bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling of charged-particle multiplicity and transverse-momentum distributions in pp collisions using a DNN
Authors: Shokr E. , De Roeck A. , Mahmoud M. A.
Published: May 2022

A machine learning technique is used to fit multiplicity distributions in high energy proton-proton collisions and applied to make predictions for collisions at higher energies. The method is tested with Monte Carlo event generators. Charged-particle multiplicity and transverse-momentum distributions within different pseudorapidity intervals in proton-proton collisions were simulated using the PYTHIA event generator for center of mass energies $$\sqrt{s}$$

s

= 0.9, 2.36, 2.76, 5, 7, 8, 13 TeV for model training and validation and at 10, 20, 27, 50, 100 and 150 TeV for model predictions. Comparisons are made in order to ensure the model reproduces the relation between input variables and output distributions for the charged particle multiplicity and transverse-momentum. The multiplicity and transverse-momentum distributions are described and predicted very well, not only in the case of the trained but also in the case of untrained energy values. The study proposes a way to predict multiplicity distributions at a new energy by extrapolating the information inherent in the lower energy data. Using real data instead of Monte Carlo, as measured at the LHC, the technique has the potential to project the multiplicity distributions for different intervals at very high collision energies, e.g. 27 TeV or 100 TeV for the upgraded HE-LHC and FCC-hh respectively, using only data collected at the LHC, i.e. at center of mass energies from 0.9 up to 13 TeV.
The hospital environment versus carriage: transmission pathways for third-generation cephalosporin-resistant bacteria in blood in neonates in a low-resource country healthcare setting
Authors: Kovacs Dory , Silago Vitus , Msanga Delfina R. , Mshana Stephen E. , Seni Jeremiah , Oravcova Katarina , Matthews Louise
Published: May 2022

Neonatal bloodstream infections (BSI) can lead to sepsis, with high morbidity and mortality, particularly in low-income settings. The high prevalence of third-generation cephalosporin-resistant organisms (3GC-RO) complicates the management of BSI. Whether BSI is linked to carriage of 3GC-RO, or to acquisition from the hospital environment is important for infection prevention and control, but the relationship remains unclear, especially in low-income settings. At a tertiary hospital in Mwanza, Tanzania, we screened neonatal blood and rectal samples from 200 neonates, and 400 (hospital) environmental samples. We used logistic regression to identify risk factors, and Kolmogorov–Smirnov tests and randomisation analyses to compare distributions of species and resistance patterns to assess potential routes of transmission. We found that BSIs caused by 3GC-RO were frequent (of 59 cases of BSI, 55 were caused by 3GC-RO), as was carriage of 3GC-RO, particularly Escherichia coli, Klebsiella pneumoniae, and Acinetobacter species. In the 28 infants with both a carriage and blood isolate, there were more (4 of 28) isolate pairs of the same species and susceptibility profile than expected by chance (p < 0.05), but most pairs were discordant (24 of 28). Logistic regression models found no association between BSI and carriage with either 3GC-RO or only 3GC-R K. pneumoniae. These analyses suggest that carriage of 3GC-RO is not a major driver of BSI caused by 3GC-RO in this setting. Comparison with environmental isolates showed very similar distributions of species and resistance patterns in the carriage, BSI, and the environment. These similar distributions, a high frequency of Acinetobacter spp. isolations, the lack of strong association between carriage and BSI, together with the high proportion of 3GC-RO in BSI all suggest that these neonates acquire multidrug-resistant carriage and blood isolates directly from the hospital environment.
Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC–MS/MS technique
Authors: Hosseinkhani Shaghayegh , Arjmand Babak , Dilmaghani-Marand Arezou , Mohammadi Fateh Sahar , Dehghanbanadaki Hojat , Najjar Niloufar , Alavi-Moghadam Sepideh , Ghodssi-Ghassemabadi Robabeh , Nasli-Esfahani Ensieh , Farzadfar Farshad , Larijani Bagher , Razi Farideh
Published: May 2022

Diabetes is a common chronic disease affecting millions of people worldwide. It underlies various complications and imposes many costs on individuals and society. Discovering early diagnostic biomarkers takes excellent insight into preventive plans and the best use of interventions. Therefore, in the present study, we aimed to evaluate the association between the level of amino acids and acylcarnitines and diabetes to develop diabetes predictive models. Using the targeted LC–MS/MS technique, we analyzed fasting plasma samples of 206 cases and 206 controls that were matched by age, sex, and BMI. The association between metabolites and diabetes was evaluated using univariate and multivariate regression analysis with adjustment for systolic and diastolic blood pressure and lipid profile. To deal with multiple comparisons, factor analysis was used. Participants' average age and BMI were 61.6 years, 28.9 kg/m2, and 55% were female. After adjustment, Factor 3 (tyrosine, valine, leucine, methionine, tryptophan, phenylalanine), 5 (C3DC, C5, C5OH, C5:1), 6 (C14OH, C16OH, C18OH, C18:1OH), 8 (C2, C4OH, C8:1), 10 (alanine, proline) and 11 (glutamic acid, C18:2OH) were positively associated with diabetes. Inline, factor 9 (C4DC, serine, glycine, threonine) and 12 (citrulline, ornithine) showed a reverse trend. Some amino acids and acylcarnitines were found as potential risk markers for diabetes incidents that reflected the disturbances in the several metabolic pathways among the diabetic population and could be targeted to prevent, diagnose, and treat diabetes.
Microfluidic-assisted synthesis and modeling of stimuli-responsive monodispersed chitosan microgels for drug delivery applications
Authors: Sartipzadeh Omid , Naghib Seyed Morteza , Haghiralsadat Fatemeh , Shokati Farhad , Rahmanian Mehdi
Published: May 2022

