Using transfer learning-based plant disease classification and detection for sustainable agriculture

Subsistence farmers and global food security depend on sufficient food production, which aligns with the UN's "Zero Hunger," "Climate Action," and "Responsible Consumption and Production" sustainable development goals. In addition to already available methods for early disease detection and classification facing overfitting and fine feature extraction complexities during the training process, how early signs of green attacks can be identified or classified remains uncertain. Most pests and disease symptoms are seen in plant leaves and fruits, yet their diagnosis by experts in the laboratory is expensive, tedious, labor-intensive, and time-consuming. Notably, how plant pests and diseases can be appropriately detected and timely prevented is a hotspot paradigm in smart, sustainable agriculture remains unknown. In recent years, deep transfer learning has demonstrated tremendous advances in the recognition accuracy of object detection and image classification systems since these frameworks utilize previously acquired knowledge to solve similar problems more effectively and quickly. Therefore, in this research, we introduce two plant disease detection (PDDNet) models of early fusion (AE) and the lead voting ensemble (LVE) integrated with nine pre-trained convolutional neural networks (CNNs) and fine-tuned by deep feature extraction for efficient plant disease identification and classification. The experiments were carried out on 15 classes of the popular PlantVillage dataset, which has 54,305 image samples of different plant disease species in 38 categories. Hyperparameter fine-tuning was done with popular pre-trained models, including DenseNet201, ResNet101, ResNet50, GoogleNet, AlexNet, ResNet18, EfficientNetB7, NASNetMobile, and ConvNeXtSmall. We test these CNNs on the stated plant disease detection and classification problem, both independently and as part of an ensemble. In the final phase, a logistic regression (LR) classifier is utilized to determine the performance of various CNN model combinations. A comparative analysis was also performed on classifiers, deep learning, the proposed model, and similar state-of-the-art studies. The experiments demonstrated that PDDNet-AE and PDDNet-LVE achieved 96.74% and 97.79%, respectively, compared to current CNNs when tested on several plant diseases, depicting its exceptional robustness and generalization capabilities and mitigating current concerns in plant disease detection and classification.

A Comprehensive Study on Cyber Attacks in Communication Networks in Water Purification and Distribution Plants: Challenges, Vulnerabilities, and Future Prospects

In recent years, the Internet of Things (IoT) has had a big impact on both industry and academia. Its profound impact is particularly felt in the industrial sector, where the Industrial Internet of Things (IIoT), also known as Industry 4.0, is revolutionizing manufacturing and production through the fusion of cutting-edge technologies and network-embedded sensing devices. The IIoT revolutionizes several industries, including crucial ones such as oil and gas, water purification and distribution, energy, and chemicals, by integrating information technology (IT) with industrial control and automation systems. Water, a vital resource for life, is a symbol of the advancement of technology, yet knowledge of potential cyberattacks and their catastrophic effects on water treatment facilities is still insufficient. Even seemingly insignificant errors can have serious consequences, such as aberrant pH values or fluctuations in the concentration of hydrochloric acid (HCI) in water, which can result in fatalities or serious diseases. The water purification and distribution industry has been the target of numerous hostile cyber security attacks, some of which have been identified, revealed, and documented in this paper. Our goal is to understand the range of security threats that are present in this industry. Through the lens of IIoT, the survey provides a technical investigation that covers attack models, actual cases of cyber intrusions in the water sector, a range of security difficulties encountered, and preventative security solutions. We also explore upcoming perspectives, illuminating the predicted advancements and orientations in this dynamic subject. For industrial practitioners and aspiring scholars alike, our work is a useful, enlightening, and current resource. We want to promote a thorough grasp of the cybersecurity landscape in the water industry by combining key insights and igniting group efforts toward a safe and dependable digital future.

Security Framework for Network-Based Manufacturing Systems with Personalized Customization: An Industry 4.0 Approach

Smart manufacturing is pivotal in the context of Industry 4.0, as it integrates advanced technologies like the Internet of Things (IoT) and automation to streamline production processes and improve product quality, paving the way for a competitive industrial landscape. Machines have become network-based through the IoT, where integrated and collaborated manufacturing system responds in real time to meet demand fluctuations for personalized customization. Within the network-based manufacturing system (NBMS), mobile industrial robots (MiRs) are vital in increasing operational efficiency, adaptability, and productivity. However, with the advent of IoT-enabled manufacturing systems, security has become a serious challenge because of the communication of various devices acting as mobile nodes. This paper proposes the framework for a newly personalized customization factory, considering all the advanced technologies and tools used throughout the production process. To encounter the security concern, an IoT-enabled NBMS is selected as the system model to tackle a black hole attack (BHA) using the NTRUEncrypt cryptography and the ad hoc on-demand distance-vector (AODV) routing protocol. NTRUEncrypt performs encryption and decryption while sending and receiving messages. The proposed technique is simulated by network simulator NS-2.35, and its performance is evaluated for different network environments, such as a healthy network, a malicious network, and an NTRUEncrypt-secured network based on different evaluation metrics, including throughput, goodput, end-to-end delay, and packet delivery ratio. The results show that the proposed scheme performs safely in the presence of a malicious node. The implications of this study are beneficial for manufacturing industries looking to embrace IoT-enabled subtractive and additive manufacturing facilitated by mobile industrial robots. Implementation of the proposed scheme ensures operational efficiency, enables personalized customization, and protects confidential data and communication in the manufacturing ecosystem.

