Clinical activity and safety of sintilimab, bevacizumab, and TMZ in patients with recurrent glioblastoma.

PURPOSE: There are limited and no standard therapies for recurrent glioblastoma. We herein report the antitumour activity and safety of sintilimab, bevacizumab and temozolomide (TMZ) in recurrent glioblastoma. METHODS: We retrospectively analysed eight patients with recurrent glioblastoma treated with sintilimab (200 mg) every three weeks + bevacizumab (10 mg/kg) every three weeks + TMZ (200 mg/m²orally) (5 days orally every 28 days for a total of four weeks). The primary objective was investigator-assessed median progression-free survival(mPFS). Secondary objectives were to assess the 6-month PFS, objective response rate (ORR) and duration of response (DOR) accroding to RANO criteria. RESULTS: The mPFS time for 8 patients was 3.340 months (95% CI: 2.217-4.463), The longest PFS was close to 9 months. Five patients were assessed to have achieved partial response (PR), with an overall remission rate of 62.5%, Four patients experienced a change in tumour volume at the best response time of greater than 60% shrinkage from baseline, and one patient remained progression free upon review, with a DOR of more than 6.57 months. The 6-month PFS was 25% (95% CI: 5.0-55.0%). Three patients had a treatment-related adverse events, though no grade 4 or 5 adverse events occurred. CONCLUSION: In this small retrospective study, the combination regimen of sintilimab, bevacizumab and TMZ showed promising antitumour activity in treatment of recurrent glioblastoma, with a good objective remission rate.

Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas.

BACKGROUND: 1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI. METHODS: This retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant. RESULTS: The radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist. CONCLUSIONS: Our results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.

Natural Infection of Murraya paniculata and Murraya sumatrana with CLas in Java.

The phloem-limited bacterium, 'Candidatus Liberibacter asiaticus' (CLas), is the putative causal pathogen of the severe Asiatic form of huanglongbing (citrus greening) and is most commonly transmitted by the Asiatic citrus psyllid (ACP), Diaphorina citri. CLas severely affects many Citrus species and hybrids and has been recorded in the Citrus relative, orange jasmine, Murraya paniculata (L.) Jack (syn. M. exotica L.). In this study, 13 accessions of three Murraya species (M. paniculata, M. sumatrana Roxb. and M. lucida (G.Forst.) Mabb,) and the Papuan form of a putative hybrid (M. omphalocarpa Hayata) were identified morphologically and molecularly based on sequence identity of the matK-5'trnK region of the chloroplast genome, and infection on these plants under field conditions was determined by PCR and qPCR on 2-4 occasions over 14 months. CLas was repeatedly detected in leaflet midribs by PCR and qPCR on four and three accessions of M. paniculata and M. sumatrana, respectively. It was not detected in leaflet midribs of single accessions of M. lucida and M. omphalocarpa. The species identification of the CLas-positive accessions was further confirmed using all the molecular taxonomic markers consisting of the six fragments of the maternally inherited chloroplast genome and part of the nuclear-encoded ITS region. The results indicated that natural infection of M. paniculata and M. sumatrana with CLas can occur in Java. This is the first demonstration of the natural infection of M. sumatrana with CLas. Further studies are required to determine if infections persist in the absence of D. citri.

Optical coherence tomography for in vivo longitudinal monitoring of artificial dermal scaffold.

OBJECTIVES: Artificial dermal scaffold (ADS) has undergone rapid development and been increasingly used for treating skin wound in clinics due to its good biocompatibility, controllable degradation, and low risk of disease infection. To obtain good treatment efficacy, ADS needs to be monitored longitudinally during the treatment process. For example, scaffold-tissue fit, cell in-growth, vascular regeneration, and scaffold degradation are the key properties to be inspected. However, to date, there are no effective, real-time, and noninvasive techniques to meet the requirement of the scaffold monitoring above. MATERIALS AND METHODS: In this study, we propose to use optical coherence tomography (OCT) to monitor ADS in vivo through three-dimensional imaging. A swept source OCT system with a handheld probe was developed for in vivo skin imaging. Moreover, a cell in-growth, vascular regeneration, and scaffold degradation rate (IRDR) was defined with the volume reduction rate of the scaffold's collagen sponge layer. To measure the IRDR, a semiautomatic image segmentation algorithm was designed based on U-Net to segment the collagen sponge layer of the scaffold from OCT images. RESULTS: The results show that the scaffold-tissue fit can be clearly visualized under OCT imaging. The IRDR can be computed based on the volume of the segmented collagen sponge layer. It is observed that the IRDR appeared to a linear function of the time and in addition, the IRDR varied among different skin parts. CONCLUSION: Overall, it can be concluded that OCT has a good potential to monitor ADS in vivo. This can help guide the clinicians to control the treatment with ADS to improve the therapy.

