Miracle-dz/UniFAR-FTUs huggingface dataset:
Hemagglutination Inhibition (HAI) antibody landscapes after vaccination with H7Nx virus like particles

Background A systemic evaluation of the antigenic differences of the H7 influenza hemagglutinin (HA) proteins, especially for the viruses isolated after 2016, are limited. The purpose of this study was to investigate the antigenic differences of major H7 strains with an ultimate aim to discover H7 HA proteins that can elicit protective receptor-binding antibodies against co-circulating H7 influenza strains. Method A panel of eight H7 influenza strains were selected from 3,633 H7 HA amino acid sequences identified over the past two decades (2000–2018). The sequences were expressed on the surface of virus like particles (VLPs) and used to vaccinate C57BL/6 mice. Serum samples were collected and tested for hemagglutination-inhibition (HAI) activity. The vaccinated mice were challenged with lethal dose of H7N9 virus, A/Anhui/1/2013. Results VLPs expressing the H7 HA antigens elicited broadly reactive antibodies each of the selected H7 HAs, except the A/Turkey/Italy/589/2000 (Italy/00) H7 HA. A putative glycosylation due to an A169T substitution in antigenic site B was identified as a unique antigenic profile of Italy/00. Introduction of the putative glycosylation site (H7 HA-A169T) significantly altered the antigenic profile of HA of the A/Anhui/1/2013 (H7N9) strain. Conclusion This study identified key amino acid mutations that result in severe vaccine mismatches for future H7 epidemics. Future universal influenza vaccine candidates will need to focus on viral variants with these key mutations.
The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling

Significance Many biological networks are modeled with multivariate discrete dynamical systems. Current theory suggests that the network of interactions captures salient features of system dynamics, but it misses a key aspect of these networks: some interactions are more important than others due to dynamical redundancy and nonlinearity. This unequivalence leads to a canalized dynamics that differs from constraints inferred from network structure alone. To capture the redundancy present in biochemical regulatory and signaling interactions, we present the effective graph, an experimentally validated mathematical framework that synthesizes both structure and dynamics in a weighted graph representation of discrete multivariate systems. Our results demonstrate the ubiquity of redundancy in biology and provide a tool to increase causal explainability and control of biochemical systems. The ability to map causal interactions underlying genetic control and cellular signaling has led to increasingly accurate models of the complex biochemical networks that regulate cellular function. These network models provide deep insights into the organization, dynamics, and function of biochemical systems: for example, by revealing genetic control pathways involved in disease. However, the traditional representation of biochemical networks as binary interaction graphs fails to accurately represent an important dynamical feature of these multivariate systems: some pathways propagate control signals much more effectively than do others. Such heterogeneity of interactions reflects canalization—the system is robust to dynamical interventions in redundant pathways but responsive to interventions in effective pathways. Here, we introduce the effective graph, a weighted graph that captures the nonlinear logical redundancy present in biochemical network regulation, signaling, and control. Using 78 experimentally validated models derived from systems biology, we demonstrate that 1) redundant pathways are prevalent in biological models of biochemical regulation, 2) the effective graph provides a probabilistic but precise characterization of multivariate dynamics in a causal graph form, and 3) the effective graph provides an accurate explanation of how dynamical perturbation and control signals, such as those induced by cancer drug therapies, propagate in biochemical pathways. Overall, our results indicate that the effective graph provides an enriched description of the structure and dynamics of networked multivariate causal interactions. We demonstrate that it improves explainability, prediction, and control of complex dynamical systems in general and biochemical regulation in particular.
Growth and Photosynthetic Activity for Tomato Plants Treated With different Cations

The effect of the treatment with nitrates on growth and photosynthesis for tomato plants(Lycopersicon esculentum)is presented. Tomato plants were grown in pots and treated with solution of nitrates. The experiments were carried out twice in a greenhouse of the University. Measurements for leaves number, height of plants and flowers number were performed. The content and composition of photosynthetic pigments were examined in the third leaf of tomato plants. Our results show that the tomato plants treated with Mg(NO)2and Ca(NO)2have a bigger content of the pigments but the tomato plants treated with Ba(NO)2are better developed than the control. The physiological significance of the modifications to the pigment composition induced by this treatment is discussed.
Miscibility and specific interactions in blends of poly(4‐vinylphenol‐co‐methyl methacrylate)/poly(styrene‐co‐4‐vinylpyridine)