High-Speed Network DDoS Attack Detection: A Survey

Having a large number of device connections provides attackers with multiple ways to attack a network. This situation can lead to distributed denial-of-service (DDoS) attacks, which can cause fiscal harm and corrupt data. Thus, irregularity detection in traffic data is crucial in detecting malicious behavior in a network, which is essential for network security and the integrity of modern Cyber-Physical Systems (CPS). Nevertheless, studies have shown that current techniques are ineffective at detecting DDoS attacks on networks, especially in the case of high-speed networks (HSN), as detecting attacks on the latter is very complex due to their fast packet processing. This review aims to study and compare different approaches to detecting DDoS attacks, using machine learning (ML) techniques such as k-means, K-Nearest Neighbors (KNN), and Naive Bayes (NB) used in intrusion detection systems (IDSs) and flow-based IDSs, and expresses data paths for packet filtering for HSN performance. This review highlights the high-speed network accuracy evaluation factors, provides a detailed DDoS attack taxonomy, and classifies detection techniques. Moreover, the existing literature is inspected through a qualitative analysis, with respect to the factors extracted from the presented taxonomy of irregular traffic pattern detection. Different research directions are suggested to support researchers in identifying and designing the optimal solution by highlighting the issues and challenges of DDoS attacks on high-speed networks.

Using a Novel Convolutional Neural Network for Plant Pests Detection and Disease Classification

BACKGROUND

Early plant diseases and pests identification reduces social, economic, and environmental deficiencies entailing toxic chemical utilization on agricultural farms, thus posing a threat to global food security.

METHODOLOGY

An enhanced convolutional neural network (CNN) along with long short-term memory (LSTM) using a majority voting (MVE) ensemble classifier has been proposed to tackle plant pest and disease identification and classification. Within pre-trained models, deep feature extractions have been obtained from connected layers. Deep features have been extracted and are sent to the LSTM layer to build a robust, enhanced LSTM-CNN model for detecting plant pests and diseases. Experiments were carried out using Turkey Dataset, with 4,447 apple pests and diseases categorized into 15 different classes.

RESULTS

The study has been evaluated in different CNNs using logistic regression (LR), LSTM, and extreme learning machine (ELM), focusing on plant disease detection problems. The ensemble majority voting (EMV) classifier was used at the LSTM layer to detect and classify plant disease labels. Furthermore, an autonomous selection of the optimal LSTM layer network parameters was applied. Finally, the performance was validated based on sensitivity, F1-score, accuracy, and specificity using LSTM, ELM, and LR classifiers.

CONCLUSION

The presented model attained 99.2% accuracy in comparison to the cutting-edge models on different classifiers like LSTM, LR, and ELM, and performed better in comparison to transfer learning (TL). Pre-trained models, like VGG-19, VGG-18, and AlexNet, demonstrated better accuracy when the fc6 layer was compared to other layers. This article is protected by copyright. All rights reserved.

A Systematic Literature Review on Service Composition for People with Disabilities: Taxonomies, Solutions, and Open Research Challenges

Integrating smart heterogeneous objects, IoT devices, data sources, and software services to produce new business processes and functionalities continues to attract considerable attention from the research community due to its unraveled advantages, including reusability, adaptation, distribution, and pervasiveness. However, the exploitation of service-oriented computing technologies (e.g., SOC, SOA, and microservice architectures) by people with special needs is underexplored and often overlooked. Furthermore, the existing challenges in this area are yet to be identified clearly. This research study presents a rigorous literature survey of the recent advances in service-oriented composition approaches and solutions for disabled people, their domains of application, and the major challenges, covering studies published between January 2010 and October 2022. To this end, we applied the systematic literature review (SLR) methodology to retrieve and collate only the articles presenting and discussing service composition solutions tailored to produce digitally accessible services for consumption by people who suffer from an impairment or loss of some physical or mental functions. We searched six renowned bibliographic databases, particularly IEEE Xplore, Web of Science, Springer Link, ACM Library, ScienceDirect, and Google Scholar, to synthesize a final pool of 38 related articles. Our survey contributes a comprehensive taxonomy of service composition solutions, techniques, and practices that are utilized to create assistive technologies and services. The seven-facet taxonomy helps researchers and practitioners to quickly understand and analyze the fundamental conceptualizations and characteristics of accessible service composition for people with disabilities. Key findings showed that services are fused to assist disabled persons to carry out their daily activities, mainly in smart homes and ambient intelligent environments. Despite the emergence of immersive technologies (e.g., wearable computing), user-service interactions are enabled primarily through tactile and speech modalities. Service descriptions mainly incorporate functional features (e.g., performance, latency, and cost) of service quality, largely ignoring accessibility features. Moreover, the outstanding research problems revolve around (1) the unavailability of assistive services datasets, (2) the underspecification of accessibility aspects of disabilities, (3) the weak adoption of accessible and universal design practices, (4) the abstraction of service composition approaches, and (5) the rare experimental testing of composition approaches with disabled users. We conclude our survey with a set of guidelines to realize effective assistive service composition in IoT and cloud environments. Researchers and practitioners are advised to create assistive services that support the social relationships of disabled users and model their accessibility needs as part of the quality of service (QoS). Moreover, they should exploit AI/ML models to address the evolving requirements of disabled users in their unique environments. Furthermore, weaknesses of service composition solutions and research challenges are exposed as notable opportunities for future research.