Climate change and Australia's primary industries: factors hampering an effective and coordinated response.

Australia's primary production sector operates in one of the world's most variable climates with future climate change posing a challenge to its ongoing sustainability. Recognising this, Australia has invested in understanding climate change risks to primary production with a substantial amount of research produced. Recently, focus on this research space has broadened, with interests from the financial sector and expanded scopes of works from government and industry. These expanded needs require sector- and country-wide assessments to assist with the implementation of climate strategies. We considered the applicability of the current research body for these needs by reviewing 188 peer-reviewed studies that considered the quantitative impacts of climate change on Australia's primary industries. Our broad review includes cropping, livestock, horticulture, forestry and fisheries and biosecurity threats. This is the first such review for Australia, and no other similar country-wide review was found. We reviewed the studies through three lenses, industry diversity, geographic coverage and study comparability. Our results show that all three areas are lacking for sector- and country-wide assessments. Industry diversity was skewed towards cropping and biosecurity threats (64% of all studies) with wheat in particular a major focus (25% of all studies). Geographic coverage at a state level appeared to be evenly distributed across the country; however, when considered in conjunction with industry focus, gaps emerged. Study comparability was found to be very limited due to the use of different historical baseline periods and different impact models. We make several recommendations to assist with future research directions, being (1) co-development of a standard set of method guidelines for impact assessments, (2) filling industry and geographic knowledge gaps, and (3) improving transparency in study method descriptions. Uptake of these recommendations will improve study application and transparency enabling and enhancing responses to climate change in Australia's primary industries.

Development of a handheld compression optical coherence elastography probe with a disposable stress sensor.

Optical coherence elastography (OCE) is a functional extension of optical coherence tomography (OCT). OCE measures a sample's deformation under force stimuli. Compression is often used to generate the force stimuli in OCE. In this Letter, we report the development of a handheld quantitative compression OCE probe with a novel stress senor, dedicated to measuring the force. The stress sensor consists of a circular glass window and a metal ring which are connected with polyurethane spokes. This sensor is mounted on the tip of the OCT sample arm as an imaging window, so that the force applied to the sample through the window can be measured by detecting the window displacement from the OCT image. The force-displacement function was first developed through simulation on COMSOL Multiphysics and eventually calibrated experimentally. A phase-sensitive OCT technique was employed to measure both the window displacement and the sample deformation. The performance of an OCE probe with this stress sensor was evaluated on a two-layer phantom. The results show that it is extremely capable of measuring the sample Young's modulus. Finally, we successfully measured the elasticity of the human fingertip, indicating a good potential of this OCE probe for in vivo elastogram measurement on human skin.

Dual-side view optical coherence tomography for thickness measurement on opaque materials.

Optical coherence tomography (OCT), as an optical interferometric imaging technique, has found wide applications in various fields. In principle, OCT is well suited for imaging layered structures, and thus, one of the typical applications is thickness measurement. However, due to the limited imaging depth resulting from light attenuation, thickness measurement by OCT is limited to non-opaque materials. In this study, we developed a novel (to the best of our knowledge) dual-side view OCT (DSV-OCT) system for thickness measurement on opaque materials. The dual-side view was achieved on a conventional swept source OCT platform by creating two symmetrical sampling arms. This allows us to image both sides of the material simultaneously and produce the surface contours of the two sides in a single C scan. Finally, the thickness of the opaque material can be calculated from the two surface contours above. We demonstrated that our DSV-OCT technique can measure the thickness of opaque material with an accuracy of about 3 µm.

Extending axial focus of optical coherence tomography using parallel multiple aperture synthesis.

