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Plant-parasitic nematodes are a major threat to crop production in all agricultural systems. The scarcity of classical resistance genes highlights a pressing need to find new ways to develop nematode-resistant germplasm. Here, we sequence and assemble a high-quality phased genome of the model cyst nematode Heterodera schachtii to provide a platform for the first system-wide dual analysis of host and parasite gene expression over time, covering all major parasitism stages. Analysis of the hologenome of the plant-nematode infection site identified metabolic pathways that were incomplete in the parasite but complemented by the host. Using a combination of bioinformatic, genetic, and biochemical approaches, we show that a highly atypical completion of vitamin B5 biosynthesis by the parasitic animal, putatively enabled by a horizontal gene transfer from a bacterium, is required for full pathogenicity. Knockout of either plant-encoded or now nematode-encoded steps in the pathway significantly reduces parasitic success. Our experiments establish a reference for cyst nematodes, further our understanding of the evolution of plant-parasitism by nematodes, and show that congruent differential expression of metabolic pathways in the infection hologenome represents a new way to find nematode susceptibility genes. The approach identifies genome-editing-amenable targets for future development of nematode-resistant crops.

PurposeOsteoporosis is a highly prevalent skeletal disease that frequently entails vertebral fractures. Areal bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the reference standard, but has well-known limitations. Texture analysis can provide surrogate markers of tissue microstructure based on computed tomography (CT) or magnetic resonance imaging (MRI) data of the spine, thus potentially improving fracture risk estimation beyond areal BMD. However, it is largely unknown whether MRI-derived texture analysis can predict volumetric BMD (vBMD), or whether a model incorporating texture analysis based on CT and MRI may be capable of differentiating between patients with and without osteoporotic vertebral fractures.Materials and methodsTwenty-six patients (15 females, median age: 73 years, 11 patients showing at least one osteoporotic vertebral fracture) who had CT and 3-Tesla chemical shift encoding-based water-fat MRI (CSE-MRI) available were analyzed. In total, 171 vertebral bodies of the thoracolumbar spine were segmented using an automatic convolutional neural network (CNN)-based framework, followed by extraction of integral and trabecular vBMD using CT data. For CSE-MRI, manual segmentation of vertebral bodies and consecutive extraction of the mean proton density fat fraction (PDFF) and T2* was performed. First-order, second-order, and higher-order texture features were derived from texture analysis using CT and CSE-MRI data. Stepwise multivariate linear regression models were computed using integral vBMD and fracture status as dependent variables.ResultsPatients with osteoporotic vertebral fractures showed significantly lower integral and trabecular vBMD when compared to patients without fractures (p

Plant-parasitic nematodes are a continuing threat to food security, causing an estimated 100 billion USD in crop losses each year. The most problematic are the obligate sedentary endoparasites (primarily root knot nematodes and cyst nematodes). Progress in understanding their biology is held back by a lack of tools for functional genetics: forward genetics is largely restricted to studies of natural variation in populations and reverse genetics is entirely reliant on RNA interference. There is an expectation that the development of functional genetic tools would accelerate the progress of research on plant-parasitic nematodes, and hence the development of novel control solutions. Here, we develop some of the foundational biology required to deliver a functional genetic tool kit in plant-parasitic nematodes. We characterize the gonads of male Heterodera schachtii and Meloidogyne hapla in the context of spermatogenesis. We test and optimize various methods for the delivery, expression, and/or detection of exogenous nucleic acids in plant-parasitic nematodes. We demonstrate that delivery of macromolecules to cyst and root knot nematode male germlines is difficult, but possible. Similarly, we demonstrate the delivery of oligonucleotides to root knot nematode gametes. Finally, we develop a transient expression system in plant-parasitic nematodes by demonstrating the delivery and expression of exogenous mRNA encoding various reporter genes throughout the body of H. schachtii juveniles using lipofectamine-based transfection. We anticipate these developments to be independently useful, will expedite the development of genetic modification tools for plant-parasitic nematodes, and ultimately catalyze research on a group of nematodes that threaten global food security.