Droplet microfluidic has been established to synthesize and functionalize micro/nanoparticles for drug delivery and screening, biosensing, cell/tissue engineering, lab-on-a-chip, and organ-on-a-chip have attracted much attention in chemical and biomedical engineering. Chitosan (CS) has been suggested for different biomedical applications due to its unique characteristics, such as antibacterial bioactivities, immune-enhancing influences, and anticancer bioactivities. The simulation results exhibited an alternative for attaining visions in this complex method. In this regard, the role of the flow rate ratio on the CS droplet features, including the generation rate and droplet size, were thoroughly described. Based on the results, an appropriate protocol was advanced for controlling the CS droplet properties for comparing their properties, such as the rate and size of the CS droplets in the microchip. Also, a level set (LS) laminar two-phase flow system was utilized to study the CS droplet-breaking process in the Flow Focused-based microchip. The outcomes demonstrated that different sizes and geometries of CS droplets could be established via varying the several parameters that validated addressing the different challenges for several purposes like drug delivery (the droplets with smaller sizes), tissue engineering, and cell encapsulation (the droplets with larger sizes), lab-on-a-chip, organ-on-a-chip, biosensing and bioimaging (the droplets with different sizes). An experimental study was added to confirm the simulation results. A drug delivery application was established to verify the claim.
Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery
Authors: Ruiz Puentes Paola , Rueda-Gensini Laura , Valderrama Natalia , Hernández Isabela , González Cristina , Daza Laura , Muñoz-Camargo Carolina , Cruz Juan C. , Arbeláez Pablo
Published: May 2022

Drug Discovery is an active research area that demands great investments and generates low returns due to its inherent complexity and great costs. To identify potential therapeutic candidates more effectively, we propose protein–ligand with adversarial augmentations network (PLA-Net), a deep learning-based approach to predict target–ligand interactions. PLA-Net consists of a two-module deep graph convolutional network that considers ligands’ and targets’ most relevant chemical information, successfully combining them to find their binding capability. Moreover, we generate adversarial data augmentations that preserve relevant biological backgrounds and improve the interpretability of our model, highlighting the relevant substructures of the ligands reported to interact with the protein targets. Our experiments demonstrate that the joint ligand–target information and the adversarial augmentations significantly increase the interaction prediction performance. PLA-Net achieves 86.52% in mean average precision for 102 target proteins with perfect performance for 30 of them, in a curated version of actives as decoys dataset. Lastly, we accurately predict pharmacologically-relevant molecules when screening the ligands of ChEMBL and drug repurposing Hub datasets with the perfect-scoring targets.
Integrated strategic planning and multi-criteria decision-making framework with its application to agricultural water management
Authors: Radmehr Ahmad , Bozorg-Haddad Omid , Loáiciga Hugo A.
Published: May 2022

Sustainable water resources management involves social, economic, environmental, water use, and resources factors. This study proposes a new framework of strategic planning with multi-criteria decision-making to develop sustainable water management alternatives for large scale water resources systems. A fuzzy multi-criteria decision-making model is developed to rank regional management alternatives for agricultural water management considering water-resources sustainability criteria. The decision-making model combines hierarchical analysis and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The management alternatives were presented spatially in the form of zoning maps at the level of irrigation zones of the study area. The results show that the irrigation management zone No.3 (alternative A3) was ranked first based on agricultural water demand and supply management in five among seven available scenarios, in which the scenarios represents a possible combination of weights assigned to the weighing criteria. Specifically, the results show that irrigation management zone No.3 (alternative A3) achieved the best ranking values of 0.151, 0.169, 0.152, 0.174 and 0.164 with respect to scenarios 1, 4, 5, 6 and 7, respectively. However, irrigation management zone No.2 (alternative A2) achieved the best values of 0.152 and 0.150 with respect to the second and third scenarios, respectively. The model results identify the best management alternatives for agricultural water management in large-scale irrigation and drainage networks.
On the measurement of skeletal muscle anisotropic permittivity property with a single cross-shaped needle insertion
Authors: Kwon Hyeuknam , Park Hyoung Churl , Barrera Albert Cheto , Rutkove Seward B. , Sanchez Benjamin
Published: May 2022

Application of minimally invasive methods to enable the measurement of tissue permittivity in the neuromuscular clinic remain elusive. This paper provides a theoretical and modeling study on the measurement of the permittivity of two-dimensional anisotropic tissues such as skeletal muscle with a multi-electrode cross-shaped needle. For this, we design a novel cross-shaped needle with multiple-electrodes and analyse apparent impedance corresponding to the measured impedance. In addition, we propose three methods of estimate anisotropic muscle permittivity. Compared to existing electrical impedance-based needle methods that we have developed, the new needle design and numerical methods associated enable estimating in vivo muscle permittivity values with only a single needle insertion. Being able to measure muscle permittivity directly with a single needle insertion could open up an entirely new area of research with direct clinical application, including using these values to assist in neuromuscular diagnosis and to assess subtle effects of therapeutic intervention on muscle health.
Peptidomic changes in the milk of water buffaloes (Bubalus bubalis) with intramammary infection by non-aureus staphylococci
Authors: Addis Maria Filippa , Maffioli Elisa Margherita , Penati Martina , Albertini Mariangela , Bronzo Valerio , Piccinini Renata , Tangorra Francesco , Tedeschi Gabriella , Cappelli Giovanna , Di Vuolo Gabriele , Vecchio Domenico , De Carlo Esterina , Ceciliani Fabrizio
Published: May 2022

