Mask Design Research Articles

Breaking Ground: A New Area Record for Low-Latency First-Order Masked SHA-3

SHA-3, the latest hash standard from NIST, is utilized by numerous cryptographic algorithms to handle sensitive information. Consequently, SHA-3 has become a prime target for side-channel attacks, with numerous studies demonstrating successful breaches in unprotected implementations. Masking, a countermeasure capable of providing theoretical security, has been explored in various studies to protect SHA-3. However, masking for hardware implementations may significantly increase area costs and introduce additional delays, substantially impacting the speed and area of higher-level algorithms. In particular, current low-latency first-order masked SHA-3 hardware implementations require more than four times the area of unprotected implementations. To date, the specific structure of SHA-3 has not been thoroughly analyzed for exploitation in the context of masking design, leading to difficulties in minimizing the associated area costs using existing methods. We bridge this gap by conducting detailed leakage path and data dependency analyses on two-share masked SHA-3 implementations. Based on these analyses, we propose a compact and low-latency first-order SHA-3 masked hardware implementation, requiring only three times the area of unprotected implementations and almost no fresh random number demand. We also present a complete theoretical security proof for the proposed implementation in the glitch+register-transition-robust probing model. Additionally, we conduct leakage detection experiments using PROLEAD, TVLA and VerMI to complement the theoretical evidence. Compared to state-of-theart designs, our implementation achieves a 28% reduction in area consumption. Our design can be integrated into first-order implementations of higher-level cryptographic algorithms, contributing to a reduction in overall area costs.

PyMOE: Mask design and modeling for micro optical elements and flat optics

We introduce a new open-source software package written in Python to design and model micro optical elements, such as diffractive lenses, holograms, as well as other components within the broad area of flat optics, and generate their corresponding (production-ready) lithography mask files. To this aim, the package provides functions to design a multitude of kinoform lenses, phase masks and holograms, but is versatile and the user can implement any arbitrary numerical or analytical optical component designs. For validating the designs, this package provides scalar diffraction propagation to simulate optical field propagation in different regimes covering near- and far-field regions (Fresnel, Fraunhofer and Rayleigh-Sommerfeld). Particularly, by implementing Rayleigh-Sommerfeld propagation, we demonstrate accurate field propagation within near- and far-field ranges, providing versatility and accuracy. Importantly, the package allows to directly export production-ready multilevel/binary lithography mask files of the designed optical components. Additionally, metasurface masks can conveniently be generated for any user-defined meta-element library given as input. Finally, the software package capabilities are illustrated with examples of mask design and modeling of diffractive lenses, holograms, and metasurfaces susceptible of being fabricated via lithography techniques. Beyond lithography, the package can also straightforwardly be used in other applications requiring mask generation, such as beam shaping, optical trapping and digital holography.

Abstract 719: A tumor-activated PD1/IL2 bispecific molecule, designed to overcome IL-2 receptor-mediated clearance, improve tolerability and stimulate antigen-experienced CD8+ T cells in the tumor microenvironment of murine models