BackgroundHeterodera glycines, commonly referred to as the soybean cyst nematode (SCN), is an obligatory and sedentary plant parasite that causes over a billion-dollar yield loss to soybean production annually. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. The parasitic success of H. glycines relies on the comprehensive re-engineering of an infection site into a syncytium, as well as the long-term suppression of host defense to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms of effector acquisition, diversification, and selection need to be understood before effective control strategies can be developed, but the lack of an annotated genome has been a major roadblock.ResultsHere, we use PacBio long-read technology to assemble a H. glycines genome of 738 contigs into 123 Mb with annotations for 29,769 genes. The genome contains significant numbers of repeats (34%), tandem duplicates (18.7 Mb), and horizontal gene transfer events (151 genes). A large number of putative effectors (431 genes) were identified in the genome, many of which were found in transposons.ConclusionsThis advance provides a glimpse into the host and parasite interplay by revealing a diversity of mechanisms that give rise to virulence genes in the soybean cyst nematode, including: tandem duplications containing over a fifth of the total gene count, virulence genes hitchhiking in transposons, and 107 horizontal gene transfers not reported in other plant parasitic nematodes thus far. Through extensive characterization of the H. glycines genome, we provide new insights into H. glycines biology and shed light onto the mystery underlying complex host-parasite interactions. This genome sequence is an important prerequisite to enable work towards generating new resistance or control measures against H. glycines.

Metabolic bone diseases (MBDs) are a diverse group of diseases, affecting the mass or structure of bones and leading to reduced bone quality. Parameters representing different aspects of bone health can be obtained from various magnetic resonance imaging (MRI) methods such as proton MR spectroscopy, as well as chemical shift encoding-based water-fat imaging, that have been frequently applied to study bone marrow in particular. Furthermore, T2* mapping and high-resolution trabecular bone imaging have been implemented to study bone microstructure. In addition, quantitative susceptibility mapping and ultrashort echo time imaging are used for trabecular and cortical bone assessment. This review offers an overview of technical aspects, as well as major clinical applications and derived main findings, for MRI-based assessment of bone quality in MBDs. It focuses on osteoporosis as the most common MBD. [ABSTRACT FROM AUTHOR]

Standard DXA measurements, including Fracture Risk Assessment Tool (FRAX) scores, have shown limitations in assessing fracture risk in Type 2 Diabetes (T2D), underscoring the need for novel biomarkers and suggesting that other pathomechanisms may drive diabetic bone fragility. MicroRNAs (miRNAs) are secreted into the circulation from cells of various tissues proportional to local disease severity and were recently found to be crucial to bone homeostasis and T2D. Here, we studied, if and which circulating miRNAs or combinations of miRNAs can discriminate best fracture status in a well-characterized study of diabetic bone disease and postmenopausal osteoporosis (n = 80 postmenopausal women). We then tested the most discriminative and most frequent miRNAs in vitro. Using miRNA-qPCR-arrays, we showed that 48 miRNAs can differentiate fracture status in T2D women and that several combinations of four miRNAs can discriminate diabetes-related fractures with high specificity and sensitivity (area under the receiver-operating characteristic curve values [AUCs], 0.92 to 0.96; 95% CI, 0.88 to 0.98). For the osteoporotic study arm, 23 miRNAs were fracture-indicative and potential combinations of four miRNAs showed AUCs from 0.97 to 1.00 (95% CI, 0.93 to 1.00). Because a role in bone homeostasis for those miRNAs that were most discriminative and most present among all miRNA combinations had not been described, we performed in vitro functional studies in human adipose tissue-derived mesenchymal stem cells to investigate the effect of miR-550a-5p, miR-188-3p, and miR-382-3p on osteogenesis, adipogenesis, and cell proliferation. We found that miR-382-3p significantly enhanced osteogenic differentiation (p

Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) method for the assessment of cerebral blood flow (CBF). This review summarizes recent ASL-based investigations in adult and pediatric patients with migraine with aura, migraine without aura, and chronic migraine. A systematic search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted within PubMed and reference sections of articles identified from April 2014 to November 2022. Out of 236 initial articles, 20 remained after filtering, encompassing data from 1155 subjects in total. Cross-sectional studies in adults showed inconsistent results, while longitudinal studies demonstrated that cerebral perfusion changes over the migraine cycle can be tracked using ASL. The most consistent findings were observed in ictal states among pediatric migraine patients, where studies showed hypoperfusion matching aura symptoms during early imaging followed by hyperperfusion. Overall, ASL is a useful but currently underutilized modality for evaluating cerebral perfusion in patients with migraine. The generalizability of results is currently limited by heterogeneities regarding study design and documentation of clinical variables (e.g., relation of attacks to scanning timepoint, migraine subtypes). Future MRI studies should consider augmenting imaging protocols with ASL to further elucidate perfusion dynamics in migraine. [ABSTRACT FROM AUTHOR]