Mastitis by non-aureus staphylococci (NAS) is a significant issue in dairy buffalo farming. In a herd with subclinical NAS mastitis, we identified Staphylococcus microti as the predominant species. To assess milk protein integrity and investigate potential disease markers, we characterized 12 NAS-positive and 12 healthy quarter milk samples by shotgun peptidomics combining peptide enrichment and high-performance liquid chromatography/tandem mass spectrometry (LC–MS/MS). We observed significant changes in the milk peptidome. Out of 789 total peptides identified in each group, 49 and 44 were unique or increased in NAS-positive and healthy milk, respectively. In NAS-positive milk, the differential peptides belonged mainly to caseins, followed by milk fat globule membrane proteins (MFGMP) and by the immune defense/antimicrobial proteins osteopontin, lactoperoxidase, and serum amyloid A. In healthy milk, these belonged mainly to MFGMP, followed by caseins. In terms of abundance, peptides from MFGMP and immune defense protein were higher in NAS-positive milk, while peptides from caseins were higher in healthy milk. These findings highlight the impact of NAS on buffalo milk quality and mammary gland health, even when clinical signs are not evident, and underscore the need for clarifying the epidemiology and relevance of the different NAS species in this dairy ruminant.
Machine learning to predict end stage kidney disease in chronic kidney disease
Authors: Bai Qiong , Su Chunyan , Tang Wen , Li Yike
Published: May 2022

The purpose of this study was to assess the feasibility of machine learning (ML) in predicting the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease (CKD). Data were obtained from a longitudinal CKD cohort. Predictor variables included patients’ baseline characteristics and routine blood test results. The outcome of interest was the presence or absence of ESKD by the end of 5 years. Missing data were imputed using multiple imputation. Five ML algorithms, including logistic regression, naïve Bayes, random forest, decision tree, and K-nearest neighbors were trained and tested using fivefold cross-validation. The performance of each model was compared to that of the Kidney Failure Risk Equation (KFRE). The dataset contained 748 CKD patients recruited between April 2006 and March 2008, with the follow-up time of 6.3 ± 2.3 years. ESKD was observed in 70 patients (9.4%). Three ML models, including the logistic regression, naïve Bayes and random forest, showed equivalent predictability and greater sensitivity compared to the KFRE. The KFRE had the highest accuracy, specificity, and precision. This study showed the feasibility of ML in evaluating the prognosis of CKD based on easily accessible features. Three ML models with adequate performance and sensitivity scores suggest a potential use for patient screenings. Future studies include external validation and improving the models with additional predictor variables.
Whole genome resequencing and complementation tests reveal candidate loci contributing to bacterial wilt (Ralstonia sp.) resistance in tomato
Authors: Barchenger Derek W. , Hsu Yu-ming , Ou Jheng-yang , Lin Ya-ping , Lin Yao-cheng , Balendres Mark Angelo O. , Hsu Yun-che , Schafleitner Roland , Hanson Peter
Published: May 2022

Tomato (Solanum lycopersicum) is one of the most economically important vegetable crops worldwide. Bacterial wilt (BW), caused by the Ralstonia solanacearum species complex, has been reported as the second most important plant pathogenic bacteria worldwide, and likely the most destructive. Extensive research has identified two major loci, Bwr-6 and Bwr-12, that contribute to resistance to BW in tomato; however, these loci do not completely explain resistance. Segregation of resistance in two populations that were homozygous dominant or heterozygous for all Bwr-6 and Bwr-12 associated molecular markers suggested the action of one or two resistance loci in addition to these two major QTLs. We utilized whole genome sequence data analysis and pairwise comparison of six BW resistant and nine BW susceptible tomato lines to identify candidate genes that, in addition to Bwr-6 and Bwr-12, contributed to resistance. Through this approach we found 27,046 SNPs and 5975 indels specific to the six resistant lines, affecting 385 genes. One sequence variant on chromosome 3 captured by marker Bwr3.2dCAPS located in the Asc (Solyc03g114600.4.1) gene had significant association with resistance, but it did not completely explain the resistance phenotype. The SNP associated with Bwr3.2dCAPS was located within the resistance gene Asc which was inside the previously identified Bwr-3 locus. This study provides a foundation for further investigations into new loci distributed throughout the tomato genome that could contribute to BW resistance and into the role of resistance genes that may act against multiple pathogens.
Integrated analysis of an in vivo model of intra-nasal exposure to instilled air pollutants reveals cell-type specific responses in the placenta
Authors: Tosevska Anela , Ghosh Shubhamoy , Ganguly Amit , Cappelletti Monica , Kallapur Suhas G. , Pellegrini Matteo , Devaskar Sherin U.
Published: May 2022