A Two-Phase Machine Learning Framework for Context-Aware Service Selection to Empower People with Disabilities

The use of software and IoT services is increasing significantly among people with special needs, who constitute 15% of the world's population. However, selecting appropriate services to create a composite assistive service based on the evolving needs and context of disabled user groups remains a challenging research endeavor. Our research applies a scenario-based design technique to contribute (1) an inclusive disability ontology for assistive service selection, (2) semi-synthetic generated disability service datasets, and (3) a machine learning (ML) framework to choose services adaptively to suit the dynamic requirements of people with special needs. The ML-based selection framework is applied in two complementary phases. In the first phase, all available atomic tasks are assessed to determine their appropriateness to the user goal and profiles, whereas in the subsequent phase, the list of service providers is narrowed by matching their quality-of-service factors against the context and characteristics of the disabled person. Our methodology is centered around a myriad of user characteristics, including their disability profile, preferences, environment, and available IT resources. To this end, we extended the widely used QWS V2.0 and WS-DREAM web services datasets with a fusion of selected accessibility features. To ascertain the validity of our approach, we compared its performance against common multi-criteria decision making (MCDM) models, namely AHP, SAW, PROMETHEE, and TOPSIS. The findings demonstrate superior service selection accuracy in contrast to the other methods while ensuring accessibility requirements are satisfied.

An Ensemble Learning Based Classification Approach for the Prediction of Household Solid Waste Generation

With the increase in urbanization and smart cities initiatives, the management of waste generation has become a fundamental task. Recent studies have started applying machine learning techniques to prognosticate solid waste generation to assist authorities in the efficient planning of waste management processes, including collection, sorting, disposal, and recycling. However, identifying the best machine learning model to predict solid waste generation is a challenging endeavor, especially in view of the limited datasets and lack of important predictive features. In this research, we developed an ensemble learning technique that combines the advantages of (1) a hyperparameter optimization and (2) a meta regressor model to accurately predict the weekly waste generation of households within urban cities. The hyperparameter optimization of the models is achieved using the Optuna algorithm, while the outputs of the optimized single machine learning models are used to train the meta linear regressor. The ensemble model consists of an optimized mixture of machine learning models with different learning strategies. The proposed ensemble method achieved an R2 score of 0.8 and a mean percentage error of 0.26, outperforming the existing state-of-the-art approaches, including SARIMA, NARX, LightGBM, KNN, SVR, ETS, RF, XGBoosting, and ANN, in predicting future waste generation. Not only did our model outperform the optimized single machine learning models, but it also surpassed the average ensemble results of the machine learning models. Our findings suggest that using the proposed ensemble learning technique, even in the case of a feature-limited dataset, can significantly boost the model performance in predicting future household waste generation compared to individual learners. Moreover, the practical implications for the research community and respective city authorities are discussed.

Biomarkers of systemic inflammation predict survival with first-line immune checkpoint inhibitors in non-small-cell lung cancer

INTRODUCTION

Pembrolizumab is an established first-line option for patients with advanced non-small-cell lung cancer (NSCLC) expressing programmed death-ligand 1 ≥50%. Durable responses are seen in a subset of patients; however, many derive little clinical benefit. Biomarkers of the systemic inflammatory response predict survival in NSCLC. We evaluated their prognostic significance in patients receiving first-line pembrolizumab for advanced NSCLC.

METHODS

Patients treated with first-line pembrolizumab for advanced NSCLC with programmed death-ligand 1 expression ≥50% at two regional Scottish cancer centres were identified. Pretreatment inflammatory biomarkers (white cell count, neutrophil count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, albumin, prognostic nutritional index) were recorded. The relationship between these and progression-free survival (PFS) and overall survival (OS) were examined.

RESULTS

Data were available for 219 patients. On multivariate analysis, albumin and neutrophil count were independently associated with PFS (P < 0.001, P = 0.002, respectively) and OS (both P < 0.001). A simple score combining these biomarkers was explored. The Scottish Inflammatory Prognostic Score (SIPS) assigned 1 point each for albumin <35 g/l and neutrophil count >7.5 × 10⁹/l to give a three-tier categorical score. SIPS predicted PFS [hazard ratio 2.06, 95% confidence interval (CI) 1.68-2.52 (P < 0.001)] and OS [hazard ratio 2.33, 95% CI 1.86-2.92 (P < 0.001)]. It stratified PFS from 2.5 (SIPS2), to 8.7 (SIPS1) to 17.9 months (SIPS0) (P < 0.001) and OS from 5.1 (SIPS2), to 12.4 (SIPS1) to 28.7 months (SIPS0) (P < 0.001). The relative risk of death before 6 months was 2.96 (95% CI 1.98-4.42) in patients with SIPS2 compared with those with SIPS0-1 (P < 0.001).