Plant-parasitic nematodes constrain global food security. During parasitism, they secrete effectors into the host plant from two types of pharyngeal gland cells. These effectors elicit profound changes in host biology to suppress immunity and establish a unique feeding organ from which the nematode draws nutrition. Despite the importance of effectors in nematode parasitism, there has been no comprehensive identification and characterisation of the effector repertoire of any plant-parasitic nematode. To address this, we advance techniques for gland cell isolation and transcriptional analysis to define a stringent annotation of putative effectors for the cyst nematode Heterodera schachtii at three key life-stages. We define 717 effector gene loci: 269 "known" high-confidence homologs of plant-parasitic nematode effectors, and 448 "novel" effectors with high gland cell expression. In doing so we define the most comprehensive "effectorome" of a plant-parasitic nematode to date. Using this effector definition, we provide the first systems-level understanding of the origin, deployment and evolution of a plant-parasitic nematode effectorome. The robust identification of the effector repertoire of a plant-parasitic nematode will underpin our understanding of nematode pathology, and hence, inform strategies for crop protection. Author summary: Pathogenic organisms deliver so called "effectors", typically proteins, into their host to alter cell structure and function. Identifying and characterising the repertoire of effector-encoding genes is requisite to understanding infection. Here we advance methods and understanding, in combination with an extensive literature survey, to define a stringent annotation of putative effectors for the plant-parasitic cyst nematode, Heterodera schachtii. Using this effector definition, we provide the first systems-level understanding of the origin, deployment, and evolution of a plant-parasitic nematode effectorome. Given that plant-parasitic nematodes are major, and in some cases dominant, threats to global food security, it is widely cited that understanding how they infect their host (i.e. effectors) will deliver routes to alleviate their threat to agriculture. [ABSTRACT FROM AUTHOR]

Manipulating dielectric properties of polydimethylsiloxane (PDMS) is an important consideration for flexible, low-loss device design. This paper presents a method for reducing dielectric loss (tan δ) by forming PDMS composites loaded with various concentrations of either alumina (Al2O3) or polytetrafluoroethylene (PTFE) particles. The structural, mechanical, and electrical properties of the composites are investigated. Theoretical mixing models were used to predict the relative permittivity (εr) of PDMS composites, and good similarity with the measured εr was observed. The incorporation of either low dielectric loss filler in the PDMS matrix (up to 50 wt. % filler loading) is shown to reduce the dielectric loss while maintaining the flexibility of the host matrix. The fillers can also control the permittivity of the composite, either increasing or decreasing relative permittivity from that of PDMS. Interestingly, a strain of ∼500% can be applied to 15 wt. % PDMS/PTFE composites, compared with ∼350% for pure PDMS.

BackgroundAnterior cruciate ligaments (ACL) injuries represent a major risk factor for early osteoarthritis (OA).PurposeTo evaluate the prevalence and 4-year progression of knee OA measured with 3T MR-imaging in individuals with ruptured, reconstructed or normal ACL and to assess the impact of thigh muscle characteristics.MethodsA total of 54 knees (23/54 male, 31/54 female) were recruited from the Osteoarthritis Initiative (OAI). At baseline, 15/54 subjects had prevalent ACL ruptures and 15/54 subjects had prevalent ACL reconstruction (24/54 normal ACL). Western Ontario and McMasters Universities Arthritis Index (WOMAC) scores, Physical Activity Scores of the Elderly (PASE) and thigh muscle characteristics including strength, fat infiltration (Goutallier score) and thigh muscle cross-sectional area (CSA) MR measurements were obtained at baseline. Whole-organ MR-imaging Scores (WORMS) were obtained at baseline and at a 4-year follow-up time-point. Multivariate regression models, adjusting for covariates (age, gender, body mass index), were used for statistical analysis.ResultsAt baseline, subjects with prevalent ACL ruptures had worse WORMS total scores (mean±SEM, 44.1±3.5) than subjects with ACL reconstruction (30.8±4.0; P = 0.015) and worse than subjects with normal ACL (21.3±3.0; P

We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R2. The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R2: 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R2: 0.61 ± 0.101) (p < 10-4). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.