Compromising the inherent trade-off between transverse resolution and depth of focus (DOF) remains a long-standing issue in optical coherence tomography (OCT). In this work, we report a novel technique-parallel multiple aperture synthesis (pMAS) to simultaneously generate multiple optical apertures in an OCT sample arm by employing a two-surface coated mirror. In the proposed pMAS, the DOF is extended by a factor of 16.49 without sacrificing the transverse resolution for proof-of-concept experiments when multiple distinctive apertures are digitally synthesized. The microparticles and tissue experiments demonstrate the feasibility of pMAS to address the fundamental problem of limited DOF in high-resolution OCT.

Depth-encoded synthetic aperture optical coherence tomography of biological tissues with extended focal depth.

Optical coherence tomography (OCT) has proven to be able to provide three-dimensional (3D) volumetric images of scattering biological tissues for in vivo medical diagnostics. Unlike conventional optical microscopy, its depth-resolving ability (axial resolution) is exclusively determined by the laser source and therefore invariant over the full imaging depth. In contrast, its transverse resolution is determined by the objective's numerical aperture and the wavelength which is only approximately maintained over twice the Rayleigh range. However, the prevailing laser sources for OCT allow image depths of more than 5 mm which is considerably longer than the Rayleigh range. This limits high transverse resolution imaging with OCT. Previously, we reported a novel method to extend the depth-of-focus (DOF) of OCT imaging in Mo et al.Opt. Express 21, 10048 (2013)]. The approach is to create three different optical apertures via pupil segmentation with an annular phase plate. These three optical apertures produce three OCT images from the same sample, which are encoded to different depth positions in a single OCT B-scan. This allows for correcting the defocus-induced curvature of wave front in the pupil so as to improve the focus. As a consequence, the three images originating from those three optical apertures can be used to reconstruct a new image with an extended DOF. In this study, we successfully applied this method for the first time to both an artificial phantom and biological tissues over a four times larger depth range. The results demonstrate a significant DOF improvement, paving the way for 3D high resolution OCT imaging beyond the conventional Rayleigh range.

Near-infrared Raman spectroscopy for assessing biochemical changes of cervical tissue associated with precarcinogenic transformation.

Raman spectroscopy measures the inelastically scattered light from tissue that is capable of identifying native tissue biochemical constituents and their changes associated with disease transformation. This study aims to characterize the Raman spectroscopic properties of cervical tissue associated with the multi-stage progression of cervical precarcinogenic sequence. A rapid-acquisition fiber-optic near-infrared (NIR) Raman diagnostic system was employed for tissue Raman spectral measurements at 785 nm excitation. A total of 68 Raman spectra (23 benign, 29 low-grade squamous intraepithelial lesions (LSIL) and 16 high grade squamous intraepithelial lesions (HSIL)) were measured from 25 cervical tissue biopsy specimens, as confirmed by colposcopy-histopathology. The semi-quantitative biochemical modeling based on the major biochemicals (i.e., DNA, proteins (histone, collagen), lipid (triolein) and carbohydrates (glycogen)) in cervical tissue uncovers the stepwise accumulation of biomolecular changes associated with progressive cervical precarcinogenesis. Multi-class partial least squares-discriminant analysis (PLS-DA) together with leave-one tissue site-out, cross-validation yielded the diagnostic sensitivities of 95.7%, 82.8% and 81.3%; specificities of 100.0%, 92.3% and 88.5%,for discrimination among benign, LSIL and HSIL cervical tissues, respectively. This work suggests that the Raman spectral biomarkers have identified the potential to be used for monitoring the multi-stage cervical precarcinogenesis, forming the foundation of applying NIR Raman spectroscopy for the early diagnosis of cervical precancer in vivo at the molecular level.

Focus-extension by depth-encoded synthetic aperture in Optical Coherence Tomography.

We present a novel method to extend the depth-of-focus of Optical Coherence Tomography (OCT). OCT is an interferometric imaging technique that provides depth-resolved scattering information. The axial resolution in OCT is provided by the coherence gate and is invariant over the full image depth. The lateral resolution is determined by the beam parameters such as wavelength and numerical aperture. The Rayleigh range determines the depth range over which the lateral resolution can be maintained. The lateral resolution is often sacrificed to maintain relatively long Rayleigh range. In this study, we propose to use a depth-encoded synthetic aperture detection scheme to extend the depth range over which a sharp focus can be maintained beyond the Rayleigh range. An annular phase plate is inserted into the light path in the sample arm, which gives rise to three separate images in a single B-scan, corresponding to three different optical path length encoded apertures. These three images are coherently summed after phase-manipulation to reconstruct a new image with a lateral resolution that is maintained over a five times larger depth range.