The placenta is a heterogeneous organ whose development involves complex interactions of trophoblasts with decidual, vascular, and immune cells at the fetal–maternal interface. It maintains a critical balance between maternal and fetal homeostasis. Placental dysfunction can lead to adverse pregnancy outcomes including intra-uterine growth restriction, pre-eclampsia, or pre-term birth. Exposure to environmental pollutants contributes to the development of placental abnormalities, with poorly understood molecular underpinning. Here we used a mouse (C57BL/6) model of environmental pollutant exposure by administration of a particulate matter (SRM1649b at 300 μg/day/mouse) suspension intra-nasally beginning 2 months before conception and during gestation, in comparison to saline-exposed controls. Placental transcriptomes, at day 19 of gestation, were determined using bulk RNA-seq from whole placentas of exposed (n = 4) and control (n = 4) animals and scRNAseq of three distinct placental layers, followed by flow cytometry analysis of the placental immune cell landscape. Our results indicate a reduction in vascular placental cells, especially cells responsible for structural integrity, and increase in trophoblast proliferation in animals exposed to particulate matter. Pollution-induced inflammation was also evident, especially in the decidual layer. These data indicate that environmental exposure to air pollutants triggers changes in the placental cellular composition, mediating adverse pregnancy outcomes.
Reduced body length and morphological disorders in Chrysomya albiceps (Diptera: Calliphoridae) larvae reared on aluminum phosphide-treated rabbits
Authors: El-Ashram Saeed , Toto Noura A. , El Wakil Abeer , Augustyniak Maria , El-Samad Lamia M.
Published: May 2022

Assessing the time of death based on the growth and development of insects is a critical task in forensic entomology. The rate of larvae development can be affected by a variety of toxins, including pesticides. Aluminum phosphide (AlP) is a low-cost insecticide that has yet to be tested for entomotoxicological significance, despite the fact that it is frequently the cause of fatal poisoning. In this study, we measured the body length of Chrysomya albiceps larvae reared on the carcasses of rabbits poisoned with AlP and analyzed the morphological changes of the larvae reared on the carcasses of rabbits poisoned with AlP. The concentration of AlP in the body of the larvae was significantly lower than in rabbit tissues. Insects from the AlP group had a significantly lower gain in body length. Furthermore, deformities in the larvae were found. Smaller respiratory spiracles were found, as well as a deformed small posterior end with hypogenesis of the posterior respiratory spiracles. Thus, disturbed growth and development of carrion flies found at a crime scene could indicate pesticide poisoning, such as aluminum phosphide.
The impact of short-term confinement on human innate immunity
Authors: Ponomarev S. A. , Sadova A. A. , Rykova M. P. , Orlova K. D. , Vlasova D. D. , Shulgina S. M. , Antropova E. N. , Kutko O. V. , Germanov N. S. , Galina V. S. , Shmarov V. A.
Published: May 2022

During space missions cosmonauts are exposed to a myriad of distinct stressors such as radiation, overloads, weightlessness, radiation, isolation in artificial environmental conditions, which causes changes in immune system. During space flights it is very difficult to determine the particular factor associated with the observed immunological responses. This makes ground-based experiments examining the effect of each space flight associated factor along of particular value. Determining mechanisms causing alterations in cosmonauts’ immunity can lead to potential targets for different countermeasures. In the current article we present the study of the early period of adaptation of human innate immunity of 6 healthy test-subjects, 4 males and 2 females aged 25 through 40, to isolation factors (hypodynamia, psychological stress, artificial environment). We measured multiple parameters characterizing innate immunity status in blood samples at chosen time points before, during and after the mission. In the experiment, highly enhanced cytokine responses were observed upon ex vivo antigen stimulations in comparison to baseline values. For cellular parameters we found multidirectional dynamics with a persistent prevalence of increasing TLRs+ monocytes as well as TLRs expression. Our study provides evidence that even a short-term confinement leads to immune changes in healthy humans that may trigger aberrant immune response.
Genome-wide association of polygenic risk extremes for Alzheimer's disease in the UK Biobank
Authors: Gouveia Catarina , Gibbons Elizabeth , Dehghani Nadia , Eapen James , Guerreiro Rita , Bras Jose
Published: May 2022

In just over a decade, advances in genome-wide association studies (GWAS) have offered an approach to stratify individuals based on genetic risk for disease. Using recent Alzheimer's disease (AD) GWAS results as the base data, we determined each individual's polygenic risk score (PRS) in the UK Biobank dataset. Using individuals within the extreme risk distribution, we performed a GWAS that is agnostic of AD phenotype and is instead based on known genetic risk for disease. To interpret the functions of the new risk factors, we conducted phenotype analyses, including a phenome-wide association study. We identified 246 loci surpassing the significance threshold of which 229 were not reported in the base AD GWAS. These include loci that showed suggestive levels of association in the base GWAS and loci not previously suspected to be associated with AD. Among these, there are loci, such asIL34andKANSL1, that have since been shown to be associated with AD in recent studies. We also show highly significant genetic correlations with multiple health-related outcomes that provide insights into prodromal symptoms and comorbidities. This is the first study to utilize PRS as a phenotype-agnostic group classification in AD genetic studies. We identify potential new loci for AD and detail phenotypic analysis of these PRS extremes.
Optimal strategies and cost-benefit analysis of the $${\varvec{n}}$$-player weightlifting game
Authors: Cuaresma Diane Carmeliza N. , Chiba Erika , Tubay Jerrold M. , Rabajante Jomar F. , Gavina Maica Krizna A. , Yoshimura Jin , Ito Hiromu , Okabe Takuya , Morita Satoru
Published: May 2022