Abstract PD-1/PD-L1 therapies have shown significant activity across a range of tumor types, however, 70-90% of patients do not derive durable benefit. In preclinical settings, delivery of PD-1 blockade and IL-2 agonism in cis via a bispecific molecule, comprising a PD-1 antibody fused to IL-2, has demonstrated superior activity compared to delivery of individual components or their combination. Targeting of IL-2 to PD-1+ cells in cis has been shown to drive a unique differentiation path endowing CD8+ T cells with enhanced functionality. However, we show that the IL-2 component in an unmasked PD1/IL2 bispecific molecule dominates its pharmacology, driving marked peripheral activation of immune cells, rapid IL-2 receptor-mediated clearance and systemic toxicity. To address these challenges and enable tumor-specific activity, we designed a PD1/IL2 bispecific molecule that incorporates a single domain antibody-based mask to bind to the IL-2 component and maintain it in a quiescent state until activated by prevalent and dysregulated proteases in the tumor microenvironment (TME). In preclinical models, the affinity-optimized mask prevented peripheral IL-2 receptor binding, associated toxicity and receptor-mediated clearance. Improved pharmacokinetics of our tumor-activated PD1/IL2 enabled PD1 antibody-like exposures and is projected to achieve complete blockade of PD1 signaling. Tumor-activated PD1/IL2 significantly inhibited tumor growth compared to anti-PD-1 alone or vehicle and demonstrated improved tolerability compared to an unmasked PD1/IL2 bispecific in mouse models. In addition, pharmacodynamic activity of tumor-activated PD1/IL2 was restricted to the TME. Consistent with the masked design, we observed no significant change in CD8+ T cells in the periphery and significant increases in antigen specific CD8+ T cells, memory CD8+ T cells and TCF1+ stem-like CD8+ T cells in the TME. Ex vivo protease cleavage assays performed in human samples demonstrated efficient activation of tumor-activated PD1/IL2 by multiple tumor types and minimal activation in human plasma. In non-human primates, tumor-activated PD1/IL2 achieved tolerable exposures that were comparable to those of existing PD-1 blocking immunotherapies. Taken together, these preclinical data suggest that tumor-activated PD1/IL2 has the potential to improve upon existing PD-1/PD-L1 immunotherapies by inhibiting PD-1/PD-L1 axis and simultaneously directing immunostimulatory IL-2 to antigen-experienced effector cell populations in the TME. Citation Format: Ertan Eryilmaz, Wilson Guzman, Stephanie Hsiao, Parker Johnson, Lisa Quinn, Jimit Lakhani, Brendan Whalen, Rosa Quiroz, Kurt Jenkins, Bernard Lanter, Oleg Yerov, Will Scott, Justin Greene, Zhen Liu, Jason Hedges, Megan McLaughlin, Sallyann Vu, Chelsea Turcotte, Jacob Taylor, Caitlin O'Toole, Magali Pederzoli-Ribeil, Haley Duprey, Natalia Malkova, Damiano Fantini, David Crowe, Kyle Smith, Joseph Card, Janice Lee, Kerri Smith, Benjamin Nicholson, Jennifer O'Neil, Carl U. Bialucha. A tumor-activated PD1/IL2 bispecific molecule, designed to overcome IL-2 receptor-mediated clearance, improve tolerability and stimulate antigen-experienced CD8+ T cells in the tumor microenvironment of murine models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 719.

Masking Floating-Point Number Multiplication and Addition of Falcon

In this paper, we provide the first masking scheme for floating-point number multiplication and addition to defend against recent side-channel attacks on Falcon’s pre-image vector computation. Our approach involves a masked nonzero check gadget that securely identifies whether a shared value is zero. This gadget can be utilized for various computations such as rounding the mantissa, computing the sticky bit, checking the equality of two values, and normalizing a number. To support the masked floating-point number addition, we also developed a masked shift and a masked normalization gadget. Our masking design provides both first- and higherorder mask protection, and we demonstrate the theoretical security by proving the (Strong)-Non-Interference properties in the probing model. To evaluate the performance of our approach, we implemented unmasked, first-order, and second-order algorithms on an Arm Cortex-M4 processor, providing cycle counts and the number of random bytes used. We also report the time for one complete signing process with our countermeasure on an Intel-Core CPU. In addition, we assessed the practical security of our approach by conducting the test vector leakage assessment (TVLA) to validate the effectiveness of our protection. Specifically, our TVLA experiment results for second-order masking passed the test in 100,000 measured traces.

Efficacy of a topical combination of esafoxolaner, eprinomectin and praziquantel against Amblyomma maculatum infestations in cats.

