting several hundred transcripts per cell on average. Applied to Bacillus subtilis and Escherichia coli, ProBac-seq correctly identifies known cell states and uncovers previously unreported transcriptional heterogeneity. In the context of bacterial pathogenesis, application of the approach to Clostridium perfringens reveals heterogeneous expression of toxin by a subpopulation that can be controlled by acetate, a short-chain fatty acid highly prevalent in the gut. Overall, ProBac-seq can be used to uncover heterogeneity in isogenic microbial populations and identify perturbations that affect pathogenicity.
A new improved generalized class of estimators for population distribution function using auxiliary variable under simple random sampling
Authors: Ahmad Sohaib , Ullah Kalim , Zahid Erum , Shabbir Javid , Aamir Muhammad , Alshanbari Huda M. , El-Bagoury Abd Al-Aziz Hosni
Published: April 2023

This article aims to suggest a new improved generalized class of estimators for finite population distribution function of the study and the auxiliary variables as well as mean of the usual auxiliary variable under simple random sampling. The numerical expressions for the bias and mean squared error (MSE) are derived up to first degree of approximation. From our generalized class of estimators, we obtained two improved estimators. The gain in second proposed estimator is more as compared to first estimator. Three real data sets and a simulation are accompanied to measure the performances of our generalized class of estimators. The MSE of our proposed estimators is minimum and consequently percentage relative efficiency is higher as compared to their existing counterparts. From the numerical outcomes it has been shown that the proposed estimators perform well as compared to all considered estimators in this study.
Composition and function of the Galapagos penguin gut microbiome vary with age, location, and a putative bacterial pathogen
Authors: Rohrer Sage D. , Jiménez-Uzcátegui Gustavo , Parker Patricia G. , Chubiz Lon M.
Published: April 2023

Microbial colonization plays a direct role in host health. Understanding the ecology of the resident microbial community for a given host species is thus an important step for detecting population vulnerabilities like disease. However, the idea of integrating microbiome research into conservation is still relatively new, and wild birds have received less attention in this field than mammals or domesticated animals. Here we examine the composition and function of the gut microbiome of the endangered Galapagos penguin (Spheniscus mendiculus) with the goals of characterizing the normal microbial community and resistome, identifying likely pathogens, and testing hypotheses of structuring forces for this community based on demographics, location, and infection status. We collected fecal samples from wild penguins in 2018 and performed 16S rRNA gene sequencing and whole genome sequencing (WGS) on extracted DNA. 16S sequencing revealed that the bacterial phyla Fusobacteria, Epsilonbacteraeota, Firmicutes, and Proteobacteria dominate the community. Functional pathways were computed from WGS data, showing genetic functional potential primarily focused on metabolism—amino acid metabolism, carbohydrate metabolism, and energy metabolism are the most well-represented functional groups. WGS samples were each screened for antimicrobial resistance, characterizing a resistome made up of nine antibiotic resistance genes. Samples were screened for potential enteric pathogens using virulence factors as indicators;Clostridium perfringenswas revealed as a likely pathogen. Overall, three factors appear to be shaping the alpha and beta diversity of the microbial community: penguin developmental stage, sampling location, andC. perfringens. We found that juvenile penguins have significantly lower alpha diversity than adults based on three metrics, as well as significantly different beta diversity. Location effects are minimal, but one site has significantly lower Shannon diversity than the other primary sites. Finally, when samples were grouped byC. perfringensvirulence factors, we found dramatic changes in beta diversity based on operational taxonomic units, protein families, and functional pathways. This study provides a baseline microbiome for an endangered species, implicates both penguin age and the presence of a potential bacterial pathogen as primary factors associated with microbial community variance, and reveals widespread antibiotic resistance genes across the population.
Engineering-geological study of relationships between soil and rock workability, type and volume of excavated materials, and earthwork costs (six case studies)
Authors: Marschalko Marian , Popielarczyk Dariusz , Matuskova Simona , Niemiec Dominik , Neuman David , Glacova Veronika
Published: April 2023