The miscibility and phase behavior of poly(4-vinylphenol-co-methyl methacrylate) (PVPhMMA50) containing 50% of methyl methacrylate with random copolymers of poly(styrene-co-4-vinylpyridine) (PS4VPy) containing 5, 15, 30, 40, and 100% of 4-vinylpyridine, respectively, were investigated by differential scanning calorimetry, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). It was shown that for a composition of 4-vinylpyridine less than 30%, all blends of PVPhMMA50/PS4VPy are immiscible, characterized by the apparition of two glass transitions (Tg) over their entire composition range. However, above this composition, a single Tg has been observed in all the blends of PVPhMMA50 and PS4VPy. When the amount of vinylpyridine exceeds to 40% in PS4VPy, the obtained Tgs of PVPhMMA50/PS4VPy blends were found to be significantly higher than those observed for each individual component of the mixture indicating that these blends are able to form interpolymer complexes. FTIR analysis reveals the existence of preferential specific interactions via hydrogen bonding between the hydroxyl and pyridyl groups and intensifies when the amount of 4VPy is increased in PS4VPy copolymers. Furthermore, the quantitative FTIR study carried out for PVPhMMA50/PS4VPy blends was also performed for the vinylphenol and vinylpyridine functional groups. These results were also confirmed by SEM study. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
Gas density in a pulsed positive streamer measured using laser shadowgraph

Gas density in a pulsed positive streamer is quantitatively measured using a laser shadowgraph. The discharge occurs in a point–plane gap of 13 mm in humid air. After the onset of the streamer, the gas density decreases in two steps. The first step is a rapid decrease in gas density, which is caused by gas heating owing to electron impact onto molecules. This step is significant within 1 mm from the anode, although it occurs throughout the gap. The second step is a gradual decrease in gas density after the streamer pulse, which is caused by gas heating due to vibration-to-translation energy transfer. This step takes place mainly in the secondary streamer channel, not in the primary streamer channel. When the discharge voltage is 32 kV, the decrease in gas density reaches 30% of the ambient density. This large decrease in gas density affects the rate of various chemical reactions in the postdischarge period.
Physiological adjustments to high foraging effort negatively affect fecundity but not final reproductive output in captive zebra finches.

Foraging at elevated rates to provision offspring is thought to be an energetically costly activity and it has been suggested that there are potentially physiological costs associated with the high workload involved. However, for the most part evidence for costs of increased foraging and/or reproductive effort is weak. Furthermore, despite some experimental evidence demonstrating negative effects of increased foraging and parental effort, the physiological mechanisms underlying costs associated with high workload remain poorly understood. To examine how high workload affects hematology, oxidative stress and reproductive output, we experimentally manipulated foraging effort in captive zebra finches, Taeniopygia guttata, using a previously described technique, and allowed individuals to breed first in low foraging effort conditions, and then in high foraging effort conditions. We found that birds up-regulated hematocrit and hemoglobin in response to training. Birds subjected to increased workload during reproduction had lower fecundity, although final reproductive output was not significantly different than that of controls. Offspring of parents subjected to high workload during reproduction also had higher oxidative stress when they were 90 d of age. Total antioxidant capacity and reactive oxygen metabolites of birds responded differently in the two breeding attempts, but we did detect an overall increase in oxidative stress in response to training in either attempt, which could explain the lower fecundity observed in birds subjected to increased workload during reproduction.
Unexpected greening in a boreal permafrost peatland undergoing forest loss is partially attributable to tree species turnover