Amblyomma maculatum, the Gulf Coast tick, infests a wide range of vertebrate species including livestock, dogs, cats, and humans. It is a species of significant veterinary and public health importance, especially as a vector of diseases, for instance American canine hepatozoonosis or tidewater spotted fever. An experimental study was conducted to evaluate the efficacy of NexGard® Combo, a topical endectoparasiticide product for cats combining eprinomectin, praziquantel and esafoxolaner, against induced infestations of A. maculatum in cats. This Good Clinical Practice (GCP) study used a randomized, negative controlled, masked design. Ten cats were allocated to an untreated group and ten to a treated group, dosed once on Day 0 at the minimum label dose. On Days -2, 7, 14, 21, 28, 35, and 42, cats were infested with ~50 unfed adult A. maculatum. On Days 3, 10, 17, 24, 31, 38, and 45, i.e., 72h after treatment and subsequent infestations, ticks were removed, counted and the numbers of live attached tick in each group were used for efficacy calculations. At each time-point, all untreated cats were adequately infested, demonstrating a vigorous tick population and an adequate study model. The curative efficacy after a single application against existing tick infestation, 72h after treatment, was 98.7%. The preventive efficacy, 72h after weekly infestations, over the following five weeks ranged from 93.8% to 99.4%.

Deep Unrolled Single Snapshot Phase Retrieval via Non-Convex Formulation and Phase Mask Design

Deep Unrolled Single Snapshot Phase Retrieval via Non-Convex Formulation and Phase Mask Design

Art Mask Design Using Grotesque Characteristics in Modern Art

Art in the fast-changing modern era creates various works through organic combinations without any clear distinction. Art mask, a territory of art expressed by using masks that resemble a human face, the representation of the grotesque fusion design implemented by the art mask present various senses and thinking skills to modern people who expect new things against the existing forms. Therefore, the characteristics of fear, dislike, playfulness, and atypia in Grotesque can open up to a new making method in a comprehensive and innovative way. By incorporating the characteristics of Grotesque paintings that have become popular in modern art, this study expressed demonism by expressing the heterogeneous appearance of a sleeping woman and in a smooth line and geometric way in the form of a human face in the work expressed in art mask which is based on “Nightmare” by John Henry Pujelly in Work I, the bizarre image of the extremely exaggerated size of the eyes was embodied in a deformed form by not expressing the nose with the motif of “Strange Balloon-like Eyes Traveling to Infinite” by Odilong Le Dong in Work II, the tears in both eyes on the mask represented a physically damaged body, and used various lines to express disgust. Work III expressed the playfulness of infantile grotesque like clowns by using elements of satire in “conspiracy” by James Ansore as a motif. The Work IV expressed the time of hopelessness without life by expressing abnormally abhorrent and unnatural things and the distorted cravings of life in fear as skeletons that are abnormally disgusting and unnatural by using “Release of the Fifth Seal of John's Apocalypse” by El Greco as a motif. The conflicting emotions were expressed by gradating the skull's eyes with black paint, and was reinterpreted as a dream and hope using various colors of color. As a result of this study, it was identified that paintings that expressed the characteristics of grotesque through art mask production can present unlimited imagination and a variety of topics to artists in the makeup field. This study is expected to be used as a basic data for a follow-up study on art mask design in the future and will help to develop art mask designs.

Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models

Point-of-interest (POI) search is important for location-based services, such as navigation and online ride-hailing service. The goal of POI search is to find the most relevant destinations from a large-scale POI database given a text query. To improve the effectiveness and efficiency of POI search, most existing approaches are based on a multi-stage pipeline that consists of an efficiency-oriented retrieval stage and one or more effectiveness-oriented re-rank stages. In this article, we focus on the first efficiency-oriented retrieval stage of the POI search. We first identify the limitations of existing first-stage POI retrieval models in capturing the semantic-geography relationship and modeling the fine-grained geographical context information. Then, we propose a Geo-Enhanced Dense Retrieval framework for POI search to alleviate the above problems. Specifically, the proposed framework leverages the capacity of pre-trained language models (e.g., BERT) and designs a pre-training approach to better model the semantic match between the query prefix and POIs. With the POI collection, we first perform a token-level pre-training task based on a geographical-sensitive masked language prediction and design two retrieval-oriented pre-training tasks that link the address of each POI to its name and geo-location. With the user behavior logs collected from an online POI search system, we design two additional pre-training tasks based on users’ query reformulation behavior and the transitions between POIs. We also utilize a late-interaction network structure to model the fine-grained interactions between the text and geographical context information within an acceptable query latency. Extensive experiments on the real-world datasets collected from the Didichuxing application demonstrate that the proposed framework can achieve superior retrieval performance over existing first-stage POI retrieval methods.

