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The neighborhood polynomial of graph G is the generating function for the number of vertex subsets of G of which the vertices have a common neighbor in G. In this paper, we investigate the behavior of this polynomial under several graph operations. Specifically, we provide an explicit formula for the neighborhood polynomial of the graph obtained from a given graph G by vertex attachment. We use this result to propose a recursive algorithm for the calculation of the neighborhood polynomial. Finally, we prove that the neighborhood polynomial can be found in polynomial-time in the class of k-degenerate graphs.

Abstract Background Sustainable agriculture increasingly emphasizes the importance of microbial communities in influencing plant health and productivity. In viticulture, understanding the impact of management practices on fungal communities is critical, given their role in disease dynamics, grape and wine quality. This study investigates the effects of integrated, organic, and biodynamic management practices on the diversity and function of fungal communities in a vineyard located in Geisenheim, Germany, focusing on above-ground parts such as bark, leaves, and grapes. Results Our findings indicate that while overall fungal species richness did not significantly differ among management systems across various compartments, the composition of these communities was distinctly influenced by the type of management system. In particular, leaf and grape compartments showed notable variations in fungal community structure between integrated and organic/biodynamic management. No differences were observed between organic and biodynamic management. Integrated management demonstrated a significantly higher abundance of mycoparasites in comparison to organic and biodynamic management, primarily attributed to the increased presence of Sporobolomyces roseus, Sporobolomyces ellipsoideus and Rhodotorula glutinis. Conclusions The findings highlight the importance of management practices in shaping fungal community composition and function in vineyards. Although overall species richness remained unaffected, community composition and functional diversity varied, highlighting the potential for strategic microbiome management to enhance vineyard sustainability and plant health.

This paper introduces a trivariate graph polynomial that is a common generalization of the domination polynomial, the Ising polynomial, the matching polynomial, and the cut polynomial of a graph. This new graph polynomial, called the bipartition polynomial, permits a variety of interesting representations, for instance as a sum ranging over all spanning forests. As a consequence, the bipartition polynomial is a powerful tool for proving properties of other graph polynomials and graph invariants. We apply this approach to show that, analogously to the Tutte polynomial, the Ising polynomial introduced by Andrén and Markström in [3], can be represented as a sum over spanning forests.

Abstract Objective Examining the distribution of breast cancer (BC) stage and molecular subtype among women aged below ( 65 years) the recommended screening age range helps to understand the screening program's characteristics and contributes to enhancing the effectiveness of BC screening programs. Methods In this retrospective study, female patients with newly diagnosed BC from 2010 to 2020 were identified. The distribution of cases in terms of TNM stages, severity classes, and subtypes was analysed according to age groups. Results A total of 3282 women diagnosed with BC were included in the analysis. Among these cases 51.4% were detected outside the screening age group, and these were characterized by a higher TNM stage compared to those diagnosed within the screening age band. We observed significantly higher relative frequency of advanced BC in the older age group compared to both the screening age population and women younger than 45 years (14.9% vs. 8.7% and 7.7%, P

Ultrasound is an excellent way to acquire data that reveal useful information about systems operating in harsh environments, which may include elevated temperature, ionizing radiation, and aggressive chemicals. The effects of harsh environments on piezoelectric materials have been studied in much more depth than the other aspects of ultrasonic transducers used in pulse-echo mode. Therefore, finite element simulations and laboratory experiments are used to demonstrate the unique characteristics of pulse-echo immersion testing. Using an aluminum nitride piezoelectric element mounted on a vessel wall, characteristics associated with electrode thickness, couplant, backing material, and an acoustic matching layer are investigated. Considering a wave path through a vessel wall and into a fluid containing a target, when the travel distance in the fluid is relatively short, it can be difficult to discern the target echo from the reverberations in the vessel wall. When an acoustic matching layer between the vessel wall and the fluid does not suffice, a simple subtractive signal-processing method can minimize the reverberations, leaving just the target echoes of interest. Simulations and experiments demonstrate that sufficient target echoes are detected to determine the time of flight. Furthermore, a simple disc-like surface anomaly on the target is detectable.