The study of cooperation has been extensively studied in game theory. Especially, two-player two-strategy games have been categorized according to their equilibrium strategies and fully analysed. Recently, a grand unified game covering all types of two-player two-strategy games, i.e., the weightlifting game, was proposed. In the present study, we extend this two-player weightlifting game into an $$n$$
n
-player game. We investigate the conditions for pure strategy Nash equilibria and for Pareto optimal strategies, expressed in terms of the success probability and benefit-to-cost ratio of the weightlifting game. We also present a general characterization of $$n$$
n
-player games in terms of the proposed game. In terms of a concrete example, we present diagrams showing how the game category varies depending on the benefit-to-cost ratio. As a general rule, cooperation becomes difficult to achieve as group size increases because the success probability of weightlifting saturates towards unity. The present study provides insights into achieving behavioural cooperation in a large group by means of a cost–benefit analysis.
Long-term outcomes of cataract surgery with toric intraocular lens implantation by the type of preoperative astigmatism
Authors: Oshika Tetsuro , Nakano Shinichiro , Fujita Yoshifumi , Nomura Yuya , Inoue Yasushi , Takehara Hiroyasu , Miyata Kazunori , Honbou Masato , Sugita Toru , Kaneko Tsutomu
Published: May 2022

Surgical outcomes of toric intraocular lens (IOL) implantation for 8 years after surgery were analyzed. Data were retrospectively collected in 176 eyes of 176 patients before and 1 month, 1, 3, 5, and 8 years after phacoemulsification and implantation of a toric IOL. Preoperative corneal and postoperative manifest astigmatism was analyzed by converting to power vector notations; horizontal/vertical (J0) and oblique (J45) astigmatism components. Toric IOL implantation significantly reduced pre-existing astigmatism by decreasing J0 in eyes with preoperative with-the-rule (WTR) astigmatism, increasing J0 in eyes with against-the-rule (ATR) astigmatism, and correcting J45 in eyes with oblique astigmatism. After surgery, the eyes with preoperative ATR astigmatism showed a significant ATR astigmatic shift, and J0 at 5 and 8 years was significantly smaller than that at 1 month postoperatively. Uncorrected distance visual acuity was also significantly worse at 5 and 8 years than at 1 month postoperatively. In eyes with WTR and oblique astigmatism, the effects of toric IOLs on astigmatism and visual acuity were sustained for 8 years. The long-term astigmatism-correcting effects did not differ among the models of toric IOL used in this study, SN6AT3–8 (Alcon Laboratories). In eyes with preoperative ATR astigmatism, astigmatism-correcting effects of toric IOLs decreased at 5 years and later postoperatively, indicating that overcorrection may be considered at the time of cataract surgery. In eyes with WTR and oblique astigmatism, the effects of toric IOLs were maintained throughout the 8-year follow-up period.
Reliability and generalization of gait biometrics using 3D inertial sensor data and 3D optical system trajectories
Authors: Santos Geise , Tavares Tiago , Rocha Anderson
Published: May 2022

Particularities in the individuals’ style of walking have been explored for at least three decades as a biometric trait, empowering the automatic gait recognition field. Whereas gait recognition works usually focus on improving end-to-end performance measures, this work aims at understanding which individuals’ traces are more relevant to improve subjects’ separability. For such, a manifold projection technique and a multi-sensor gait dataset were adopted to investigate the impact of each data source characteristics on this separability. Assessments have shown it is hard to distinguish individuals based only on their walking patterns in a subject-based identification scenario. In this setup, the subjects’ separability is more related to their physical characteristics than their movements related to gait cycles and biomechanical events. However, this study’s results also points to the feasibility of learning identity characteristics from individuals’ walking patterns learned from similarities and differences between subjects in a verification setup. The explorations concluded that periodic components occurring in frequencies between 6 and 10 Hz are more significant for learning these patterns than events and other biomechanical movements related to the gait cycle, as usually explored in the literature.
NOD2 signaling in CD11c + cells is critical for humoral immune responses during oral vaccination and maintaining the gut microbiome
Authors: Fox B. E. , Vilander A. , Abdo Z. , Dean G. A.
Published: May 2022

Nucleotide-binding oligomerization domain containing 2 (NOD2) is a critical regulator of immune responses within the gastrointestinal tract. This innate immune receptor is expressed by several cell types, including both hematopoietic and nonhematopoietic cells within the gastrointestinal tract. Vaccination targeting the gastrointestinal mucosal immune system is especially difficult due to both physical and mechanistic barriers to reaching inductive sites. The use of lactic acid bacteria is appealing due to their ability to persist within harsh conditions, expression of selected adjuvants, and manufacturing advantages. Recombinant Lactobacillus acidophilus (rLA) has shown great promise in activating the mucosal immune response with minimal impacts on the resident microbiome. To better classify the kinetics of mucosal vaccination with rLA, we utilized mice harboring knockouts of NOD2 expression specifically within CD11c + cells. The results presented here show that NOD2 signaling in CD11c + cells is necessary for mounting a humoral immune response against exogenous antigens expressed by rLA. Additionally, disruption of NOD2 signaling in these cells results in an altered bacterial microbiome profile in both control mice and mice receiving L. acidophilus strain NCK1895 and vaccine strain LaOVA.
Novel metal based nanocomposite for rapid and efficient removal of lead from contaminated wastewater sorption kinetics, thermodynamics and mechanisms
Authors: Elkhatib Elsayed A. , Moharem Mohamed L. , Saad Ahmed F. , Attia Farida A.
Published: May 2022

