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The whale shark (Rhincodon typus) is an iconic and endangered species with a broad distribution spanning warm-temperate and tropical oceans. Effective conservation management of the species requires an understanding of the degree of genetic connectivity among populations, which is hampered by the need for sampling that involves invasive techniques. Here, the feasibility of minimally-invasive sampling was explored by isolating and sequencing whale shark DNA from a commensal or possibly parasitic copepod, Pandarus rhincodonicus that occurs on the skin of the host. We successfully recovered mitochondrial control region DNA sequences (~1,000 bp) of the host via DNA extraction and polymerase chain reaction from whole copepod specimens. DNA sequences obtained from multiple copepods collected from the same shark exhibited 100% sequence similarity, suggesting a persistent association of copepods with individual hosts. Newly-generated mitochondrial haplotypes of whale shark hosts derived from the copepods were included in an analysis of the genetic structure of the global population of whale sharks (644 sequences; 136 haplotypes). Our results supported those of previous studies and suggested limited genetic structuring across most of the species range, but the presence of a genetically unique and potentially isolated population in the Atlantic Ocean. Furthermore, we recovered the mitogenome and nuclear ribosomal genes of a whale shark using a shotgun sequencing approach on copepod tissue. The recovered mitogenome is the third mitogenome reported for the species and the first from the Mozambique population. Our invertebrate DNA (iDNA) approach could be used to better understand the population structure of whale sharks, particularly in the Atlantic Ocean, and also for genetic analyses of other elasmobranchs parasitized by pandarid copepods.

AMG 256 is a bi-specific, heteroimmunoglobulin molecule with an anti-PD-1 antibody domain and a single IL-21 mutein domain on the C-terminus. Nonclinical studies in cynomolgus monkeys revealed that AMG 256 administration led to the development of immunogenicity-mediated responses and indicated that the IL-21 mutein domain of AMG 256 could enhance the anti-drug antibody response directed toward the monoclonal antibody domain. Anti-AMG 256 IgE were also observed in cynomolgus monkeys. A first-in-human (FIH) study in patients with advanced solid tumors was designed with these risks in mind. AMG 256 elicited ADA in 28 of 33 subjects (84.8%). However, ADA responses were only robust and exposure-impacting at the 2 lowest doses. At mid to high doses, ADA responses remained low magnitude and all subjects maintained exposure, despite most subjects developing ADA. Limited drug-specific IgE were also observed during the FIH study. ADA responses were not associated with any type of adverse event. The AMG 256 program represents a unique case where nonclinical studies informed on the risk of immunogenicity in humans, due to the IL-21-driven nature of the response.

Panels of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the population genetic analysis of Plasmodium falciparum in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries, characterised by moderate-to-high transmission, where multiclonal infections are prevalent. For SNP barcodes it is generally recommended that the SNPs chosen i) are biallelic, ii) have a minor allele frequency greater than 0.10, and iii) are independently segregating, to minimise bias in the analysis of genetic diversity and population structure. Further, to be standardised and used in many population genetic studies, these barcodes should maintain characteristics i) to iii) across various iv) geographies and v) time points. Using haplotypes generated from the MalariaGEN P. falciparum Community Project version six database, we investigated the ability of these two barcodes to fulfil these criteria in moderate-to-high transmission African populations in 25 sites across 10 countries. Predominantly clinical infections were analysed, with 52.3% found to be multiclonal, generating high proportions of mixed-allele calls (MACs) per isolate thereby impeding haplotype construction. Of the 24- and 96-SNPs, loci were removed if they were not biallelic and had low minor allele frequencies in all study populations, resulting in 20- and 75-SNP barcodes respectively for downstream population genetics analysis. Both SNP barcodes had low expected heterozygosity estimates in these African settings and consequently biased analyses of similarity. Both minor and major allele frequencies were temporally unstable. These SNP barcodes were also shown to identify weak genetic differentiation across large geographic distances based on Mantel Test and DAPC. These results demonstrate that these SNP barcodes are vulnerable to ascertainment bias and as such cannot be used as a standardised approach for malaria surveillance in moderate-to-high transmission areas in Africa, where the greatest genomic diversity of P. falciparum exists at local, regional and country levels.

Object detection models have become the current tool of choice for plant disease detection in precision agriculture. Most existing research improved the performance by ameliorating networks and optimizing the loss function. However, because of the vast influence of data annotation quality and the cost of annotation, the data-centric part of a project also needs more investigation. We should further consider the relationship between data annotation strategies, annotation quality, and the model’s performance. In this paper, a systematic strategy with four annotation strategies for plant disease detection is proposed: local, semi-global, global, and symptom-adaptive annotation. Labels with different annotation strategies will result in distinct models’ performance, and their contrasts are remarkable. An interpretability study of the annotation strategy is conducted by using class activation maps. In addition, we define five types of inconsistencies in the annotation process and investigate the severity of the impact of inconsistent labels on model’s performance. Finally, we discuss the problem of label inconsistency during data augmentation. Overall, this data-centric quantitative analysis helps us to understand the significance of annotation strategies, which provides practitioners a way to obtain higher performance and reduce annotation costs on plant disease detection. Our work encourages researchers to pay more attention to annotation consistency and the essential issues of annotation strategy. The code will be released at: https://github.com/JiuqingDong/PlantDiseaseDetection_Yolov5 .