Time series of vegetation indices derived from satellite imagery are useful in measuring vegetation response to climate warming in remote northern regions. These indices show that productivity is generally declining in the boreal forest, but it is unclear which components of boreal vegetation are driving these trends. We aimed to compare trends in the normalized difference vegetation index (NDVI) to forest growth and demographic data taken from a 10 ha mapped plot located in a spruce‐dominated boreal peatland. We used microcores to quantify recent growth trends and tree census data to characterize mortality and recruitment rates of the three dominant tree species. We then compared spatial patterns in growth and demography to patterns in Landsat‐derived maximum NDVI trends (1984–2019) in 78 pixels that fell within the plot. We found that NDVI trends were predominantly positive (i.e., “greening”) in spite of the ongoing loss of black spruce (the dominant species; 80% of stems) from the plot. The magnitude of these trends correlated positively with black spruce growth trends, but was also governed to a large extent by tree mortality and recruitment. Greening trends were weaker (lower slope) in areas with high larch mortality, and high turnover of spruce and birch, but stronger (higher slope) in areas with high larch recruitment. Larch dominance is currently low (~11% of stems), but it is increasing in abundance as permafrost thaw progresses and will likely have a substantial influence on future NDVI trends. Our results emphasize that NDVI trends in boreal peatlands can be positive even when the forest as a whole is in decline, and that the magnitude of trends can be strongly influenced by the demographics of uncommon species.
Recognizing and counting Dendrocephalus brasiliensis (Crustacea: Anostraca) cysts using deep learning

The Dendrocephalus brasiliensis, a native species from South America, is a freshwater crustacean well explored in conservational and productive activities. Its main characteristics are its rusticity and resistance cysts production, in which the hatching requires a period of dehydration. Independent of the species utilization nature, it is essential to manipulate its cysts, such as the counting using microscopes. Manually counting is a difficult task, prone to errors, and that also very time-consuming. In this paper, we propose an automatized approach for the detection and counting of Dendrocephalus brasiliensis cysts from images captured by a digital microscope. For this purpose, we built the DBrasiliensis dataset, a repository with 246 images containing 5141 cysts of Dendrocephalus brasiliensis. Then, we trained two state-of-the-art object detection methods, YOLOv3 (You Only Look Once) and Faster R-CNN (Region-based Convolutional Neural Networks), on DBrasiliensis dataset in order to compare them under both cyst detection and counting tasks. Experiments showed evidence that YOLOv3 is superior to Faster R-CNN, achieving an accuracy rate of 83,74%, R2 of 0.88, RMSE (Root Mean Square Error) of 3.49, and MAE (Mean Absolute Error) of 2.24 on cyst detection and counting. Moreover, we showed that is possible to infer the number of cysts of a substrate, with known weight, by performing the automated counting of some of its samples. In conclusion, the proposed approach using YOLOv3 is adequate to detect and count Dendrocephalus brasiliensis cysts. The DBrasiliensis dataset can be accessed at: https://doi.org/10.6084/m9.figshare. 13073240.
Severity of post-traumatic stress symptoms, level of experienced stress and coping strategies in mothers of children previously treated in the neonatal intensive care unit.

OBJECTIVES The aim of the study was to develop a model of the relationship between the severity of post-traumatic stress symptoms, levels of experienced stress and coping strategies in mothers of children previously treated in neonatal intensive care units. METHODS Anonymous questionnaire survey covered 62 mothers of infants aged from three to 12 months who had previously been hospitalized in neonatal intensive care units. Respondents completed a questionnaire comprising standardized tools such as the Impact Event Scale - Revised (IES-R), COPE Inventory and Perceived Stress Scale (PSS-10). RESULTS The severity of PTSD symptoms is explained by the model comprising four variables: three stress coping strategies (focus on and venting of emotions, denial and mental disengagement) and perceived stress. The model explains nearly 40% of post-traumatic stress symptoms. Perceived stress partly affects PTSD through one stress coping strategy - denial, which also has the effect on post-traumatic stress symptoms severity regardless of perceived stress. CONCLUSIONS Focus on and venting of emotions, denial, mental disengagement, and the level of perceived stress are potentially modifiable factors that are strongly associated with PTSD. Planning, realization and assessment of interventions aimed at reduction of maladaptive coping strategies and perceived stress are recommended for mothers of infants requiring treatment in neonatal intensive care units. In order to minimize distress and improve coping with the treatment of the child, it is necessary to evaluate the effects of various methods of supporting parents.
Perfect Match Genomic Landscape strategy: Refinement and customization of reference genomes