The engineering-geological study deals with the study of significance and relationship of soil and rock workability (factor representing the engineering-geological structure of rock massif) and the remaining earthwork parameters influencing the cost of construction work, such as excavation type and its technology, and excavated cubic volume. The comparative tool was the cost of earthwork as it reflects the real value of the given parameters during the implementation of earthwork. Soil and rock workability is the most important parameter of rock massif engineering-geological structure during any earthwork. The investor pays the contractor for earthwork based on workability classes which have their accounting value expressed as a volume unit of earthwork per particular project. The research results arise from a comparison of 6 sewer system construction project case studies in the north-east of the Czech Republic. The research shows that the most important factor during the implementation of earthwork is the specific engineering-geological structure (52%), which reflects in the parameter of soil and rock workability classes, using which all earthwork is priced. The second most important factor (33%) is the type of excavation and its technology. The least important is the excavated cubic volume (15%), which means the overall cubic volume of earthwork. The results were obtained within three evaluation approaches, where the comparison unit was one cubic meter of excavated volume during earthwork.
Demonstration of laser cooling in a novel all oxide GAYY silica glass
Authors: Thomas Jyothis , Meyneng Thomas , Tehranchi Amirhossein , Gregoire Nicolas , Monet Frederic , Seletskiy Denis , Messaddeq Younès , Kashyap Raman
Published: April 2023

We demonstrate laser induced cooling in ytterbium doped silica (SiO2) glass with alumina, yttria co-doping (GAYY-Aluminum: Yttrium: Ytterbium Glass) fabricated using the modified chemical vapour deposition (MCVD) technique. A maximum temperature reduction by − 0.9 K from room temperature (296 K) at atmospheric pressure was achieved using only 6.5 W of 1029 nm laser radiation. The developed fabrication process allows us to incorporate ytterbium at concentration of 4 × 1026 ions/m3 which is the highest value reported for laser cooling without clustering or lifetime shortening, as well as to reach a very low background absorptive loss of 10 dB/km. The numerical simulation of temperature change versus pump power well agrees with the observation and predicts, for the same conditions, a temperature reduction of 4 K from room temperature in a vacuum. This novel silica glass has a high potential for a vast number of applications in laser cooling such as radiation-balanced amplifiers and high-power lasers including fiber lasers.
A novel Raman spectroscopic method for detecting traces of blood on an interfering substrate
Authors: Kistenev Yury V. , Borisov Alexei V. , Samarinova Alisa A. , Colón-Rodríguez Sonivette , Lednev Igor K.
Published: April 2023

Traces of body fluids discovered at a crime scene are a primary source of DNA evidence. Raman spectroscopy is a promising universal technique for identifying biological stains for forensic purposes. The advantages of this method include the ability to work with trace amounts, high chemical specificity, no need for sample preparation and the nondestructive nature. However, common substrate interference limits the practical application of this novel technology. To overcome this limitation, two approaches called "Reducing a spectrum complexity" (RSC) and "Multivariate curve resolution combined with the additions method" (MCRAD) were investigated for detecting bloodstains on several common substrates. In the latter approach, the experimental spectra were “titrated” numerically with a known spectrum of a targeted component. The advantages and disadvantages of both methods for practical forensics were evaluated. In addition, a hierarchical approach to reduce the possibility of false positives was suggested.
Descriptor engineering in machine learning regression of electronic structure properties for 2D materials
Authors: Dau Minh Tuan , Al Khalfioui Mohamed , Michon Adrien , Reserbat-Plantey Antoine , Vézian Stéphane , Boucaud Philippe
Published: April 2023

We build new material descriptors to predict the band gap and the work function of 2D materials by tree-based machine-learning models. The descriptor’s construction is based on vectorizing property matrices and on empirical property function, leading to mixing features that require low-resource computations. Combined with database-based features, the mixing features significantly improve the training and prediction of the models. We find R$$^{2}$$

2

greater than 0.9 and mean absolute errors (MAE) smaller than 0.23 eV both for the training and prediction. The highest R$$^{2}$$

2

of 0.95, 0.98 and the smallest MAE of 0.16 eV and 0.10 eV were obtained by using extreme gradient boosting for the bandgap and work-function predictions, respectively. These metrics were greatly improved as compared to those of database features-based predictions. We also find that the hybrid features slightly reduce the overfitting despite a small scale of the dataset. The relevance of the descriptor-based method was assessed by predicting and comparing the electronic properties of several 2D materials belonging to new classes (oxides, nitrides, carbides) with those of conventional computations. Our work provides a guideline to efficiently engineer descriptors by using vectorized property matrices and hybrid features for predicting 2D materials properties via ensemble models.
Valley-optical absorption in planar transition metal dichalcogenide superlattices
Authors: Hashemi R. , Shojaei S. , Rezaei B. , Liu Zheng
Published: April 2023