Design of a Generative AI Image Similarity Test Application and Handmade Images Using Deep Learning Methods

Purpose: The aim of this research is to develop a classification model using the Transformer approach, specifically the BEiT architecture, to differentiate between handmade images and AI Generative Art. The objective is to ensure the authenticity of art and address ethical and legal concerns related to AI Generative Art.Design/methodology/approach: The study utilizes the BEiT architecture within the Transformer approach to create a classification model. The training process uses Bidirectional Encoder representation from Image Transformers (BEiT) to improve image classification. The primary datasets are collected through a Python image scraper program. The BEiT workflow includes Pre-training, Masking, Inpainting, and Interface Design with Gradio.Findings/result: The Transformer model, using the BEiT architecture, achieves 96.34% accuracy and 0.0921 loss in differentiating handmade images and AI Generative Art. The model demonstrates a balanced precision and recall in each category, outperforming previous methods such as Convolutional Neural Network (CNN) and VGG16. The language used is clear, objective, and value-neutral, with a formal register and precise word choice. No changes in content were made. The Gradio interface was used to successfully test the model.Originality/value/state of the art: The research presents a state-of-the-art classification model that uses the Transformer approach, specifically the BEiT architecture, to differentiate between handmade and AI Generative Art images. The research presents a state-of-the-art classification model that uses the Transformer approach, specifically the BEiT architecture, to differentiate between handmade and AI Generative Art images. The text adheres to conventional structure and formatting features, including consistent citation and footnote style. The sentences and paragraphs create a logical flow of information with causal connections between statements. The text is free from grammatical errors, spelling mistakes, and punctuation errors. Additionally, the research is enhanced by the innovative approach to data collection using a Python image scraper program.

Evaluating a Brief Big Five Personality Test in a Diverse Chinese Sample: The Role of Midpoint Designs and Reversely-Worded Items

Response styles present a threat to the validity of data from Likert scales. This study evaluates a brief personality test administered by interviewers to a diverse Chinese sample, focusing on two factors with direct impacts on response styles, the midpoint designs and the inclusion of reversely-worded items. We randomly assign respondents into three midpoint designs: masked midpoint, explicit midpoint and removed midpoint. Cronbach’s alpha tends to be low and is not drastically affected by midpoint designs. Score reliability estimates from the removed and explicit midpoint designs are above or close to .60 along the whole score range for openness, but not the other subscales. The masked midpoint design presents some advantages in criterion relationship validity evidence based on correlations with demographic, behavioral, subjective and cognitive variables. Dropping reversely-worded items increases the estimates of Cronbach’s alpha, but shows no positive effects on the criterion relationship validity. In conclusion, for interviewer-administered brief personality scales applied to Chinese respondents, masked midpoint design that aims to reduce a possible overuse of midpoint presents some advantages in the overall psychometric properties, but the inclusion of reversely-worded items shows mixed effects.