CONCLUSIONS

SIPS, a simple score combining albumin and neutrophil count, predicts survival in patients with NSCLC receiving first-line pembrolizumab. Unlike many proposed prognostic scores, SIPS uses only routinely collected pretreatment test results and provides a categorical score. It stratifies survival across clinically meaningful time periods that may assist clinicians and patients with treatment decisions. We advocate validation of the prognostic utility of SIPS in this and other immune checkpoint inhibitor treatment settings.

Leaf cell membrane stability-based mechanisms of zinc nutrition in mitigating salinity stress in rice

Excess salt affects about 955 million ha of arable land worldwide, and 49% of agricultural land is Zn-deficient. Soil salinity and zinc deficiency can intensify plant abiotic stress. The mechanisms by which Zn can mitigate salinity effects on plant functions are not well understood. We conducted an experiment to determine how Zn and salinity effects on rice plant retention of Zn, K⁺ and the salt ion Na⁺ affect chlorophyll formation, leaf cell membrane stability and grain yield. We examined the mechanisms of Zn nutrition in mitigating salinity stress by examining plant physiology and nutrition. We used native Zn-deficient soils (control), four salinity (EC) and Zn treatments - Zn 10 mg·kg^-1 (Zn₁₀ ), EC 5 dS·m^-1 (EC₅ ), Zn₁₀ +EC₅ and Zn₁₅ +EC₅ , a coarse rice (KS-282) and a fine rice (Basmati-515) in the study. Our results showed that Zn alone (Zn₁₀ ) significantly increased rice tolerance to salinity stress by promoting Zn/K⁺ retention, inhibiting plant Na⁺ uptake and enhancing leaf cell membrane stability and chlorophyll formation in both rice cultivars in native alkaline, Zn-deficient soils (P < 0.05). Further, under the salinity treatment (EC₅ ), Zn inputs (10-15 mg·kg^-1 ) could also significantly promote rice plant Zn/K⁺ retention and reduce plant Na⁺ uptake, and thus increased leaf cell membrane stability and grain yield. Coarse rice was more salinity-tolerant than fine rice, having significantly higher Zn/K⁺ nutrient retention. The mechanistic basis of Zn nutrition in mitigating salinity impacts was through promoting plant Zn/K⁺ uptake and inhibiting plant Na⁺ uptake, which could result in increased plant physiological vigour, leaf cell membrane stability and rice productivity.

Structural changes of the choroid in sarcoid- and tuberculosis-related granulomatous uveitis

AIM

The aim of this study is to characterise the choroidal features of patients diagnosed with sarcoid- and tuberculosis (TB)-associated granulomatous uveitis using spectral domain optical coherence tomography (OCT).

METHODS

Twenty-seven patients (27 eyes) diagnosed with sarcoid- (13 eyes) and TB (14 eyes)-related uveitis were included in this retrospective, cross-sectional study. Over a six-month period, patients diagnosed with sarcoid and TB granulomatous uveitis were scanned using enhanced depth imaging OCT. Clinical and demographical characteristics were recorded, including the method of diagnosis, disease activity, site of inflammation (anterior or posterior), treatments, and visual acuity (VA). Manual segmentation of the choroidal layers was performed using custom image analysis software.

RESULTS

The main outcome measure was OCT-derived thickness measurements of the choroid and choroidal sublayers (Haller's large vessel and Sattler's medium vessel layers) at the macula region. The ratio of Haller's large vessel to Sattler's medium vessel layer was significantly different at the total macula circle in eyes diagnosed with TB uveitis (1.47 (=140.71/95.72 μm)) compared with sarcoid uveitis (1.07 (=137.70/128.69 μm)) (P=0.001). A thinner choroid was observed in eyes with a VA ≥0.3 LogMAR (Snellen 6/12; 198.1 μm (interquartile range (IQR)=147.0-253.4 μm) compared with those with VA <0.3 LogMAR (292.4 μm (IQR=240.1-347.6 μm)) at the total macula circle (P=0.004). At the foveal central subfield, the median choroidal thickness was 336.8 μm (IQR=272.3-375.4 μm) in active compared with 239.3 μm (IQR=195.3-330.9 μm) in quiescent disease (P=0.04).

CONCLUSION

A disproportionately enlarged Sattler's layer may indicate a diagnosis of sarcoid-related uveitis, and choroidal thickening may be a feature of active granulomatous uveitis.