In this study, we investigate the optical absorption of a planar superlattice comprising alternatively arranged two-dimensional Transition Metal DiChalcogenide semiconductors. Within a semi-classical model and using the Dirac-like equation in the presence of light interaction as a perturbation, we obtained the governing Hamiltonian. Using this Hamiltonian, we derived a fully analytical relationship for the absorption coefficient of the structure. By calculating the effective mass for different bands and using the Drude-Lorentz model, our approach is able to determine the oscillator strength and the effective refractive index of the structure. We found that the spin–orbit coupling has important effect on the absorption coefficient and energy bands where it reduces the absorption coefficient of the structure from typical value of $$11.54 ({10}^{5}{\mathrm{cm}}^{-1})$$

11.54
(

10

5

cm

-
1

)

–$$5.937({10}^{5}{\mathrm{cm}}^{-1})$$

5.937
(

10

5

cm

-
1

)

, also the valence band experiences a significant blue shift, while the conduction band shows minor changes due to spin orbit coupling. Moreover, the role of incident light angle and light polarization were studied in details at different valleys of $$K$$
K
and $${K}^{^{\prime}}$$

K

′

. The most important finding is that by changing the polarization of incident light, it is possible to increase the absorption coefficients of $$K$$
K
and $${K}^{^{\prime}}$$

K

′

valleys by up to 30 times. For light propagation direction close to perpendicular to the plane of the superlattice, the right-circular polarization is absorbed only by $$K$$
K
valley in contrast to the left-circular polarization, which is absorbed by the $${K}^{^{\prime}}$$

K

′

valley. Our model might be used to design newly developed 2D optovalleytronic devices.
Autofocusing MALDI MS imaging of processed food exemplified by the contaminant acrylamide in German gingerbread
Authors: Wittek Oliver , Römpp Andreas
Published: April 2023

Acrylamide is a toxic reaction product occurring in dry-heated food such as bakery products. To meet the requirements laid down in recent international legal norms calling for reduction strategies in food prone to acrylamide formation, efficient chromatography-based quantification methods are available. However, for an efficient mitigation of acrylamide levels, not only the quantity, but also the contaminant’s distributions are of interest especially in inhomogeneous food consisting of multiple ingredients. A promising tool to investigate the spatial distribution of analytes in food matrices is mass spectrometry imaging (MS imaging). In this study, an autofocusing MALDI MS imaging method was developed for German gingerbread as an example for highly processed and instable food with uneven surfaces. Next to endogenous food constituents, the process contaminant acrylamide was identified and visualized keeping a constant laser focus throughout the measurement. Statistical analyses based on relative acrylamide intensities suggest a higher contamination of nut fragments compared to the dough. In a proof-of-concept experiment, a newly developed in-situ chemical derivatization protocol is described using thiosalicylic acid for highly selective detection of acrylamide. This study presents autofocusing MS imaging as a suitable complementary method for the investigation of analytes’ distributions in complex and highly processed food.
An integrative machine learning framework for classifying SEER breast cancer
Authors: Manikandan P. , Durga U. , Ponnuraja C.
Published: April 2023

Breast cancer is the commonest type of cancer in women worldwide and the leading cause of mortality for females. The aim of this research is to classify the alive and death status of breast cancer patients using the Surveillance, Epidemiology, and End Results dataset. Due to its capacity to handle enormous data sets systematically, machine learning and deep learning has been widely employed in biomedical research to answer diverse classification difficulties. Pre-processing the data enables its visualization and analysis for use in making important decisions. This research presents a feasible machine learning-based approach for categorizing SEER breast cancer dataset. Moreover, a two-step feature selection method based on Variance Threshold and Principal Component Analysis was employed to select the features from the SEER breast cancer dataset. After selecting the features, the classification of the breast cancer dataset is carried out using Supervised and Ensemble learning techniques such as Ada Boosting, XG Boosting, Gradient Boosting, Naive Bayes and Decision Tree. Utilizing the train-test split and k-fold cross-validation approaches, the performance of various machine learning algorithms is examined. The accuracy of Decision Tree for both train-test split and cross validation achieved as 98%. In this study, it is observed that the Decision Tree algorithm outperforms other supervised and ensemble learning approaches for the SEER Breast Cancer dataset.
Investigation of time profile of FEV1 across the onset of potential COPD: a retrospective cohort study using medical checkup data in Japan
Authors: Suzuki Masaru , Matsumoto Isao , Ishida Masato , Horie Yoshiharu , Ban Hideyuki , Takeuchi Wataru , Nakagawa Shunki , Nakagawa Tohru , Kitamura Tetsuhisa , Muro Shigeo
Published: April 2023