Abstract Besides vaccines, the development of antiviral drugs targeting SARS-CoV-2 is critical for preventing future COVID outbreaks. The SARS-CoV-2 main protease (Mpro), a cysteine protease with essential functions in viral replication, has been validated as an effective drug target. Here, we show that Mpro is subject to redox regulation in vitro and reversibly switches between the enzymatically active dimer and the functionally dormant monomer through redox modifications of cysteine residues. These include a disulfide-dithiol switch between the catalytic cysteine C145 and cysteine C117, and generation of an allosteric cysteine-lysine-cysteine SONOS bridge that is required for structural stability under oxidative stress conditions, such as those exerted by the innate immune system. We identify homo- and heterobifunctional reagents that mimic the redox switching and inhibit Mpro activity. The discovered redox switches are conserved in main proteases from other coronaviruses, e.g. MERS-CoV and SARS-CoV, indicating their potential as common druggable sites.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.

Regional tree die-off events generate large quantities of standing dead wood, raising concern over catastrophic wildfire and other hazards. Governmental responses to tree die-off have often focused on incentivizing biomass energy production that utilizes standing dead trees removed for safety concerns. However, the full distribution of potential woody bioenergy feedstock after tree die-off has not been evaluated due to the complexities of surveying and precisely measuring large forested areas. In this paper, we present a novel method for estimating standing dead biomass at a fine spatial resolution that combines aerial survey data with forest structure maps. Using this method, we quantify biomass generated by the unprecedented tree die-off that occurred in California following a 4-year drought and widespread pest outbreaks. The results are used to estimate feasibly recoverable feedstock for energy production. We find that approximately 95.1 million bone-dry tons (BDT) of dead biomass resulted from 2012-2017 mortality, with a lower bound of 26.2 million BDT. In other words, of the aboveground live tree biomass in 2012, ~1.3-4.8% died by 2017. Of the standing dead biomass, 29% meets minimum constraints for potential cost-effective bioenergy feedstock. This proportion drops to as low as 15% in the most affected areas due to terrain slope, wilderness status, and other factors, highlighting the need to complement disposal via biomass energy with other strategies to mitigate the risks of the tree mortality crisis, which is likely to only become more severe over time due to climate change.

To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1-10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk.

Biofuels are expected to play a major role in meeting California's long-term energy needs, but many factors influence the commercial viability of the various feedstock and production technology options. We developed a spatially explicit analytic framework that integrates models of plant growth, crop adoption, feedstock location, transportation logistics, economic impact, biorefinery costs and biorefinery energy use and emissions. We used this framework to assess the economic potential of hybrid poplar as a feedstock for jet fuel production in Northern California. Results suggest that the region has sufficient suitable croplands (2.3 million acres) and nonarable lands (1.5 million acres) for poplar cultivation to produce as much as 2.26 billion gallons of jet fuel annually. However, there are major obstacles to such large-scale production, including, on nonarable lands, low poplar yields and broad spatial distribution and, on croplands, competition with existing crops. We estimated the production cost of jet fuel to be $4.40 to $5.40 per gallon for poplar biomass grown on nonarable lands and $3.60 to $4.50 per gallon for biomass grown on irrigated cropland; the current market price is $2.12 per gallon. Improved poplar yields, use of supplementary feedstocks at the biorefinery and economic supports such as carbon credits could help to overcome these barriers.

Abstract Background IgG-class autoantibodies to N-Methyl-D-Aspartate (NMDA)-type glutamate receptors define a novel entity of autoimmune encephalitis. Studies examining the prevalence of NMDA IgA/IgM antibodies in patients with Parkinson disease with/without dementia produced conflicting results. We measured NMDA antibodies in a large, well phenotyped sample of Parkinson patients without and with cognitive impairment (n = 296) and controls (n = 295) free of neuropsychiatric disease. Detailed phenotyping and large numbers allowed statistically meaningful correlation of antibody status with diagnostic subgroups as well as quantitative indicators of disease severity and cognitive impairment. Methods NMDA antibodies were analysed in the serum of patients and controls using well established validated assays. We used anti-NMDA antibody positivity as the main independent variable and correlated it with disease status and phenotypic characteristics. Results The frequency of NMDA IgA/IgM antibodies was lower in Parkinson patients (13%) than in controls (22%) and higher than in previous studies in both groups. NMDA IgA/IgM antibodies were neither significantly associated with diagnostic subclasses of Parkinson disease according to cognitive impairment, nor with quantitative indicators of disease severity and cognitive impairment. A positive NMDA antibody status was positively correlated with age in controls but not in Parkinson patients. Conclusion It is unlikely albeit not impossible that NMDA antibodies play a significant role in the pathogenesis or progression of Parkinson disease e.g. to Parkinson disease with dementia, while NMDA IgG antibodies define a separate disease of its own.

