Identifying Rapid Glaucoma Progression Using Hemifield Rates of Progression.

PRCIS: Hemifield rates of progression are more sensitive to focal progression (or faster progression) than global rates. This can aid in tailoring management and treatment decisions. PURPOSE: To determine if the rate of progression (ROP) of each hemifield of the 24-2 visual field (VF) aids in the detection of rapidly progressing eyes. METHODS: In this retrospective longitudinal study, we evaluated 1658 eyes of 1658 consecutive glaucoma patients with global mean deviation (MD) VF loss between -3 and -15 dB at baseline and ≥8 reliable VF tests (Swedish Interactive Thresholding Algorithm 24-2) with over ≥3 years of follow-up. The ROP (dB/year) based on global MD, superior hemifield MD, and inferior hemifield MD was calculated. The worst hemifield ROP (ROPworst) and hemifield ROP absolute difference (ROPdiff) were determined for each eye. Eyes were categorized based on the ROP from each metric as slow (-0.5 dB/year or better), rapid (worse than -0.5 dB/year), very rapid (worse than -1.0 dB/year), and catastrophic (worse than -2.0 dB/year) progression. The rate of significant asymmetric hemifield progression rate (ROPdiff ≥0.5 dB/year) was also evaluated. RESULTS: On average, ROPworst was faster than ROPglobal by 0.25±0.3 dB/year ( P <0.001). Based on ROPworst, 422 eyes (25%) were classified as progressing more rapidly than the ROPglobal classification. Over 40% (153/339) of the eyes classified as rapid progressors by ROPglobal were classified as very rapid or catastrophic progressors based on ROPworst. Eyes that progressed more rapidly based on ROPworst also had a higher rate of asymmetric progression. CONCLUSION: Hemifield ROPs are more sensitive to focal progression (or faster progression) than global rates and can aid in tailoring management and treatment decisions.

A Fine-Grained Image Classification Approach for Dog Feces Using MC-SCMNet under Complex Backgrounds.

In a natural environment, factors such as weathering and sun exposure will degrade the characteristics of dog feces; disturbances such as decaying wood and dirt are likely to make false detections; the recognition distinctions between different kinds of feces are slight. To address these issues, this paper proposes a fine-grained image classification approach for dog feces using MC-SCMNet under complex backgrounds. First, a multi-scale attention down-sampling module (MADM) is proposed. It carefully retrieves tiny feces feature information. Second, a coordinate location attention mechanism (CLAM) is proposed. It inhibits the entry of disturbance information into the network's feature layer. Then, an SCM-Block containing MADM and CLAM is proposed. We utilized the block to construct a new backbone network to increase the efficiency of fecal feature fusion in dogs. Throughout the network, we decrease the number of parameters using depthwise separable convolution (DSC). In conclusion, MC-SCMNet outperforms all other models in terms of accuracy. On our self-built DFML dataset, it achieves an average identification accuracy of 88.27% and an F1 value of 88.91%. The results of the experiments demonstrate that it is more appropriate for dog fecal identification and maintains stable results even in complex backgrounds, which may be applied to dog gastrointestinal health checks.

Automatic Detection of Small Sample Apple Surface Defects Using ASDINet.

The appearance quality of apples directly affects their price. To realize apple grading automatically, it is necessary to find an effective method for detecting apple surface defects. Aiming at the problem of a low recognition rate in apple surface defect detection under small sample conditions, we designed an apple surface defect detection network (ASDINet) suitable for small sample learning. The self-developed apple sorting system collected RGB images of 50 apple samples for model verification, including non-defective and defective apples (rot, disease, lacerations, and mechanical damage). First, a segmentation network (AU-Net) with a stronger ability to capture small details was designed, and a Dep-conv module that could expand the feature capacity of the receptive field was inserted in its down-sampling path. Among them, the number of convolutional layers in the single-layer convolutional module was positively correlated with the network depth. Next, to achieve real-time segmentation, we replaced the flooding of feature maps with mask output in the 13th layer of the network. Finally, we designed a global decision module (GDM) with global properties, which inserted the global spatial domain attention mechanism (GSAM) and performed fast prediction on abnormal images through the input of masks. In the comparison experiment with state-of-the-art models, our network achieved an AP of 98.8%, and a 97.75% F1-score, which were higher than those of most of the state-of-the-art networks; the detection speed reached 39ms per frame, achieving accuracy-easy deployment and substantial trade-offs that are in line with actual production needs. In the data sensitivity experiment, the ASDINet achieved results that met the production needs under the training of 42 defective pictures. In addition, we also discussed the effect of the ASDINet in actual production, and the test results showed that our proposed network demonstrated excellent performance consistent with the theory in actual production.

The Boundary of the Market for Biosecurity Risk.