This study compared the time profile of FEV1 after COPD diagnosis among rapid decliners, slow decliners, and sustainers in the year of COPD diagnosis. COPD subjects were identified from the annual medical checkup records of Hitachi, Ltd., employees in Japan (April 1998-March 2019). Subjects were categorized into 3 groups (rapid decliner [decrease of FEV1 ≥ 63 mL/year], slow decliner [< 63 and ≥ 31 mL/year], and sustainer [< 31 mL/year]) for 5 years. The time profile of FEV1 was compared using mixed-effects model for 5 years after diagnosis; risk factors of rapid decliner were detected using logistic model/gradient boosting decision tree. Of 1294 eligible subjects, 18.6%, 25.7%, and 55.7% were classified as rapid decliners, slow decliners, and sustainers, respectively. The annual rates of FEV1 decline were similar 3 years before and until COPD diagnosis. The mean FEV1 in rapid decliners was 2.82 ± 0.04 L in year 0 and 2.41 ± 0.05 L in year 5, and in sustainers, it was 2.67 ± 0.02 L and 2.72 ± 0.02 L (year 0, p = 0.0004). In conclusion, FEV1 declined yearly before diagnosis and the time profiles of FEV1 were different in the 3 groups after COPD diagnosis. Therefore, appropriate treatment of the 3 groups with regular lung function tests is necessary to follow FEV1 decline after COPD onset.
A dynamically coherent pattern of rhythms that matches between distant species across the evolutionary scale
Authors: Kembro J. M. , Flesia A. G. , Nieto P. S. , Caliva J. M. , Lloyd D. , Cortassa S. , Aon M. A.
Published: April 2023

We address the temporal organization of circadian and ultradian rhythms, crucial for understanding biological timekeeping in behavior, physiology, metabolism, and alignment with geophysical time. Using a newly developed five-steps wavelet-based approach to analyze high-resolution time series of metabolism in yeast cultures and spontaneous movement, metabolism, and feeding behavior in mice, rats, and quails, we describe a dynamically coherent pattern of rhythms spanning over a broad range of temporal scales (hours to minutes). The dynamic pattern found shares key features among the four, evolutionary distant, species analyzed. Specifically, a branching appearance given by splitting periods from 24 h into 12 h, 8 h and below in mammalian and avian species, or from 14 h down to 0.07 h in yeast. Scale-free fluctuations with long-range correlations prevail below ~ 4 h. Synthetic time series modeling support a scenario of coexisting behavioral rhythms, with circadian and ultradian rhythms at the center of the emergent pattern observed.
Analysis of fatality impact and seroprevalence surveys in a community sustaining a SARS-CoV-2 superspreading event
Authors: Richter Enrico , Liebl Dominik , Schulte Bianca , Lehmann Nils , Fuhrmann Christine , Jöckel Karl-Heinz , Ioannidis John P. A. , Streeck Hendrik
Published: April 2023

There is an ongoing debate on the COVID-19 infection fatality rate (IFR) and the impact of COVID-19 on overall population mortality. Here, we addressed these issues in a community in Germany with a major superspreader event analyzing deaths over time and auditing death certificates in the community.18 deaths that occurred within the first six months of the pandemic had a positive test for SARS-CoV-2. Six out of 18 deaths had non-COVID-19 related causes of death (COD). Individuals with COVID-19 COD typically died of respiratory failure (75%) and tended to have fewer reported comorbidities (p = 0.029). Duration between first confirmed infection and death was negatively associated with COVID-19 being COD (p = 0.04). Repeated seroprevalence essays in a cross-sectional epidemiological study showed modest increases in seroprevalence over time, and substantial seroreversion (30%). IFR estimates accordingly varied depending on COVID-19 death attribution. Careful ascertainment of COVID-19 deaths is important in understanding the impact of the pandemic.
Recellularized lymph node scaffolds with human adipose-derived stem cells enhance lymph node regeneration to improve lymphedema
Authors: Kang Hyo Jin , Moon Soo Young , Kim Baek-Kyu , Myung Yujin , Lee Ju-Hee , Jeong Jae Hoon
Published: April 2023