Recognizing plant diseases is a major challenge in agriculture, and recent works based on deep learning have shown high efficiency in addressing problems directly related to this area. Nonetheless, weak performance has been observed when a model trained on a particular dataset is evaluated in new greenhouse environments. Therefore, in this work, we take a step towards these issues and present a strategy to improve model accuracy by applying techniques that can help refine the model’s generalization capability to deal with complex changes in new greenhouse environments. We propose a paradigm called “control to target classes.” The core of our approach is to train and validate a deep learning-based detector using target and control classes on images collected in various greenhouses. Then, we apply the generated features for testing the inference of the system on data from new greenhouse conditions where the goal is to detect target classes exclusively. Therefore, by having explicit control over inter- and intra-class variations, our model can distinguish data variations that make the system more robust when applied to new scenarios. Experiments demonstrate the effectiveness and efficiency of the proposed approach on our extended tomato plant diseases dataset with 14 classes, from which 5 are target classes and the rest are control classes. Our detector achieves a recognition rate of target classes of 93.37% mean average precision on the inference dataset. Finally, we believe that our study offers valuable guidelines for researchers working in plant disease recognition with complex input data.

Interstitial solutes can be removed by various overlapping clearance systems, including blood–brain barrier (BBB) transport and glymphatic clearance. Recently, focused ultrasound (FUS)-induced BBB disruption (BBBD) has been applied to visualize glymphatic transport. Despite evidence that FUS–BBBD might facilitate glymphatic transport, the nature of fluid movement within the sonication region is yet to be determined. In this study, we sought to determine whether FUS–BBBD may facilitate the local movement of water molecules. Two different FUS conditions (0.60–0.65 MPa and 0.75–0.80 MPa) were used to induce BBBD in the caudate-putamen and thalamus regions of healthy Sprague–Dawley rats. The water diffusion caused by FUS–BBBD was analyzed using the apparent diffusion coefficient (ADC), axial diffusivity, radial diffusivity (RD), and fractional anisotropy, obtained at 5 min, 24 and 48 h, as well as the water channel expression of aquaporin-4 (AQP-4) immunostaining at 48 h after FUS-induced BBBD. In addition, hematoxylin and eosin histopathology and Fluoro-Jade C (FJC) immunostaining were performed to analyze brain damage. The signal changes in ADC and RD in the sonication groups showed significant and transient reduction at 5 min, with subsequent increases at 24 and 48 h after FUS-induced BBBD. When we applied higher sonication conditions, the ADC and RD showed enhancement until 48 h, and became comparable to contralateral values at 72 h. AQP-4 expression was upregulated after FUS-induced BBBD in both sonication conditions at 48 h. The results of this study provide preliminary evidence on how mechanical forces from FUS alter water dynamics through diffusion tensor imaging (DTI) measures and AQP4 expression.

Body composition (fat, skeletal muscle and bone mass) is an important determinant of overall health and risk of endocrine disorders such as type 2 diabetes and osteoporosis. Although diet and physical activity are strongly implicated, body composition is also heritable. We conducted a discovery genome-wide association study on 31 phenotypes from the three-compartment body composition model (fat, lean and bone mass) in a set of 4 386 individuals (n = 2 109 males, n = 2 294 females) from the UK Biobank pilot imaging enhancement program that underwent a dual energy X-ray absorptiometry (DXA) scan for assessment of body composition and genetic screening. From 6 137 607 imputed single nucleotide polymorphisms (SNPs) we identified 17 body composition loci (P

MRI-guided focused ultrasound (MRgFUS) combined with microbubbles (MBs) is a promising technology that can facilitate drug delivery through a temporarily disrupted blood-brain barrier (BBB) and induce the down-regulation of P-glycoprotein (P-gp) expression on the blood vessels. Despite the increasing evidence regarding the down-regulation of P-gp expression after MRgFUS BBB disruption (BBBD), its underlying molecular events remain unclear. The aim of this study was to evaluate the underlying mechanism of FUS BBBD-mediated P-gp down-regulation. While our results showed down-regulation of P-gp at 24 h post-BBBD in transcriptional and translational levels, restoration to the normal expression appeared at different time points for transcriptional (72 h) and translational (120 h) levels. In addition, the signaling molecule, JNK, was significantly activated in the cerebral blood vessels at 24 h post-BBBD. Although P-gp levels were significantly decreased, the expression levels of proteins involved in the integrity of blood vessels, such as Glut1, ZO-1 and occludin, were not decreased at 24 h post-BBBD. Our study suggests that the JNK signaling pathway is involved in the regulation of FUS-induced P-gp expression, without affecting vessel integrity, and a detailed regulatory mechanism can provide the basis for clinical application of FUS to the treatment of neurological disease.

The rise of palm oil as the world's most consumed vegetable oil has coincided with exponential growth in palm oil research activity. Bibliometric analysis of research outputs reveals a distinct imbalance in the type of research being undertaken, notably a disproportionate focus on biofuel and engineering topics. Recognizing the expansion of oil palm agriculture across the tropics and the increasing awareness of environmental, social, and economic impacts, we seek to reorientate the existing research agenda toward one that addresses the most fundamental and urgent questions defined by the palm oil stakeholder community. Following consultation with 659 stakeholders from 38 countries, including palm oil growers, government agencies, non-governmental organizations, and researchers, the highest priority research questions were identified within 13 themes. The resulting 279 questions, including 26 ranked as top priority, reveal a diversity of environmental and social research challenges facing the industry, ranging from the ecological and ecosystem impacts of production, to the livelihoods of plantation workers and smallholder communities. Analysis of the knowledge type produced from these questions underscores a clear need for fundamental science programmes, and studies that involve the consultation of non-academic stakeholders to develop “transformative” solutions to the oil palm sector. Stakeholders were most aligned in their choice of priority questions across the themes of policy and certification related themes, and differed the most in environmental feedback, technology and smallholder related themes. Our recommendations include improved regional academic leadership and coordination, greater engagement with private and public stakeholders in Africa, and Central and South America, and enhanced collaborative efforts with researchers in the major consuming countries of India and China.