A High-Performance Masking Design Approach for Saber against High-order Side-channel Attack

Post-quantum cryptography (PQC) has become the most promising cryptographic scheme against the threat of quantum computing to conventional public-key cryptographic schemes. Saber, as the finalist in the third round of the PQC standardization procedure, presents an appealing option for embedded systems due to its high encryption efficiency and accessibility. However, side-channel attack (SCA) can easily reveal confidential information by analyzing the physical manifestations, and several works demonstrate that Saber is vulnerable to SCAs. In this work, a ciphertext comparison method for masking design based on bitslicing technique and zerotest is proposed, which balances the trade-off between the performance and security of comparing two arrays. The mathematical description of the proposed ciphertext comparison method is provided, and its correctness and security metrics are analyzed under the concept of PINI. Moreover, a high-order masking approach based on the state-of-the-art, including the hash functions, centered binomial sampling, masking conversions, and proposed ciphertext comparison is presented, using the bitslicing technique to improve throughput. As a proof of concept, the proposed implementation of Saber is on the ARM Cortex-M4. The performance results show that the run-time overhead factor of 1 st -, 2 nd -, and 3 rd -order masking is 3.01x, 5.58x, and 8.68x, and the dynamic memory used for 1 st -, 2 nd -, and 3 rd -order masking is 17.4kB, 24.0kB, and 30.2kB, respectively. The SCA-resilience evaluation results illustrate that the first-order Test Vectors Leakage Assessment (TVLA) result fails to reveal the secret key with 100,000 traces.

Deep Reinforcement Learning-Based Deterministic Routing and Scheduling for Mixed-Criticality Flows

Deterministic networking (DetNet) has recently drawn much attention by investigating deterministic flow scheduling. Combined with artificial intelligent (AI) technologies, it can be leveraged as a promising network technology for facilitating automated network configuration in the Industrial Internet of Things (IIoT). However, the stricter requirements of the IIoT have posed significant challenges, that is, deterministic and bounded latency for time-critical applications. This paper incorporates deep reinforcement learning (DRL) in Cycle Specified Queuing and Forwarding (CSQF) and proposes a DRL-based Deterministic Flow Scheduler (Deep-DFS) to solve the Deterministic Flow Routing and Scheduling (DFRS) problem. Novel delay aware network representations, action masking and criticality aware reward function design are proposed to make Deep-DFS more scalable and efficient. Simulation experiments are conducted to evaluate the performances of Deep-DFS, and the results show that Deep-DFS can schedule more flows than the other benchmark methods (heuristic-based and AI-based methods).

Mask design, fabrication, and experimental ghost imaging applications for patterned X-ray illumination.

A set of non-configurable transversely-displaced masks has been designed and fabricated to generate high-quality X-ray illumination patterns for use in imaging techniques such as ghost imaging (GI), ghost projection, and speckle tracking. The designs include a range of random binary and orthogonal patterns, fabricated through a combination of photolithography and gold electroplating techniques. We experimentally demonstrated that a single wafer can be used as an illumination mask for GI, employing individual illumination patterns and also a mixture of patterns, using a laboratory X-ray source. The quality of the reconstructed X-ray ghost images has been characterized and evaluated through a range of metrics.

Phase Mask Design Based on an Improved Particle Swarm Optimization Algorithm for Depth of Field Extension

Phase mask optimization is one of the critical steps in designing a wavefront coding system to extend the depth of field (DoF). As a classical phase mask, a cubic phase mask was taken as an example. An improved particle swarm optimization (PSO) algorithm was applied to calculate the parameters of the cubic phase mask by introducing the modulation transfer function as the optimization criterion and a threshold as a constraint. The quality of the subsequent image restoration is guaranteed on the premise of the extended DoF. Finally, the improved PSO was proved to be faster, more efficient, and more accurate compared to the simulated annealing algorithm and the traditional PSO. The experimental results verify that the cubic phase mask optimized by the improved PSO can achieve DoF extension in the wavefront coding system. The improved PSO can also be applied to other phase masks of wavefront coding systems.

Influence of Aerosol Mask Design on Fugitive Aerosol Concentrations During Nebulization.

