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Diet-regulated transcriptional plasticity of plant parasites in plant–mutualist environments
Get PDFCrop pathogens often lack exclusive access to their host and must interact with plants
concurrently engaged with numerous other symbionts. Here, we demonstrate that the
colonization of hosts by plant–mutualistic mycorrhizal fungi can indirectly induce transcriptional responses of a major plant parasite, the nematode Globodera pallida, via a
modified host resource profile. A shift in the resource profile of the root, where the
parasite feeds, is perceived and responded to by the parasite through transcriptional
changes, potentially to optimize resource intake. Specifically, G. pallida react to reduced
host-photosynthate influx due to concurrent mycorrhizal-host symbiosis by upregulating the expression of a sugar transporter (SWEET3) in the nematode intestine. We
identify this gene’s role in parasite growth and development, regulated by the putative
diet-responsive transcription factor Gp-HBL1. Overall, our data unveil a mechanism by
which a parasitic animal responds to fluctuations in host plant quality that is induced
by a plant–mutualistic fungus, to enhance parasitism and reproduction
“From that moment, everything has changed”: The experience of women with anorexia nervosa receiving a diagnosis of autism
Get PDFObjective
Autism and eating disorders (ED) frequently co-occur, particularly in women. Autistic individuals are often undiagnosed when they present to mental health services and many receive their autism diagnosis during or after ED treatment. This study sought to understand the experiences of autistic women with co-occurring anorexia nervosa (AN) receiving an autism diagnosis.
Method
Secondary data analysis was conducted on 17 semi-structured interviews with autistic women with AN using reflexive thematic analysis. Participants had a diagnosis of autism, had current or past experience of AN, were female-identifying and aged 18 or above.
Results
Participants experienced missed opportunities for autism diagnosis along with misdiagnoses and misunderstandings from healthcare professionals. Participants tended to receive their diagnosis at the point of crisis and experienced being passed between autism and ED services. Receiving a diagnosis helped participants make sense of their experiences and take control of their lives but also brought feelings of shock and distress.
Conclusions
While autism diagnosis is often a positive experience for autistic women with AN, a range of emotions can be experienced. The findings highlight a need for better and earlier identification of autism among women with EDs, alongside appropriate post-diagnosis support and ED treatment that is adapted to autistic individuals' needs
Isotopic data reveal a localist Roman population in Late Roman Albintimilium, Liguria
Get PDFThis study investigates human diet and mobility to understand the socio-economic organisation of a Late Roman community in Liguria, a transitional region between Italy and Gaul, during the 3rd-5th century CE. By combining archaeological, historical, osteological, and isotopic data with novel Bayesian modelling of multi-isotope data (collagen δ13C, δ15N, bioapatite 87Sr/86Sr) from human and animal skeletal remains, as well as modern plant samples, we provide new insights into this hitherto under-researched region. Our findings suggest the community followed a C3-based diet, heavily reliant on plant resources and carbohydrates, supplemented by animal protein, likely from omnivorous pigs. This characteristically Roman diet contrasts with ancient written sources that claimed Ligurians had a “barbarian” diet and lifestyle.
We also identified significant sex-based dietary differences, with men consuming more animal-derived protein than women, reflecting traditional Graeco-Roman societal ideals.