A sol–gel method was utilized to prepare a novel nanocomposite adsorbent (nMgO/bentonite) and was tested for Pb(II) removal from aqueous solutions. The produced nanocomposite was investigated using, SEM–EDX, XRD, and FTIR analyses before and after Pb adsorption. Adsorption equilibrium and kinetic experiments were run in batch system under different conditions of pH, adsorbent dose, competitive cations, contact time and temperature. The results exhibited rapid Pb(II) adsorption by the nanocomposite in the first five min. Experimental lead adsorption equilibrium and kinetics data fitted well to Langmuir and power function models, respectively as indicated from the lowest standard error (SE) values. The calculated Langmuir maximum adsorption capacity (qmax) value of nanocomposite (75 mg g−1) was 4.5 times higher than that of bentonite (16.66 mg g−1). Moreover, the highest quantity of Pb(II) uptake was achieved at temperature of 307 K and pH 9. The Langmuir sorption capacity of the nanocomposite for Pb(II) increased from 75 to 145 mg g−1 with increasing temperature from 287 to 307 K. The thermodynamic parameters of Pb(II) adsorption by the nanocomposite affirm the spontaneous and endothermic nature of the adsorption process. Lead adsorption mechanisms by the nanocomposite were proposed and discussed.
Asynchronous recovery of predators and prey conditions resilience to drought in a neotropical ecosystem
Authors: Ruiz Thomas , Carrias Jean-François , Bonhomme Camille , Farjalla Vinicius F. , Jassey Vincent E. J. , Leflaive Joséphine , Compin Arthur , Leroy Céline , Corbara Bruno , Srivastava Diane S. , Céréghino Régis
Published: May 2022

The predicted increase in the intensity and frequency of drought events associated with global climate change will impose severe hydrological stress to freshwater ecosystems, potentially altering their structure and function. Unlike freshwater communities’ direct response to drought, their post-drought recovery capacities remain understudied despite being an essential component driving ecosystem resilience. Here we used tank bromeliad as model ecosystem to emulate droughts of different duration and then assess the recovery capacities of ecosystem structure and function. We followed macroinvertebrate predator and prey biomass to characterize the recovery dynamics of trophic structure (i.e. predator–prey biomass ratio) during the post-drought rewetting phase. We showed that drought significantly affects the trophic structure of macroinvertebrates by reducing the predator–prey biomass ratio. The asynchronous recovery of predator and prey biomass appeared as a critical driver of the post-drought recovery trajectory of trophic structure. Litter decomposition rate, which is an essential ecosystem function, remained stable after drought events, indicating the presence of compensatory effects between detritivores biomass and detritivores feeding activity. We conclude that, in a context of global change, the asynchrony in post-drought recovery of different trophic levels may impact the overall drought resilience of small freshwater ecosystems in a more complex way than expected.
Experimental investigation of CO2 uptake in CO2 hydrates formation with amino acids as kinetic promoters and its dissociation at high temperature
Authors: Srivastava Shubhangi , Kollemparembil Ann Mary , Zettel Viktoria , Claßen Timo , Gatternig Bernhard , Delgado Antonio , Hitzmann Bernd
Published: May 2022

The dissociation of CO2 gas hydrates (GH) with amino acid kinetic promoters and without promoters was studied at a high temperature of 90 °C for a period of 20 min to understand the percentage of CO2 gas and to select the best promoter that aids CO2 gas entrapment along with stability at a high temperature. The possibility of using four hydrophobic food grade amino acids, namely cysteine, valine, leucine, and methionine, and one surfactant, lecithin, as kinetic promoters for CO2 GH has been studied. The amino acids were added 0.5 g (wt%), and lecithin was added 5 g for the GH production. Furthermore, the amino acids leucine and methionine gave some positive results, therefore, these amino acids were carried further for the experimentation purpose in the production of CO2 GH. Also, a combinational use of these amino acids was studied to investigate the effect on % CO2 retention in comparison to the normal GH. From the results, it was observed that the stability of GH decreases with an increase in temperature, but the addition of promoters, especially leucine + methionine + lecithin increased the CO2 uptake during GH formation.
Factors affecting the implementation of soil conservation practices among Iranian farmers
Authors: Savari Moslem , Yazdanpanah Masoud , Rouzaneh Davoud
Published: May 2022

As soil is the basis for agriculture, soil erosion is one of the major threats to food security in arid and semi-arid regions across the world. Therefore, soil conservation is an important step to increase productivity and ensure sustainability in agriculture. To implement soil conservation measures, farmers must voluntarily adopt soil conservation behaviors. Therefore, it may be important to understand the psychological and social factors that influence farmers' environmental sustainability. Thus, in this study, social cognitive theory (SCT) was used as a theoretical framework to investigate the factors influencing Iranian farmers' soil conservation behaviors (SCBs). The results showed that SCT was a successful theory in this area as it could explain 0.662 and 0.537 percent of behavioral intentions (BI) and SCBs, respectively. Moreover, the two components of self-efficacy (SE) and outcome expectancies (OE) were the strongest SCT variables that influenced SCBs. Overall, our results may provide new insights for policymakers in the agricultural sector to reduce soil erosion.
Low adherence to the guideline for the acute treatment of migraine
Authors: Olesen Astrid , Schytz Henrik Winther , Ostrowski Sisse Rye , Topholm Mie , Nielsen Kaspar , Erikstrup Christian , Mikkelsen Susan , Pedersen Ole Birger , Olesen Jes , Hansen Thomas Folkmann , Chalmer Mona Ameri
Published: May 2022