To overcome the limitations of lymphedema treatment, human adipose-derived stem cells (hADSCs) were injected into decellularized lymph nodes to produce a recellularized lymph node-scaffold, and the effect of lymphangiogenesis was investigated in lymphedema animal models. Axillary lymph nodes were harvested from Sprague Dawley rats (7 weeks old, 220–250 g) for decellularization. The decellularized lymph nodes were performed and PKH26-labeled hADSCs (1 × 106/50 µL) were injected in the decellularized lymph node-scaffolds. Forty rats were equally divided into four groups: lymphedema as control group, hADSC group, decellularized lymph node-scaffold group, and recellularized lymph node-scaffold group. The lymphedema model was made by removing inguinal lymph nodes, and hADSCs or scaffolds were transplanted. Histopathological assessments were performed by hematoxylin and eosin and Masson’s trichrome staining. Lymphangiogenesis was evaluated by Immunofluorescence staining and western blot. Decellularized lymph nodes showed virtually complete absence of cellular material and maintenance of lymph node architecture. The hADSCs were significantly observed in recellularized lymph node-scaffolds group. The recellularized lymph node-scaffold group was histologically similar to normal lymph nodes. The vascular endothelial growth factor A and lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) in immunofluorescence staining were highly expressed in recellularized lymph node-scaffolds group. Also, the expression of LYVE-1 protein significantly increased in recellularized lymph node-scaffold group compared with others. Recellularized lymph node -scaffold had a much better therapeutic effect than stem cells or decellularized lymph node-scaffold alone, and induced stable lymphangiogenesis.
Impact of frailty on long-term mortality in older patients receiving intensive care via the emergency department
Authors: Inaba Mototaka , Naito Hiromichi , Yorifuji Takashi , Nakamichi Chikaaki , Maeyama Hiroki , Ishikawa Hideki , Shime Nobuaki , Uemori Sadayori , Ishihara Satoshi , Takaoka Makoto , Ohtsuka Tsuyoshi , Harada Masahiro , Nozaki Satoshi , Kohama Keisuke , Sakurai Ryota , Sato Shuho , Muramatsu Shun , Yamashita Kazunori , Mayumi Toshihiko , Aita Kaoruko , Nakao Atsunori ,   the LIFE Study Investigators, Mochizuki Satoshi , Itoh Hirofumi , Senda Asase , Otani Kana , Gon Chison , Taito Shunsuke , Ohnishi Takeshi , Taguchi Yuji , Miike Toru , Umeda Koki , Kondo Yuji , Arai Takao , Tsurukiri Junya , Masuda Kaoru
Published: April 2023

The aim of this study was to evaluate whether frailty was associated with 6-month mortality in older adults who were admitted to the intensive care unit (ICU) with an illness requiring emergency care. The investigation was a prospective, multi-center, observational study conducted among the ICUs of 17 participating hospitals. Patients ≥ 65 years of age who were admitted to the ICU directly from an emergency department visit were assessed to determine their baseline Clinical Frailty Scale (CFS) scores before the illness and were surveyed 6 months after admission. Among 650 patients included in the study, the median age was 79 years old, and overall mortality at 6 months was as low as 21%, ranging from 6.2% in patients with CFS 1 to 42.9% in patients with CFS ≥ 7. When adjusted for potential confounders, CFS score was an independent prognostic factor for mortality (one-point increase in CFS, adjusted risk ratio with 95% confidence interval 1.19 [1.09–1.30]). Quality of life 6 months after admission worsened as baseline CFS score increased. However, there was no association between total hospitalization cost and baseline CFS. CFS is an important predictor of long-term outcomes among critically ill older patients requiring emergent admission.