Defining response to anti-VEGF therapies in neovascular AMD

The introduction of anti-vascular endothelial growth factor (anti-VEGF) has made significant impact on the reduction of the visual loss due to neovascular age-related macular degeneration (n-AMD). There are significant inter-individual differences in response to an anti-VEGF agent, made more complex by the availability of multiple anti-VEGF agents with different molecular configurations. The response to anti-VEGF therapy have been found to be dependent on a variety of factors including patient's age, lesion characteristics, lesion duration, baseline visual acuity (VA) and the presence of particular genotype risk alleles. Furthermore, a proportion of eyes with n-AMD show a decline in acuity or morphology, despite therapy or require very frequent re-treatment. There is currently no consensus as to how to classify optimal response, or lack of it, with these therapies. There is, in particular, confusion over terms such as 'responder status' after treatment for n-AMD, 'tachyphylaxis' and 'recalcitrant' n-AMD. This document aims to provide a consensus on definition/categorisation of the response of n-AMD to anti-VEGF therapies and on the time points at which response to treatment should be determined. Primary response is best determined at 1 month following the last initiation dose, while maintained treatment (secondary) response is determined any time after the 4th visit. In a particular eye, secondary responses do not mirror and cannot be predicted from that in the primary phase. Morphological and functional responses to anti-VEGF treatments, do not necessarily correlate, and may be dissociated in an individual eye. Furthermore, there is a ceiling effect that can negate the currently used functional metrics such as >5 letters improvement when the baseline VA is good (ETDRS>70 letters). It is therefore important to use a combination of both the parameters in determining the response.The following are proposed definitions: optimal (good) response is defined as when there is resolution of fluid (intraretinal fluid; IRF, subretinal fluid; SRF and retinal thickening), and/or improvement of >5 letters, subject to the ceiling effect of good starting VA. Poor response is defined as <25% reduction from the baseline in the central retinal thickness (CRT), with persistent or new IRF, SRF or minimal or change in VA (that is, change in VA of 0+4 letters). Non-response is defined as an increase in fluid (IRF, SRF and CRT), or increasing haemorrhage compared with the baseline and/or loss of >5 letters compared with the baseline or best corrected vision subsequently. Poor or non-response to anti-VEGF may be due to clinical factors including suboptimal dosing than that required by a particular patient, increased dosing intervals, treatment initiation when disease is already at an advanced or chronic stage), cellular mechanisms, lesion type, genetic variation and potential tachyphylaxis); non-clinical factors including poor access to clinics or delayed appointments may also result in poor treatment outcomes. In eyes classified as good responders, treatment should be continued with the same agent when disease activity is present or reactivation occurs following temporary dose holding. In eyes that show partial response, treatment may be continued, although re-evaluation with further imaging may be required to exclude confounding factors. Where there is persistent, unchanging accumulated fluid following three consecutive injections at monthly intervals, treatment may be withheld temporarily, but recommenced with the same or alternative anti-VEGF if the fluid subsequently increases (lesion considered active). Poor or non-response to anti-VEGF treatments requires re-evaluation of diagnosis and if necessary switch to alternative therapies including other anti-VEGF agents and/or with photodynamic therapy (PDT). Idiopathic polypoidal choroidopathy may require treatment with PDT monotherapy or combination with anti-VEGF. A committee comprised of retinal specialists with experience of managing patients with n-AMD similar to that which developed the Royal College of Ophthalmologists Guidelines to Ranibizumab was assembled. Individual aspects of the guidelines were proposed by the committee lead (WMA) based on relevant reference to published evidence base following a search of Medline and circulated to all committee members for discussion before approval or modification. Each draft was modified according to feedback from committee members until unanimous approval was obtained in the final draft. A system for categorising the range of responsiveness of n-AMD lesions to anti-VEGF therapy is proposed. The proposal is based primarily on morphological criteria but functional criteria have been included. Recommendations have been made on when to consider discontinuation of therapy either because of success or futility. These guidelines should help clinical decision-making and may prevent over and/or undertreatment with anti-VEGF therapy.

Diagnostic features of the autoimmune retinopathies

The term autoimmune retinopathy encompasses a spectrum of rare autoimmune diseases that affect retinal function, often but not exclusively at the level of the photoreceptor. They typically present with painless visual loss, which may be accompanied by normal fundus examination. Some are progressive, often rapidly. They present a diagnostic challenge because there are no standardised clinical or laboratory based diagnostic criteria. Included within the spectrum are cancer-associated retinopathy, melanoma-associated retinopathy and presumed non-paraneoplastic autoimmune retinopathy. Differentiation from other retinopathies can be challenging, with overlap in symptoms, signs, and investigation findings, and an absence of pathognomonic features. However, technological developments in ophthalmic imaging and serological investigation over the past decade are adding novel dimensions to the investigation and classification of patients with these rare diseases. This review addresses the clinical, imaging, and serological features of the autoimmune retinopathies, and discusses the relative strengths and limitations of candidate diagnostic features.

Ranibizumab for the treatment of choroidal neovascularisation secondary to pathological myopia: interim analysis of the REPAIR study

AIMS

To evaluate the efficacy and safety of intravitreal ranibizumab in patients with choroidal neovascularisation secondary to pathological myopia (myopic CNV). Data are from a pre-planned, 6-month interim analysis.

METHODS

Phase II, open-label, single arm, multicentre, 12-month study, recruiting patients (aged ≥18 years) with active primary or recurrent subfoveal or juxtafoveal myopic CNV, with a best-corrected visual acuity (BCVA) score of 24-78 Early Treatment Diabetic Retinopathy Study (ETDRS) letters in the study eye and a diagnosis of high myopia of at least -6 dioptres. Patients received 0.5 mg ranibizumab administered intravitreally to the study eye, followed by monthly injections given as needed (based on a predefined algorithm) for up to 11 months.

RESULTS

At 6 months, mean BCVA improved from baseline by 12.2 letters, as did central macular thickness (in this interim analysis defined as a measure of either central subfield macular thickness or centre point macular thickness) from baseline by 108 μm in the 48 study eyes of 48 patients. Fewer patients had centre-involving intraretinal oedema (13.0% vs 91.5%), intraretinal cysts (10.9% vs 57.4%), or subretinal fluid (13.0% vs 66.0%) at 6 months than at baseline. Patients received a mean of 1.9 retreatments, were satisfied with ranibizumab treatment, and well being was maintained. No new safety signals were identified.