Imported goods create value in destination countries but also create biosecurity risk. Although widely used in other domains of the economy, risk markets have not been created to manage losses that occur when exotic pests and diseases are introduced with traded goods. In this article we show that not all biosecurity risks are insurable. Losses arising from effort needed to detect and respond to exotic pests and diseases that breach national borders appear to be insurable because entry of these threats and consequent response costs, can be regarded as random events. As pests and diseases establish and spread, however, loss of access to export markets and productivity losses display systematic risk and appear to be uninsurable. Other insurability criteria support this definition of the boundary of biosecurity risk markets. We use the Australian biosecurity system as an example, although the framework described in this study will be applicable to biosecurity systems worldwide. We argue that biosecurity risk insurance could be incorporated into the current biosecurity system but would require legislation mandating importers to purchase insurance. Advantages of actuarial pricing of biosecurity risk are: (i) an increase in economic efficiency to the extent that importers respond to the price of biosecurity risk; (ii) financial sustainability would improve because actuarial pricing creates a structural link between funds available for biosecurity activities and risk exposure; and (iii) equity issues evident in the current biosecurity system could be addressed because risk creators (importers) would fund response activities through the purchase of insurance.

Optimizing the Lee-Carter Approach in the Presence of Structural Changes in Time and Age Patterns of Mortality Improvements.

Researchers using the Lee-Carter approach have often assumed that the time-varying index evolves linearly and that the parameters describing the age pattern of mortality decline are time-invariant. However, as several empirical studies suggest, the two assumptions do not seem to hold when the calibration window begins too early. This problem gives rise to the question of identifying the longest calibration window for which the two assumptions hold true. To address this question, we contribute a likelihood ratio-based sequential test to jointly test whether the two assumptions are satisfied. Consistent with the mortality structural changes observed in previous studies, our testing procedure indicates that the starting points of the optimal calibration windows for most populations fall between 1960 and 1990. Using an out-of-sample analysis, we demonstrate that in most cases, models that are estimated to the optimized calibration windows result in more accurate forecasts than models that are fitted to all available data or data beyond 1950. We further apply the proposed testing procedure to data over different age ranges. We find that the optimal calibration windows for age group 0-49 are generally shorter than those for age group 50-89, indicating that mortality at younger ages might have undergone (another) structural change in recent years.

Inhalable spray-dried formulation of D-LAK antimicrobial peptides targeting tuberculosis.

Tuberculosis (TB) is a global disease that is becoming more difficult to treat due to the emergence of multidrug resistant (MDR) Mycobacterium tuberculosis. Inhalable antimicrobial peptides (AMPs) are potentially useful alternative anti-TB agents because they can overcome resistance against classical antibiotics, reduce systemic adverse effects, and achieve local targeting. The aims of the current study were to produce inhalable dry powders containing d-enantiomeric AMPs (D-LAK120-HP13 and D-LAK120-A) and evaluate their solid state properties, aerosol performance, and structural conformation. These two peptides were spray dried with mannitol as a bulking agent at three mass ratios (peptide:mannitol 1:99, 1:49, and 1:24) from aqueous solutions. The resultant particles were spherical, with those containing D-LAK120-HP13 being more corrugated than those with D-LAK120-A. The median volumetric diameter of the particles was approximately 3µm. The residual water content of all powders were <3% w/w and crystalline, due to the low hygroscopicity and crystallinity of mannitol, respectively. The mannitol changed from a mixture of alpha- and beta-forms to delta form with an increasing proportion of AMP in the formulation. The emitted fraction and fine particle fraction of the powders when dispersed from an Osmohaler(®) at 90L/min were about 80% and 50-60% of the loaded dose, respectively, indicating good aerosol performance. Circular dichroism data showed that D-LAK120-HP13 dissolved in Tris buffer at pH 7.15 was of a disordered conformation. In contrast, D-LAK120-A showed greater α-helical conformation. Since the conformations of the AMPs were comparable to the controls (unprocessed peptides), the spray drying process did not substantially affect their secondary structures. In conclusion, spray dried powders containing d-enantiomeric AMPs with preserved secondary molecular structures and good aerosol performance could be successfully produced. They may potentially be used for treating MDR-TB when delivered by inhalation.

Redesigning Escherichia coli metabolism for anaerobic production of isobutanol.

Fermentation enables the production of reduced metabolites, such as the biofuels ethanol and butanol, from fermentable sugars. This work demonstrates a general approach for designing and constructing a production host that uses a heterologous pathway as an obligately fermentative pathway to produce reduced metabolites, specifically, the biofuel isobutanol. Elementary mode analysis was applied to design an Escherichia coli strain optimized for isobutanol production under strictly anaerobic conditions. The central metabolism of E. coli was decomposed into 38,219 functional, unique, and elementary modes (EMs). The model predictions revealed that during anaerobic growth E. coli cannot produce isobutanol as the sole fermentative product. By deleting 7 chromosomal genes, the total 38,219 EMs were constrained to 12 EMs, 6 of which can produce high yields of isobutanol in a range from 0.29 to 0.41 g isobutanol/g glucose under anaerobic conditions. The remaining 6 EMs rely primarily on the pyruvate dehydrogenase enzyme complex (PDHC) and are typically inhibited under anaerobic conditions. The redesigned E. coli strain was constrained to employ the anaerobic isobutanol pathways through deletion of 7 chromosomal genes, addition of 2 heterologous genes, and overexpression of 5 genes. Here we present the design, construction, and characterization of an isobutanol-producing E. coli strain to illustrate the approach. The model predictions are evaluated in relation to experimental data and strategies proposed to improve anaerobic isobutanol production. We also show that the endogenous alcohol/aldehyde dehydrogenase AdhE is the key enzyme responsible for the production of isobutanol and ethanol under anaerobic conditions. The glycolytic flux can be controlled to regulate the ratio of isobutanol to ethanol production.