The real-world use of triptans in the treatment of migraine is disappointing. Only 12% of the Danish migraine population purchased a triptan between 2014 and 2019, and only 43% repurchased a triptan after first prescription. The aim of the present study was to assess whether physicians and patients adhere to the therapeutic guideline on acute migraine treatment. We interviewed 299 triptan experienced participants with migraine and 101 triptan naïve participants with migraine from the Danish Migraine Population Cohort, using a semi-structured questionnaire. Descriptive statistical analyses were used to study the association with triptan use and the assessed factors. Among triptan naïve participants with migraine, 64% had consulted their general practitioner about their migraine, of whom only 23% received information about the possibility of triptan treatment. Among triptan experienced participants, 77% had only tried one type of triptan. Only 12% could recall they had been informed by their general practitioner to try each triptan three times before giving up. Twenty percent were informed to try three different triptans in total, if the first did not work. In disagreement with the guideline, participants who reported a low pain reduction by a triptan had only tried one type of triptan. Our study shows a low adherence to therapeutic guideline for the attack treatment of migraine. There is a need for better education of general practitioners regarding treatment of migraine. Future campaigns should aim to inform both the public and the general practitioner about antimigraine treatments.
Adaptation of the gut pathobiont Enterococcus faecalis to deoxycholate and taurocholate bile acids
Authors: Repoila F. , Le Bohec F. , Guérin C. , Lacoux C. , Tiwari S. , Jaiswal A. K. , Santana M. Passos , Kennedy S. P. , Quinquis B. , Rainteau D. , Juillard V. , Furlan S. , Bouloc P. , Nicolas P. , Miyoshi A. , Azevedo V. , Serror P.
Published: May 2022

Enterococcus faecalis is a natural inhabitant of the human gastrointestinal tract. This bacterial species is subdominant in a healthy physiological state of the gut microbiota (eubiosis) in adults, but can become dominant and cause infections when the intestinal homeostasis is disrupted (dysbiosis). The relatively high concentrations of bile acids deoxycholate (DCA) and taurocholate (TCA) hallmark eubiosis and dysbiosis, respectively. This study aimed to better understand how E. faecalis adapts to DCA and TCA. We showed that DCA impairs E. faecalis growth and possibly imposes a continuous adjustment in the expression of many essential genes, including a majority of ribosomal proteins. This may account for slow growth and low levels of E. faecalis in the gut. In contrast, TCA had no detectable growth effect. The evolving transcriptome upon TCA adaptation showed the early activation of an oligopeptide permease system (opp2) followed by the adjustment of amino acid and nucleotide metabolisms. We provide evidence that TCA favors the exploitation of oligopeptide resources to fuel amino acid needs in limiting oligopeptide conditions. Altogether, our data suggest that the combined effects of decreased DCA and increased TCA concentrations can contribute to the rise of E. faecalis population during dysbiosis.
Type 2 diabetes mellitus patients’ lived experience at a tertiary hospital in Ekiti State, Nigeria
Authors: Okurumeh Anthonia I. , Akpor Oluwaseyi A. , Okeya Olutoyin E. , Akpor Oghenerobor B.
Published: May 2022

Diabetes mellitus is a complex and chronic metabolic disorder that is associated with multiple complications and disabilities. This contributes to increased mortality and poor quality of life among affected individuals. The study explored the lived experience of patients with type 2 diabetes mellitus at a Teaching Hospital in Ekiti State, Nigeria. A mixed method of qualitative and quantitative design was adopted. For the quantitative aspect, a convenience sampling technique was employed while the instrument used was an adapted questionnaire. For the qualitative aspect, focus-group discussion involving twenty-four participants was conducted, and the sample size was determined by data saturation. Qualitative data was analyzed using thematic transcription. Findings revealed that 55.6% of the participants were females while 63.5% had tertiary education. Majority (18 of 24) of the respondents experienced body weakness, frequent urination and excessive thirst when diagnosed of diabetes mellitus and later experienced occasional body weakness, burning sensation, tingling and numbness of the feet, fatigue, loss of libido, and occasional visual disturbance. Two-third of the participants reported being indifferent when they were informed about their condition. However, majority of the participants perceived that the cause of diabetes mellitus was heredity. More than two-third of the participants did not experience reduction in their normal daily activities but rather experienced occasional emotional disturbances, anxiety and challenges with self-management of diabetes and this was associated with maintaining a normo-glycemic state due to the financial implications of drugs and dietary modifications.
Distributed adaptive fixed-time neural networks control for nonaffine nonlinear multiagent systems
Authors: Li Yang , Zhu Quanmin , Zhang Jianhua
Published: May 2022