Although the overall dietary pattern aligns with Roman norms, there is no isotopic evidence of long-distance migration or consumption of significant amounts of imported food. This indicates that the community may have been more localist, prioritising locally available resources over long-distance imports, which is unexpected given the prevalent idea of a large-scale interconnected food network within the Roman Empire
Software and computing for Run 3 of the ATLAS experiment at the LHC
Get PDFThe ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess its quality are described, along with the software tools used for data analysis itself. An outlook for the development of these projects towards Run 4 is also provided
An audio-based framework for anomaly detection in large-scale structural testing
Get PDFFastBlade is a research facility that tests large-scale composite and metal structures. To maximise its throughput by uninterrupted running of experiments, unmanned operation of the site is desired. One of its key enablers is anomaly detection, where microphones are used as a non-specific, affordable, and well-established sensing method. The dataset collected during the operation of the system consists of both normal and anomalous samples, which we need to classify. The problems associated with the dataset involve significant intraclass variability of the normal operation samples, as well as the scarcity of anomalous data, increasing the complexity of the classification problem. In this work, we evaluate the performance of several tools for time–frequency signal analysis, which are used to extract features from the original high-dimensional signal. We choose to apply the wavelet scattering transform (WST) due to its remarkable performance. Based on the findings from the literature review, we first rely on the reconstruction error of the processed WST images to detect anomalous samples. However, due to the nature of the dataset, both the convolutional autoencoder (CAE) and the principal component analysis (PCA) transform turn out to be unsuccessful. We then investigate the hidden layers of the CAE in search of features that can be used to separate normal and anomalous samples. Having identified the most suitable candidates, we discover that applying the normalised cross-correlation (NCC) to measure the similarity of the generic features generated and our dataset results in satisfactory separation. We train a number of classifiers and test the method on unseen data. The model’s accuracy is 99.58%, with a recall of 100% and 92% on normal and anomalous operation samples, respectively. The model’s accuracy and low latency prove the WST’s suitability for robust, real-time detection of different anomaly types. Therefore, the method can be deployed in systems with limited information about the critical assets and can be easily extrapolated to other setups
Pesticide safety behavior among vegetable farmers in Bangladesh: evaluating the role of market aggregation services
Get PDFPesticide use in Bangladesh is disproportionately high in vegetable farming compared to other crops like cereals, pulses, and cash crops. This study delves into the knowledge, attitudes, and practices regarding pesticide use among vegetable farmers, focusing on the impact of a digital aggregation service implemented by Digital Green. Based on interviews with 120 vegetable farmers in the LOOP aggregation scheme and 120 non-LOOP vegetable farmers this study indicates that the farmers using the aggregation service have a moderately higher level of food safety knowledge. LOOP farmers scored higher in pesticide safety knowledge (67.83 %) compared to non-LOOP farmers (55 %). Regarding pesticide safety attitudes, LOOP farmers scored 17.39 %, while non-LOOP farmers 4.17 %, reflecting a generally poor attitude toward pesticide application. Regarding practices, 65.55 % of LOOP farmers adhered to scientifically sound methods, compared to 43.10 % of non-LOOP farmers. Although participation in the LOOP program significantly influenced farmers’ pesticide-related knowledge, attitudes, and practices, this study still identifies the need for targeted interventions and training to improve food safety practices among both groups
High-Resolution Self-Assembly of Functional Materials and Microscale Devices via Selective Plasma Induced Surface Energy Programming
Get PDFCurrent technologies preclude effective and efficient self-assembly of heterogeneous arrangements of functional materials between 10−1 and 10−5 m. Consequently, their fabrication is dominated by methods of direct material manipulation, which struggle to meet the designers’ demands regarding resolution, material freedom, production time, and cost. A two-step, computer-controlled is presented, multi-material self-assembly technique that allows heterogenous patterns of several centimeters with features down to 12.5 µm in size. First, a micro plasma jet selectively programs the surface energy of a polydimethylsiloxane substrate through localized chemical functionalization. Second, polar fluids containing functional materials are simplistically introduced which then self-assemble according to the patterned regions of high surface energy over timescales of the order of seconds. In-process control enables both high-resolution patterning and high throughput. This approach is demonstrated to produce heterogenous patterns of materials with varying conductive, magnetic, and mechanical properties. These include magneto-mechanical films and flexible electronic devices with unprecedented processing times and economy for high-resolution patterns. This self-assembly approach can disrupt the current lithography/direct write paradigm that dominates micro/meso-fabrication, enabling the next generation of devices across a broad range of fields via a flexible, industrially scalable, and environmentally friendly manufacturing route
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