Collecting optical coherence elastography depth profiles with a micromachined cantilever probe.

We present an experimental setup that combines optical coherence elastography depth sensing with atomic force microscope indentation. The instrument relies on a miniaturized cantilever probe that compresses a sample with a small footprint force and simultaneously collects an optical coherence tomography (OCT) depth profile underneath the indenting point. The deflection of the cantilever can be monitored via optical fiber interferometry with a resolution of 2 nm. The OCT readout then provides depth profiles of the subsurface layer deformation with 15 nm resolution and depth range of a few millimeters.

Evaluation of a commercial Bacillus thuringiensis var. israelensis formulation for the control of chironomid midge larvae (Diptera: Chironomidae) in establishing rice crops in south-eastern Australia.

A commercial formulation of Bacillus thuringiensis var. israelensis (B.t.i.) was evaluated for its potential to control chironomid midge larvae in newly sown rice crops in south-eastern Australia. Two replicated small-plot field trials were conducted using product application rates of 0.5-6 kg/ha. In trial 1 application rates between 2 and 6 kg product/ha all significantly (P<0.05) reduced populations of target Chironominae/Orthocladiinae by between 71% and 93% over the 19 day post-treatment monitoring period. Trial 2 was conducted using lower application rates (0.5-2 kg product/ha) and only the 2 kg product/ha rate significantly (P<0.05) reduced numbers of the target group (81% reduction) despite lower application rates resulting in target group suppression of 38-62%. Identification of larvae to species level from selected samples indicated that populations of Chironomus tepperi, the principal pest species that attacks the roots of rice seedlings, were reduced at all application rates; elimination of C. tepperi was achieved in trial 1 at an application rate of 2 kg/ha. Consistent with other studies, non-target Tanypodinae were not adversely affected by B.t.i., and in some treatments populations of Tanypodinae exceeded control levels by up to 73%. In the first trial, which was conducted under relatively high pest pressure, plant establishment was significantly (P<0.05) increased (120-157%) by Vectobac® WDG application rates of 2-6 kg/ha. No significant increase in plant establishment relative to the controls was identified in the second trial, when pest pressure was substantially lower and minimal damage occurred in the control bays. Overall, our results demonstrate that B.t.i. may be an economically viable alternative to broad-spectrum synthetic pesticides for the control of phytophagous midge larvae in establishing rice crops where members of the Chironominae, the group most susceptible to B.t.i., are the principal species of concern. The high specificity of B.t.i. for nematoceran Diptera should lead to reduced impacts on non-target organisms.

Axial super-resolution optical coherence tomography via complex-valued network.

Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric imaging technique that can provide high-resolution cross-sectional images of biological tissues. OCT's key strength is its depth resolving capability which remains invariant along the imaging depth and is determined by the axial resolution. The axial resolution is inversely proportional to the bandwidth of the OCT light source. Thus, the use of broadband light sources can effectively improve the axial resolution and however leads to an increased cost. In recent years, real-valued deep learning technique has been introduced to obtain super-resolution optical imaging. In this study, we proposed a complex-valued super-resolution network (CVSR-Net) to achieve an axial super-resolution for OCT by fully utilizing the amplitude and phase of OCT signal. The method was evaluated on three OCT datasets. The results show that the CVSR-Net outperforms its real-valued counterpart with a better depth resolving capability. Furthermore, comparisons were made between our network, six prevailing real-valued networks and their complex-valued counterparts. The results demonstrate that the complex-valued network exhibited a better super-resolution performance than its real-valued counterpart and our proposed CVSR-Net achieved the best performance. In addition, the CVSR-Net was tested on out-of-distribution domain datasets and its super-resolution performance was well maintained as compared to that on source domain datasets, indicating a good generalization capability.

Multiscale denoising generative adversarial network for speckle reduction in optical coherence tomography images.