Secondhand exposure to fugitive aerosols may cause airway diseases in health providers. We hypothesized that redesigning aerosol masks to be closed-featured would reduce the fugitive aerosol concentrations during nebulization. This study aimed to evaluate the influence of a mask designed for a jet nebulizer on the concentration of fugitive aerosols and delivered doses. An adult intubation manikin was attached to a lung simulator to mimic normal and distressed adult breathing patterns. The jet nebulizer delivered salbutamol as an aerosol tracer. The nebulizer was attached to 3 aerosol face masks: an aerosol mask, a modified non-rebreathing mask (NRM, with no vent holes), and an AerosoLess mask. An aerosol particle sizer measured aerosol concentrations at parallel distances of 0.8 m and 2.2 m and a frontal distance of 1.8 m from the manikin. The drug dose delivered distal to the manikin's airway was collected, eluted, and analyzed using a spectrophotometer at a 276 nm wavelength. With a normal breathing pattern, the trends of aerosol concentrations were higher with an NRM followed by an aerosol mask and AerosoLess mask (P < .001) at 0.8 m; however, the concentrations were higher with an aerosol mask followed by NRM and AerosoLess mask at 1.8 m (P < .001) and 2.2 m (P < .001). With a distressed breathing pattern, the aerosol concentrations were higher with an aerosol mask followed by an NRM and AerosoLess mask at 0.8 m, 1.8 m (P < .001), and 2.2 m (P = .005). The delivered drug dose was significantly higher with AerosoLess mask with a normal breathing pattern and with an aerosol mask with a distressed breathing pattern. Mask design influences fugitive aerosol concentrations in the environment, and a filtered mask reduces the concentration of aerosols at 3 different distances and with 2 breathing patterns.

Measuring Total Filtration Efficiency of Surgical and Community Face Masks: Impact of Mask Design Features

Surgical and community face masks are used worldwide to reduce the transmission of respiratory infections in indoor environments. Performance parameters for these loose-fitting devices are mainly focused on material filtering efficiency, while, differently from face respirators, there are no standards methods for measuring the fraction of air leaking at the face seal. This study quantifies the total filtration efficiency (TFE), a parameter based both on filter efficiency and air leakage, of 50 face mask models with the aim of understanding the role of several mask design features on TFE performance. An instrumented head form equipped with sensors for measuring volumetric airflow and differential pressure was used to simulate the air exhalation from the mouth of a person wearing a face mask. A Response Surface Method (RSM) was used to model the TFE experimental data. Results showed that TFE values ranged over a wide interval (from 5 % to 73 %), with better values at higher flowrates. A significant positive correlation was found between TFE and filter breathability. The presence of a nosepiece showed to increase the TFE on average from 4 % to 6 %, according to the flowrate. Significant improvements were associated only to nosepieces incorporating a metallic wire. The RSM model evidenced that the increase in the number of the filter layers, and the use of a meltblown layer, result in higher TFE only when a nosepiece is in place. Differently, the benefit of the nosepiece is less marked for masks made of highly breathable filters. To improve overall mask performance, the design of loose-fitting face masks should carefully compromise between breathability and filtration efficiency of the filter materials. The addition of a metallic nosepiece help improving the TFE by limiting the air leaking at the face seal.

A Method for Generation of a Sizing System and Representative Models for a Facial Mask Design

A sizing system and representative face models (RFMs) need to be properly determined for the design of a facial mask. The present study proposed a novel approach for the generation of a sizing system and RFMs for a facial mask that considers not only the accommodation of the target population but also its applicability in practice (e.g., ease of use and economic efficiency). A custom sizing system with four unique sizing categories was generated by applying the proposed approach for a pilot oxygen mask for Korean pilots. Then, out of 336 faces, a face showing the minimum value of weighted sum of Euclidean distance (WSED) was identified as the RFM of each of the four sizing categories. The proposed approach can be applied to the development of a sizing system and the identification of representative human models for the design of wearable products associated with multiple body dimensions.