CONCLUSIONS

Results from the planned interim analysis support the role of ranibizumab in the treatment of myopic CNV, with excellent efficacy achieved with a low number of injections and few serious adverse events.

Ranibizumab for the treatment of choroidal neovascularisation secondary to pathological myopia: interim analysis of the REPAIR study

AIMS

To evaluate the efficacy and safety of intravitreal ranibizumab in patients with choroidal neovascularisation secondary to pathological myopia (myopic CNV). Data are from a pre-planned, 6-month interim analysis.

METHODS

Phase II, open-label, single arm, multicentre, 12-month study, recruiting patients (aged ≥18 years) with active primary or recurrent subfoveal or juxtafoveal myopic CNV, with a best-corrected visual acuity (BCVA) score of 24-78 Early Treatment Diabetic Retinopathy Study (ETDRS) letters in the study eye and a diagnosis of high myopia of at least -6 dioptres. Patients received 0.5 mg ranibizumab administered intravitreally to the study eye, followed by monthly injections given as needed (based on a predefined algorithm) for up to 11 months.

RESULTS

At 6 months, mean BCVA improved from baseline by 12.2 letters, as did central macular thickness (in this interim analysis defined as a measure of either central subfield macular thickness or centre point macular thickness) from baseline by 108 μm in the 48 study eyes of 48 patients. Fewer patients had centre-involving intraretinal oedema (13.0% vs 91.5%), intraretinal cysts (10.9% vs 57.4%), or subretinal fluid (13.0% vs 66.0%) at 6 months than at baseline. Patients received a mean of 1.9 retreatments, were satisfied with ranibizumab treatment, and well being was maintained. No new safety signals were identified.

CONCLUSIONS

Results from the planned interim analysis support the role of ranibizumab in the treatment of myopic CNV, with excellent efficacy achieved with a low number of injections and few serious adverse events.

Recurrence pattern in squamous cell carcinoma of skin of lower extremities and abdominal wall (Kangri cancer) in Kashmir valley of Indian subcontinent: impact of various treatment modalities

BACKGROUND

The spectrum of skin cancer in Kashmir valley is drastically different from the rest of the country. Maxwell was the first to report skin cancer of lower extremities in Kashmiri population, developing on/over erythema ab igne, and attributed it to the use/or exposure of Kangri. These tumors have an aggressive biological behavior with a substantial risk of loco-regional metastasis in 30-50% cases. Because of unique geographical distribution of Kangri cancer, there is dearth of literature regarding the natural history, loco-regional and distant metastatic pattern and treatment recommendations in these tumors.

AIMS

To study the metastatic pattern of these skin tumors and to assess the impact of various treatment modalities and use of prophylactic nodal treatment in this clinical entity.

METHODS

The retrospective study (study period 1993-2005) included 266 patients of squamous cell carcinoma of skin of lower extremities and abdominal wall. Two hundred and forty-four cases with a follow-up of 2-7 years were included for final analysis with stress on loco-regional relapse pattern and methods of treatment evolved and used at our institute from time to time. Statistical analysis was done using yates corrected Chi-square test and odds ratio analysis.

RESULTS

Our results favor the use of post operative radiotherapy to primary and prophylactic treatment of regional nodes on the lines of head and neck tumors in these cases.

CONCLUSION

Post operative radiotherapy significantly decreases the loco-regional recurrences and a trial of prophylactic nodal irradiation is justified in a selected group of such patients.

An enhanced backbone-assisted reliable framework for wireless sensor networks

An extremely reliable source to sink communication is required for most of the contemporary WSN applications especially pertaining to military, healthcare and disaster-recovery. However, due to their intrinsic energy, bandwidth and computational constraints, Wireless Sensor Networks (WSNs) encounter several challenges in reliable source to sink communication. In this paper, we present a novel reliable topology that uses reliable hotlines between sensor gateways to boost the reliability of end-to-end transmissions. This reliable and efficient routing alternative reduces the number of average hops from source to the sink. We prove, with the help of analytical evaluation, that communication using hotlines is considerably more reliable than traditional WSN routing. We use reliability theory to analyze the cost and benefit of adding gateway nodes to a backbone-assisted WSN. However, in hotline assisted routing some scenarios where source and the sink are just a couple of hops away might bring more latency, therefore, we present a Signature Based Routing (SBR) scheme. SBR enables the gateways to make intelligent routing decisions, based upon the derived signature, hence providing lesser end-to-end delay between source to the sink communication. Finally, we evaluate our proposed hotline based topology with the help of a simulation tool and show that the proposed topology provides manifold increase in end-to-end reliability.

Age-related macular degeneration: diagnosis and management

BACKGROUND

Age-related macular degeneration (AMD) is a leading cause of blind registration in Western Europe and the third leading cause of blindness worldwide.

METHODS

The management of AMD is discussed with a review of current and new treatments.

RESULTS

Although there is no treatment for advanced dry AMD (geographic atrophy), there have been considerable advances in the management of neovascular AMD (nAMD). Established therapies for nAMD include laser photocoagulation and photodynamic therapy (PDT), but these have largely been superseded by agents which block the action of vascular endothelial growth factor (anti-VEGF agents). Current preventative strategies involve cessation of smoking and use of specific nutritional supplements to reduce the risk of developing nAMD.