Purpose: Optical coherence tomography (OCT) is a noninvasive, high-resolution imaging modality capable of providing both cross-sectional and three-dimensional images of tissue microstructures. Owing to its low-coherence interferometry nature, however, OCT inevitably suffers from speckles, which diminish image quality and mitigate the precise disease diagnoses, and therefore, despeckling mechanisms are highly desired to alleviate the influences of speckles on OCT images. Approach: We propose a multiscale denoising generative adversarial network (MDGAN) for speckle reductions in OCT images. A cascade multiscale module is adopted as MDGAN basic block first to raise the network learning capability and take advantage of the multiscale context, and then a spatial attention mechanism is proposed to refine the denoised images. For enormous feature learning in OCT images, a deep back-projection layer is finally introduced to alternatively upscale and downscale the features map of MDGAN. Results: Experiments with two different OCT image datasets are conducted to verify the effectiveness of the proposed MDGAN scheme. Results compared those of the state-of-the-art existing methods show that MDGAN is able to improve both peak-single-to-noise ratio and signal-to-noise ratio by 3 dB at most, with its structural similarity index measurement and contrast-to-noise ratio being 1.4% and 1.3% lower than those of the best existing methods. Conclusions: Results demonstrate that MDGAN is effective and robust for OCT image speckle reductions and outperforms the best state-of-the-art denoising methods in different cases. It could help alleviate the influence of speckles in OCT images and improve OCT imaging-based diagnosis.

Loss-balanced parallel decoding network for retinal fluid segmentation in OCT.

As a leading cause of blindness worldwide, macular edema (ME) is mainly determined by sub-retinal fluid (SRF), intraretinal fluid (IRF), and pigment epithelial detachment (PED) accumulation, and therefore, the characterization of SRF, IRF, and PED, which is also known as ME segmentation, has become a crucial issue in ophthalmology. Due to the subjective and time-consuming nature of ME segmentation in retinal optical coherence tomography (OCT) images, automatic computer-aided systems are highly desired in clinical practice. This paper proposes a novel loss-balanced parallel decoding network, namely PadNet, for ME segmentation. Specifically, PadNet mainly consists of an encoder and three parallel decoder modules, which serve as segmentation, contour, and diffusion branches, and they are employed to extract the ME's characteristics, the contour area features, and to expand the ME area from the center to edge, respectively. A new loss-balanced joint-loss function with three components corresponding to each of the three parallel decoding branches is also devised for training. Experiments are conducted with three public datasets to verify the effectiveness of PadNet, and the performances of PadNet are compared with those of five state-of-the-art methods. Results show that PadNet improves ME segmentation accuracy by 8.1%, 11.1%, 0.6%, 1.4% and 8.3%, as compared with UNet, sASPP, MsTGANet, YNet, RetiFluidNet, respectively, which convincingly demonstrates that the proposed PadNet is robust and effective in ME segmentation in different cases.

Self-supervised Blind2Unblind deep learning scheme for OCT speckle reductions.

As a low-coherence interferometry-based imaging modality, optical coherence tomography (OCT) inevitably suffers from the influence of speckles originating from multiply scattered photons. Speckles hide tissue microstructures and degrade the accuracy of disease diagnoses, which thus hinder OCT clinical applications. Various methods have been proposed to address such an issue, yet they suffer either from the heavy computational load, or the lack of high-quality clean images prior, or both. In this paper, a novel self-supervised deep learning scheme, namely, Blind2Unblind network with refinement strategy (B2Unet), is proposed for OCT speckle reduction with a single noisy image only. Specifically, the overall B2Unet network architecture is presented first, and then, a global-aware mask mapper together with a loss function are devised to improve image perception and optimize sampled mask mapper blind spots, respectively. To make the blind spots visible to B2Unet, a new re-visible loss is also designed, and its convergence is discussed with the speckle properties being considered. Extensive experiments with different OCT image datasets are finally conducted to compare B2Unet with those state-of-the-art existing methods. Both qualitative and quantitative results convincingly demonstrate that B2Unet outperforms the state-of-the-art model-based and fully supervised deep-learning methods, and it is robust and capable of effectively suppressing speckles while preserving the important tissue micro-structures in OCT images in different cases.

Continent-wide evidence that landscape context can mediate the effects of local habitats on in-field abundance of pests and natural enemies.