Performance evaluation of speech masking design among listeners with varying language backgrounds

Speech masking is a technique used for protecting speech confidentiality, which is realised by adding maskers to cover target speech. Numerous studies have demonstrated the native and non-native differences in perceiving masked speech, but few have compared the effect of masker types from the perspective of effectiveness of speech privacy and their annoyance levels. This paper reports on the result of an English word perception task by native and non-native listeners where six types of maskers, both speech-like and non-speech-like, are implemented, as well as the annoyance levels of each masker. Natives, non-natives residing in an English-speaking country, and non-natives residing in a non-English-speaking country were tasked to write down sentences when masking sound was present, and also to rate the annoyance levels of the maskers. Results showed that language background significantly affected the performance of unmasked speech, the difference between the two non-native listeners became minimal in the presence of maskers, and maskers annoyed the listener groups differently, calling for a discussion in the selection of a universally effective masker to increase speech privacy.

Evaluation of compounded cidofovir, famciclovir, and ganciclovir for the treatment of feline herpesvirus ocular surface disease in shelter-housed cats.

To assess the efficacy of compounded cidofovir, famciclovir, and ganciclovir for the treatment of feline herpesvirus type 1 (FHV-1) ocular surface disease. 132 shelter-housed cats qPCR positive for FHV-1. A masked placebo-controlled study design was utilized. Animals were enrolled in one of four treatment groups: topical ocular placebo + oral placebo (n=32), compounded cidofovir 0.5% ophthalmic solution + oral placebo (n=32), compounded famciclovir oral solution (90 mg/kg) + topical ocular placebo (n=32), and compounded ganciclovir 0.15% ophthalmic solution + oral placebo (n=36). Cats were treated with each medication twice daily for 7 days and were evaluated on Day 1 and Day 8 using an ocular scoring system, body weight, and qPCR for FHV-1 viral load. Cidofovir significantly decreased viral load from Day 1 to Day 8 compared with placebo (p=.024). Neither famciclovir nor ganciclovir decreased viral load compared with placebo (p=.14, p=.41). There was no significant improvement of ocular scores for any drug group compared with placebo (p=.62). In all groups, 65%-75% of cats improved from Day 1 to Day 8. Juvenile cats had a significant increase in weight gain compared with placebo for cidofovir (p=.025) and ganciclovir (p=.023). All corneal ulcers in placebo animals failed to heal whereas 77% of ulcers in antiviral group animals healed. Topical ophthalmic cidofovir significantly decreased ocular FHV-1 viral shedding and increased weight gain in juvenile cats. Ganciclovir increased weight gain in juvenile cats. Compounded famciclovir demonstrated limited efficacy for the treatment of FHV-1 ocular surface disease in shelter-housed cats.

Analysis of Drug Clinical Trials for Eye Diseases in China.

Purpose: We systematically retrospected and analyzed the general characteristics of ophthalmic drug clinical trials (CTs) registered in China from January 2014 to December 2021. Methods: Data were retrieved from the Drug Trial Registration and Information Publication Platform and then standardized and statistically classified using bibliometric analysis. Results: We identified 201 drug CTs for eye diseases, including 24 international multicenter trials. The number of drug CTs for eye diseases has considerably increased since 2017 in parallel with new policies to encourage innovation in drugs and medical devices in China. The drug types consist of biologicals (48.26%), chemicals (45.77%), and traditional Chinese medicine/natural medicines (5.97%). The main indications were age-related macular degeneration (AMD; n = 47, 23.38%), macular edema (n = 32, 15.92%), and diabetic retinopathy (n = 19, 9.45%). The trials included those in phase I (n = 67, 33.33%), phase II (n = 33, 16.42%), and phase III (n = 72, 35.82%). The phase I trials comprised 24 innovative drug treatments for AMD and 6 novel drug treatments for neuromyelitis optica spectrum disorders, with 39 biologicals and 27 chemicals. The trials mostly followed a randomized (84.08%) or masked (67.16%) design, with 90.37% of the latter being double-masked trials. Conclusion: Research and development of ophthalmic drugs have substantially increased in recent years and are influenced by regulatory policies. Among these drugs, biologicals for AMD are the most prevalent, followed by biologicals for macular edema. Randomized double-masked research designs are often used and represent high-quality evidence.