Significance The accuracy of the nucleotide sequence of genomes is of utmost importance. The Perfect Match Genomic Landscape (PMGL) is a precise, sensitive, and nonstatistical strategy to detect genome variation. We used this strategy to refine reference genomes from microorganisms belonging to the three domains of life. Our studies show as well that the PMGL can be useful to detect variants in pathogen agents during a pandemic, and to isolate mutations generated during any desired stage of experimental evolution studies. We propose that the PMGL strategy could be the final step in the refinement of any haploid genome, independently of the methodology and algorithms used for its assembly. When addressing a genomic question, having a reliable and adequate reference genome is of utmost importance. This drives the necessity to refine and customize reference genomes (RGs). Our laboratory has recently developed a strategy, the Perfect Match Genomic Landscape (PMGL), to detect variation between genomes [K. Palacios-Flores et al. Genetics 208, 1631–1641 (2018)]. The PMGL is precise and sensitive and, in contrast to most currently used algorithms, is nonstatistical in nature. Here we demonstrate the power of PMGL to refine and customize RGs. As a proof-of-concept, we refined different versions of the Saccharomyces cerevisiae RG. We applied the automatic PMGL pipeline to refine the genomes of microorganisms belonging to the three domains of life: the archaea Methanococcus maripaludis and Pyrococcus furiosus; the bacteria Escherichia coli, Staphylococcus aureus, and Bacillus subtilis; and the eukarya Schizosaccharomyces pombe, Aspergillus oryzae, and several strains of Saccharomyces paradoxus. We analyzed the reference genome of the virus SARS-CoV-2 and previously published viral genomes from patients’ samples with COVID-19. We performed a mutation-accumulation experiment in E. coli and show that the PMGL strategy can detect specific mutations generated at any desired step of the whole procedure. We propose that PMGL can be used as a final step for the refinement and customization of any haploid genome, independently of the strategies and algorithms used in its assembly.
Cytotoxicity and antimicrobial activity of synthetic peptides alone or in combination with conventional antimicrobials against fish pathogenic bacteria

This study aimed to evaluate the in vitro cytotoxicity and efficacy of synthetic host defence peptides (HDPs), alone or in combination with florfenicol (FFC), oxytetracycline (OTC) or thiamphenicol (TAP), against different pathogenic bacteria isolated from diseased fish.
Placentas delivered by pre‐pregnant obese women have reduced abundance and diversity in the microbiome

Maternal pre‐pregnancy obesity may have an impact on both maternal and fetal health. We examined the microbiome recovered from placentas in a multi‐ethnic maternal pre‐pregnant obesity cohort, through an optimized microbiome protocol to enrich low bacterial biomass samples. We found that the microbiomes recovered from the placentas of obese pre‐pregnant mothers are less abundant and less diverse when compared to those from mothers of normal pre‐pregnancy weight. Microbiome richness also decreases from the maternal side to the fetal side, demonstrating heterogeneity by geolocation within the placenta. In summary, our study shows that the microbiomes recovered from the placentas are associated with pre‐pregnancy obesity.
Decreased Medical Care During the COVID-19 Pandemic – A Comprehensive Analysis of Radiological Examinations