Landscape-scale factors known to influence in-field abundance of pest herbivores and their natural enemies, but little is known about effects that operate through the shorter-range influences exerted by habitats immediately adjacent to crop fields.This study first compared the abundance of brassica insect pests and their natural enemy arthropods in 24 spatially independent brassica vegetable fields across southern Australia. An 'edge effect' index was used to compare the abundance of each taxon in the field center with abundance in areas of the crop adjacent to differing habitats. Then, three landscape properties: landscape composition, edge density, and connectivity of diverse crop and non-crop habitats were analyzed at five scales up to 5 km from these focal field centers to assess longer-range influences on arthropod abundances in field centers and on the edge effects.Edge effect of adjacent woody vegetation promoted ladybirds and reduced diamondback moth and whiteflies. Conversely, the presence of crops and pastures immediately adjacent to focal crop fields reduced whiteflies and aphids but with no effect on natural enemies.Effect of landscape composition and connectivity on arthropod abundance at field center found promotion of aphids (cabbage aphid and green peach aphid) by woodland in the landscape.Effect of landscape properties on the edge effects of adjacent habitats was contrasting; strengthened (landscape composition and edge density on edge effect of crops, pasture and woody vegetation in reducing diamondback moth and whiteflies) as well as weakened (edge density and landscape connectivity on edge effect of crops, pasture and woody vegetation in reducing diamondback moth on diamondback moth, whiteflies and aphids, and promoting ladybirds). Synthesis and applications: Findings of this geographically extensive study help define the level of pest risk associated with sites as well as suggest potential interventions such as establishment or restorations of woody vegetation adjacent to crop fields that could reduce risk.

High speed miniature motorized endoscopic probe for optical frequency domain imaging.

We present a miniature motorized endoscopic probe for Optical Coherence Tomography with an outer diameter of 1.65 mm and a rotation speed of 3,000-12,500 rpm. This is the smallest motorized high speed OCT probe to our knowledge. The probe has a motorized distal end which provides a significant advantage over proximally driven probes since it does not require a drive shaft to transfer the rotational torque to the distal end of the probe and functions without a fiber rotary junction. The probe has a focal Full Width at Half Maximum of 9.6 µm and a working distance of 0.47 mm. We analyzed the non uniform rotation distortion and found a location fluctuation of only 1.87° in repeated measurements of the same object. The probe was integrated in a high-speed Optical Frequency Domain Imaging setup at 1310 nm to acquire images from ex vivo pig lung tissue through the working channel of a human bronchoscope.

Topical and dietary toxicity of emamectin benzoate, chlorantraniliprole, cyantraniliprole and indoxacarb to larvae of the common armyworm Mythimna convecta (Lepidoptera: Noctuidae).

BACKGROUND: The common armyworm Mythimna convecta is an important pest of pastures and graminaceous crops in Australia, but materials currently registered for its control are limited to broad-spectrum compounds incompatible with integrated pest management (IPM) systems. In this study we assessed the response of M. convecta larvae to four alternative compounds using topical and dietary bioassays. RESULTS: Emamectin benzoate [LC50 (lethal concentration for 50% of insects tested) values 2.69 µg mL-1 topical, 0.017 µg active ingredient (AI) g-1 dietary] and chlorantraniliprole (LC50 values 4.87 µg mL-1  topical, 0.080 µg AI g-1 dietary) were significantly more active than either indoxacarb or cyantraniliprole. Our results showed strong parallels with data on the more extensively studied Australian strains of Helicoverpa armigera, with the most notable differences being the higher contact toxicity of emamectin benzoate to M. convecta and the lower acute dietary activity of formulated cyantraniliprole to this species, which was linked to feeding deterrence. Cyantraniliprole at dietary concentrations of ≥0.02 µg AI g-1 significantly reduced the weight of surviving larvae and frass production (an indirect measure of food consumption) over the seven-day exposure period. There was also some evidence of chlorantraniliprole deterring larval feeding, although to a much more limited extent. CONCLUSIONS: Both emamectin benzoate and chlorantraniliprole are suitable for use against M. convecta. The decision as to which of these compounds should be prioritized for further development should be based on their potential effects on beneficial species once their optimal field rates have been determined.