CONCLUSIONS

There have been exciting advances in the treatment of nAMD and increased understanding of the genetics and pathogenic mechanisms involved will hopefully lead to the development of new therapies in the future.

Late onset vitreoretinal complications of regressed retinopathy of prematurity

AIM

To report the clinical findings, management, and outcomes in eyes undergoing surgery for regressed retinopathy of prematurity (ROP) with vitreoretinal complications.

METHOD

Retrospective review of 40 eyes of 32 patients with regressed ROP who presented between 1989 and 2001 at two UK referral centres.

RESULTS

Of 29 eyes presenting with rhegmatogenous retinal detachment (RRD), 15 initially underwent a scleral buckling procedure and 14 initially underwent vitrectomy with or without additional buckling. Primary surgery was anatomically successful in 11/15 eyes that underwent a non-vitrectomy retinal detachment repair and 8/14 that required vitrectomy. The final reattachment rate after reoperation was 28/29 eyes. Median visual acuity improved from 6/60 to 6/36 following retinal detachment repair. A further 11 eyes of eight patients from this series underwent prophylactic surgery, laser, or cryotherapy for predisposing vitreoretinal pathology and/or retinal breaks, all of which were stabilised.

CONCLUSIONS

In eyes with RRD and signs of regressed ROP successful reattachment of the retina can be achieved using either vitrectomy or external surgery with an associated overall improvement in visual acuity. A range of external and closed microsurgical approaches is required to effectively deal with the diverse manifestations of regressed ROP.

Systemic disorders associated with detachment of the neurosensory retina and retinal pigment epithelium

Serous detachment of the neurosensory retina and of the retinal pigment epithelium is a rare event in the course of systemic disease. Retinal pigment epithelial detachments usually occur in association with serous retinal detachments, although, in some cases, they also may be observed as an isolated finding. In a number of patients, the initial pigment epithelial detachment may be at the origin of a later-developing serous detachment. Diagnosis of a serous detachment still is made clinically, although optical coherence tomography recently has allowed the detection of clinically occult serous elevations of the retina. The underlying mechanisms of subretinal exudation are thought to include choroidal vascular perfusion and permeability changes, which result in increased choroidal interstitial fluid with further extension into the subretinal space. These changes are mostly incurred in the course of systemic inflammatory and infectious diseases such as sarcoidosis, Vogt-Koyanagi-Harada disease, and cytomegalovirus infection, and also in association with disorders resulting in the acute occlusion of the precapillary choroidal arterioles by fibrin-platelet thrombi. Collagen vascular diseases, disorders associated with disseminated intravascular coagulopathy, and malignant hypertension fall into this category. Hypercortisolism, renal disease, and, very rarely, malignant disease also have been implicated in the development of serous retinal detachment. Therapy of the serous detachments consists primarily of treating the underlying systemic disease.

Increased polymorphonuclear leucocyte rigidity in HIV infected individuals

AIM

Individuals with human immunodeficiency virus (HIV) infection were evaluated for evidence of abnormal polymorphonuclear leucocyte (PMN) rigidity, which can alter capillary blood flow.

METHODS

The transit time of individual PMN through 8 microm pores in a cell transit analyser was used as a measure of cell rigidity. PMN transit time was compared between HIV infected individuals (n=45) with and without CMV retinitis and HIV negative controls (n=17).

RESULTS

Transit times were longer for PMN from HIV infected individuals than for PMN from controls (p<0.001). PMN from HIV infected individuals with CMV retinitis (n=13) had longer transit times than PMN from those without CMV retinitis (n=32, p<0.001). Transit times were longer in HIV infected individuals with lower CD4+ T lymphocyte counts (p<0.001). Regression analysis indicated that the relation between transit times and the presence of CMV retinitis could not be explained solely on the basis of low CD4+ T lymphocytes. In HIV infected individuals, mean transit time was not correlated with age, blood pressure, or serum creatinine, cholesterol, or triglycerides.

CONCLUSIONS

HIV infected individuals appear to have increased PMN rigidity, a cellular change that might be involved in the pathogenesis of HIV related retinal microvasculopathy. PMN rigidity appears to be related to severity of immune dysfunction. PMN rigidity may remain high in patients with CMV retinitis after elevations of CD4+ T lymphocyte counts that result from potent antiretroviral therapy.

Quantitative cytomegalovirus DNA level in the blood and its relationship to cytomegalovirus retinitis in patients with acquired immune deficiency syndrome

OBJECTIVE

A pilot study was performed to determine whether relationships exist between changes in a quantitative solution hybridization assay for cytomegalovirus (CMV) DNA in the blood and development of CMV retinitis, development of nonocular CMV disease, or reactivation of pre-existing CMV retinitis lesions.

DESIGN

Observational case series.

PARTICIPANTS

Two groups of human immunodeficiency virus-infected patients: 10 CMV antibody-positive patients with CD4+ T-lymphocyte counts of less than 50 ml and no CMV disease at baseline and 11 patients with CMV retinitis but no extraocular CMV disease at baseline.

INTERVENTION

Quantitative changes in leukocyte-associated CMV DNA levels were observed over time. Anti-CMV therapies were based on clinical findings only.