Abstract Objectives As a cross-section discipline within the hospital infrastructure, radiological departments might be able to provide important information regarding the impact of the COVID-19 pandemic on healthcare. The goal of this study was to quantify changes in medical care during the first wave of the pandemic using radiological examinations as a comprehensive surrogate marker and to determine potential future workload. Methods A retrospective analysis of all radiological examinations during the first wave of the pandemic was performed. The number of examinations was compared to time-matched control periods. Furthermore, an in-depth analysis of radiological examinations attributed to various medical specialties was conducted and postponed examinations were extrapolated to calculate additional workload in the near future. Results A total of 596,760 examinations were analyzed. Overall case volumes decreased by an average of 41 % during the shutdown compared to the control period. The most affected radiological modalities were sonography (–54 %), X-ray (–47 %) followed by MRI (–42 %). The most affected medical specialty was trauma and orthopedics (–60 % case volume) followed by general surgery (–49 %). Examination numbers increased during the post-shutdown period leading to a predicted additional workload of up to 22 %. Conclusion This study shows a marked decrease in radiological examinations in total and among several core medical specialties, indicating a significant reduction in medical care during the first COVID-19 shutdown. Key Points: Number of radiological examinations decreased by 41 % during the first wave of the COVID-19 pandemic. Several core medical specialties were heavily affected with a reduction of case volumes up to 60 %. When extrapolating postponed examinations to the near future, the overall workload for radiological departments might increase up to 22 %. Citation Format Fleckenstein FN, Maleitzke T, Böning G et al. Decreased Medical Care During the COVID-19 Pandemic – A Comprehensive Analysis of Radiological Examinations. Fortschr Röntgenstr 2021; 193: 937 – 946
Thyroid function in postpartum psychosis: An exploratory study

The study aimed to compare thyroid function between psychosis with postpartum onset (PPO), psychosis without postpartum onset (PWPO), and normal postpartum females (HC). Twenty women were recruited in each of the three groups. The PPO group had significantly greater psychopathology and shorter episodes compared to the PWPO group. The PPO group was found to have significantly greater right lobe volume than the other groups. The PPO group also had significantly higher FT4 levels than the HC group. We conclude that isolated increase in FT4 and thyroid lobe volumetric changes could be more specifically associated with psychosis of post‐partum onset.
Gluten Degradation, Pharmacokinetics, Safety, and Tolerability of TAK-062, an Engineered Enzyme to Treat Celiac Disease.

BACKGROUND & AIMS Celiac disease (CeD) is an immune-mediated disorder triggered by the ingestion of gluten. Despite adhering to a gluten-free diet (the only management option available to patients with CeD), many patients continue to experience symptoms and intestinal injury. Degradation of immunogenic fractions of gluten peptides in the stomach has been proposed as an approach to reduce toxicity of ingested gluten; however, no enzymes evaluated to date have demonstrated sufficient gluten degradation in complex meals. TAK-062 is a novel, computationally designed endopeptidase under development for the treatment of patients with CeD. METHODS Pharmacokinetics, safety, and tolerability of TAK-062 100-900 mg were evaluated in a phase 1 dose escalation study in healthy participants and patients with CeD. Gluten degradation by TAK-062 was evaluated under simulated gastric conditions in vitro and in healthy participants in the phase 1 study, with and without pretreatment with a proton pump inhibitor. Residual gluten (collected via gastric aspiration in the phase 1 study) was quantified using R5 and G12 monoclonal antibody enzyme-linked immunosorbent assays. RESULTS In vitro, TAK-062 degraded more than 99% gluten (3 g and 9 g) within 10 minutes. In the phase 1 study, administration of TAK-062 was well tolerated and resulted in a median gluten degradation ranging from 97% to more than 99%, in complex meals containing 1-6 g gluten, at 20-65 minutes post dose. CONCLUSIONS TAK-062 is well tolerated, and rapidly and effectively degrades large amounts of gluten, supporting the development of this novel enzyme as an oral therapeutic for patients with CeD.
The aggregation of methane in aqueous solution

Molecular dynamics simulations, 1.0 ns long, of methane particles in water show the existence of a tendency for aggregation of these solutes which increases with temperature in the range 319–351 K. This is measured by a rise in the contact-configuration peak in the methane–methane radial distribution function at the expense of a decrease in the solvent-separated configuration peak. The observed solute–solute interaction reaches a maximum at 351 K before decreasing in magnitude at 358 K. These observations are consistent with an entropy-driven hydrophobic attraction.
Exploring the effects of genomic testing on fear of cancer recurrence among breast cancer survivors

Fear of cancer recurrence (FCR) is the greatest unmet psychosocial need among breast cancer survivors (BCS). The Oncotype Dx® test predicts the 10‐year risk of distant recurrence and benefit of adjuvant chemotherapy among women with early stage hormone receptor‐positive breast cancer. Despite the test's clinical utility, psychosocial responses are poorly understood.