Airborne Light Detection And Ranging (LiDAR) is an increasingly important modality for remote sensing of forests. Unfortunately, the lack of smooth surfaces complicates visualization of LiDAR data and of the results of fundamental analysis tasks that interest environmental scientists. In this paper, we use multi-pass point-cloud rendering to produce shadows, approximate occlusion, and a non-photorealistic silhouette effect which enhances the perception of the three-dimensional structure. We employ these techniques to provide visualizations for evaluating two analysis techniques, tree segmentation and forest structure clustering.

Abstract Background The aim of our study was the identification of genetic variants associated with postoperative complications after cardiac surgery. Methods We conducted a prospective, double-blind, multicenter, randomized trial (RIPHeart). We performed a genome-wide association study (GWAS) in 1170 patients of both genders (871 males, 299 females) from the RIPHeart-Study cohort. Patients undergoing non-emergent cardiac surgery were included. Primary endpoint comprises a binary composite complication rate covering atrial fibrillation, delirium, non-fatal myocardial infarction, acute renal failure and/or any new stroke until hospital discharge with a maximum of fourteen days after surgery. Results A total of 547,644 genotyped markers were available for analysis. Following quality control and adjustment for clinical covariate, one SNP reached genome-wide significance (PHLPP2, rs78064607, p = 3.77 × 10− 8) and 139 (adjusted for all other outcomes) SNPs showed promising association with p

Ultrasonic transducers are often used in the nuclear industry as sensors to monitor the health and process status of systems or the components. Some of the after-effects of the Fukushima Daiichi earthquake could have been eased if sensors had been in place inside the four reactors and sensed the overheating causing meltdown and steam explosions. The key element of ultrasonic sensors is the piezoelectric wafer, which is usually derived from lead-zirconate-titanate (Pb(Zr, Ti)O3, PZT). This material loses its piezoelectrical properties at a temperature of about 200 °C. It also undergoes nuclear transmutation. Bismuth titanate (Bi4Ti3O12, BiTi) has been considered as a potential candidate for replacing PZT at the middle of this temperature range, with many possible applications, since it has a Curie–Weiss temperature of about 650 °C. The aim of this article is to describe experimental details for operation in gamma and nuclear radiation concomitant with elevated temperatures and details of the performance of a BiTi sensor during and after irradiation testing. In these experiments, bismuth titanate has been demonstrated to operate up to a fast neutron fluence of 5 × 1020 n/cm2 and gamma radiation of 7.23 × 1021 (gamma/cm2). The results offer a perspective on the state-of the-art for a possible sensor for harsh environments of high temperature, Gamma radiation, and nuclear fluence.

Conventionally sol-gel spray-on transducers require a high-temperature (> 700 °C) sintering process; however, this process can affect the microstructure of the substrate material. For mechanical elbows and valves utilized for fluid transport in the energy sector, the components are designed to have a specific microstructure, and deviations from these specifications can create weak points in the system. For this reason it is important to investigate how the temperature of the deposition process affects the substrate. This paper investigates the effect of high-temperature and low-temperature (

Carbon dioxide (CO2) as one of the main factors driving climate change is known to increase grapevine growth and yield and could, therefore, have an impact on the fruit quality of vines. This study reports the effects of elevated CO2 (eCO2) on berry development and bunch structure of two grapevine cultivars (Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon) within the VineyardFACE (Free-Air Carbon Dioxide enrichment) experiment, using must analysis and non-invasive fluorescence sensor technology. Berry development was examined on five dates over three consecutive years by analyzing total soluble solids (TSS), pH, total acidity, organic acids, nutrition status, and non-invasive Multiplex measurements. Before harvest, secondary bunches were collected to examine bunch and berry parameters. Results showed that eCO2 had little impact on berry composition of Riesling and Cabernet Sauvignon during berry development, which could be related to bunch structure or single berry weight within single seasons. Elevated CO2 (eCO2) did not result in modified TSS accumulation during ripening but was directly related to the chlorophyll index SFR_R. Higher single berry weights (SBW), higher malic acid (MA), and lower tartaric acid (TAA) were examined at some stages during development of berries under eCO2 levels. Our study provides evidence that eCO2 did alter some bunch and berry parameters without a negative impact on fruit quality.