This paper, with the adaptive backstepping technique, presents a novel fixed-time neural networks leader–follower consensus tracking control scheme for a class of nonaffine nonlinear multiagent systems. The expression of the error system is derived, based on homeomorphism mapping theory, to formulate a set of distributed adaptive backstepping neural networks controllers. The weights of the neural networks controllers are trained, by an adaptive law based on fixed-time theory, to determine the adaptive control input. The control algorithm can guarantee that the output of the follower agents of the system effectively follow the output of the leader of the system in a fixed time, while the upper bound of the settling time can be calculated without initial parameters. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed consensus tracking control approach. A step-by-step procedure for engineers and researchers interested in applications is proposed.
Quantum Floquet engineering with an exactly solvable tight-binding chain in a cavity
Authors: Eckhardt Christian J. , Passetti Giacomo , Othman Moustafa , Karrasch Christoph , Cavaliere Fabio , Sentef Michael A. , Kennes Dante M.
Published: May 2022

Recent experimental advances enable the manipulation of quantum matter by exploiting the quantum nature of light. However, paradigmatic exactly solvable models, such as the Dicke, Rabi or Jaynes-Cummings models for quantum-optical systems, are scarce in the corresponding solid-state, quantum materials context. Focusing on the long-wavelength limit for the light, here, we provide such an exactly solvable model given by a tight-binding chain coupled to a single cavity mode via a quantized version of the Peierls substitution. We show that perturbative expansions in the light-matter coupling have to be taken with care and can easily lead to a false superradiant phase. Furthermore, we provide an analytical expression for the groundstate in the thermodynamic limit, in which the cavity photons are squeezed by the light-matter coupling. In addition, we derive analytical expressions for the electronic single-particle spectral function and optical conductivity. We unveil quantum Floquet engineering signatures in these dynamical response functions, such as analogs to dynamical localization and replica side bands, complementing paradigmatic classical Floquet engineering results. Strikingly, the Drude weight in the optical conductivity of the electrons is partially suppressed by the presence of a single cavity mode through an induced electron-electron interaction.
Computational mechanism investigation of bismuth (BiIII/BiV) redox-catalyzed fluorination of arylboronic esters
Authors: Jia Feiyun , Luo Jiewei , Zhang Bo
Published: May 2022

DFT calculations reveal details of the redox catalytic mechanism of a heavier main group element, bismuth.
We are never ever getting (back to) ideal symmetry: structure and luminescence in a ten-coordinated europium(iii) sulfate crystal
Authors: Storm Thomsen Maria , Anker Andy S. , Kacenauskaite Laura , Sørensen Thomas Just
Published: May 2022

Our theoretical treatment of electronic structures in coordination complexes often rests on assumptions of symmetry.
Hybridization-specific chemical reactions to create interstrand crosslinking and threaded structures of nucleic acids
Authors: Onizuka Kazumitsu , Yamano Yuuhei , Abdelhady Ahmed Mostafa , Nagatsugi Fumi
Published: May 2022

This review introduces the creation of interstrand crosslinking and threaded structures based on the hybridization-specific chemical reactions and their functions and perspectives in oligonucleotide therapeutics, chemical biology and nanotechnology.
Mechanism of Zn salt-induced deactivation of a Cu/activated carbon catalyst for low-temperature denitration via CO-SCR
Authors: Wen Zhenjing , Huang Bangfu , Shi Zhe , Yang Zhengyu , Dai Meng , Li Wanjun , Zi Gaoyong , Luo Liubin
Published: May 2022

Zn slats compete with CO and NO for the active sites. Cl− not only occupies oxygen vacancies but also inhibits the Oβ migration. SO42− increases the surface acidity and promotes the Oβ supplementation, which inhibits toxicity.
Mediating the slow dynamics of polyacrylates by small molecule-bridged hydrogen bonds
Authors: Liu Yuanbiao , Shi Gaopeng , Wu Guozhang
Published: May 2022

A diminishing slow mode that gradually merges with the prominentα-peak is found in the polyacrylate matrix by adding a hindered phenol (CA) capable of forming three intermolecular hydrogen bonds per molecule with the polymer chain.
A bifunctional catalyst based on a carbon quantum dots/mesoporous SrTiO3 heterostructure for cascade photoelectrochemical nitrogen reduction
Authors: Hu Yongming , Zhao Zhi Liang , Ahmad Rafia , Harb Moussab , Cavallo Luigi , Azofra Luis Miguel , Jiang San Ping , Zhang Xinyi
Published: May 2022

An ultrathin carbon quantum dots modified hydrogenated mesoporous SrTiO3 heterostructure (CQDs/STO) has been developed as a bifunctional catalyst for enhanced photoelectrochemical nitrogen reduction, resulting in a ∼50% increase in the ammonia yield.
Preparation of a biomimetic superomniphobic hierarchical structure and analysis of droplet wettability
Authors: Li Jing , Feng Qunxiang , Guo Nan , Wang Fei , Du Xin , Du Feng
Published: May 2022

In this study, a bioinspired hierarchical structure was formed with superomniphobicity on a 7075 aluminium alloy using laser ablation. The morphology and wetting characteristics of the biomimetic sample surface were characterised using scanning electron microscopy, laser confocal microscopy, and contact angle measurements. The effect of the liquid properties and surface structures on the rolling behaviour was investigated. The results suggest that the fabricated biomimetic sample surface was a hierarchical structure. The prepared sample had superomniphobicity and low adhesion properties, and the contact angles of six different liquid droplets on the sample surface reached or approached 150°. Specifically, the largest contact angle was 152°, and the average rolling angle was 7.7°. This multi‐hydrophobic surface provides a valuable reference for the research study and use of a variety of solid–liquid contacts.