MAIN OUTCOME MEASURES

Development of CMV end-organ disease or change in activity of pre-existing CMV retinitis lesions was measured.

RESULTS

Among patients with no CMV disease at baseline, four had CMV disease develop during follow-up (three cases of CMV retinitis, one case of presumed CMV esophagitis); all had CMV DNA levels greater than 5000 genomes/ml before the onset of CMV disease. The remaining six patients had levels less than 5000 genomes/ml throughout follow-up (P = 0.05). Among patients with CMV retinitis at baseline, all whose CMV DNA blood levels rose more than tenfold had extraocular CMV disease or reactivation of CMV retinitis develop. Raised CMV DNA blood levels were not seen in every patient with clinical reactivation of CMV retinitis.

CONCLUSION

Elevated or rising CMV DNA blood levels appear to be associated with the development of CMV disease in individuals with low CD4+ T-lymphocyte counts. In patients with CMV retinitis, rising levels appear to be associated with the development of extraocular CMV disease or reactivation of CMV retinitis. Conversely, reactivation of CMV retinitis also may occur in the absence of changes in CMV DNA blood levels. Further studies are warranted to determine whether changes in CMV blood levels can be used as a guide for preemptive therapy to prevent reactivation of CMV retinitis lesions or to help choose between local and systemic therapy for management of reactivations.

Chronic multifocal retinal infiltrates in patients infected with human immunodeficiency virus

PURPOSE

To describe the clinical features of a disorder characterized by chronic multifocal retinal infiltrates and uveitis in individuals with human immunodeficiency virus (HIV) disease.

METHODS

We reviewed the medical records of HIV-infected patients with multifocal retinal infiltrates of unknown cause seen by investigators at four institutions. The following data were collected: demographic characteristics, presenting signs and symptoms, laboratory test results, and course of disease.

RESULTS

We identified 26 HIV-infected patients (50 involved eyes) with this syndrome. Median CD4+ T-lymphocyte count at presentation was 272 per microl (range, 7 to 2,118 per microl). The most common presenting symptom was floaters. Median visual acuity of involved eyes at presentation was 20/20 (range, 20/15 to 20/100) and remained stable (median, 20/20; range, 20/15 to 20/70) after a median follow-up period of 9 months (range, 0 to 110 months). Typical retinal lesions were gray-white or yellow, irregular in shape, and less than 200 microm in greatest dimension. All were located in the midperiphery or anterior retina and enlarged slowly or remained static in size. Mild to moderate anterior chamber or vitreous humor inflammatory cells were present in 47 of 50 eyes (26 of 26 patients). Retinal lesions possibly responded to zidovudine but not to acyclovir or ganciclovir. Anterior chamber and vitreous humor inflammatory reactions responded to topical or periocular injections of corticosteroid.

CONCLUSIONS

Uveitis with chronic multifocal retinal infiltrates is a distinct clinical entity of unknown cause that occurs in HIV-infected patients. Retinal lesions may respond to antiretroviral therapy. Visual prognosis is good.

Prophylactic argon laser retinopexy prior to removal of silicone oil: a pilot study

BACKGROUND

Removal of silicone oil following successful retinal detachment surgery is usually performed in an attempt to prevent the complications of silicone oil; however, removal of the oil may result in retinal redetachment.

PURPOSE

The purpose of this study was to determine whether argon laser retinopexy, 3-6 weeks prior to the removal of silicone oil, reduces the rate of retinal detachment following silicone oil removal.

METHODS

A total of 31 eyes of 31 consecutive patients were followed up for a 12 month period after the removal of silicone oil. All patients had undergone retinal reattachment surgery resulting in a clinically attached retina with the absence of residual retinal traction prior to silicone oil removal. A study group of 15 of the 31 eyes received two rows of 360 degrees of peripheral argon laser retinopexy 3-6 weeks before removal of the silicone oil. The 16 eyes of the previous 16 consecutive patients, who underwent removal of silicone oil without argon laser retinopexy, were used as a control group.

RESULTS

In the study group 1 of 15 eyes (6.7%) redetached following the removal of silicone oil and 4 of 16 (25%) redetached in the control group during the 12 month follow-up period from operation.

CONCLUSIONS

Prophylactic argon laser retinopexy applied 3-6 weeks before the removal of silicone oil appears to reduce the retinal redetachment rate. A larger prospective randomised trial is needed to confirm these findings.

Uveitis as the only clinical manifestation of poststreptococcal syndrome

PURPOSE

To report a case of streptococcal infection of the upper respiratory tract in which bilateral anterior uveitis was the only complication.

METHOD

Serologic documentation of post-streptococcal immune disease. The duration of inflammation was consistent with other forms of poststreptococcal immune disease.

RESULTS

Bilateral anterior uveitis was treated with corticosteroids alone and resolved without ophthalmic complications.

CONCLUSION

Bilateral anterior uveitis may be the only clinical manifestation of poststreptococcal syndrome.

Is the first day postoperative review necessary after cataract extraction?

BACKGROUND

In current ophthalmic practice day-case surgery cataract patients are conventionally discharged and then reviewed the following morning thus limiting the advantages of what 'true' day-case surgery strives to achieve. The aim of this study was to see if there was a difference in outcome between 'true' day-case cataract surgery and non-day-care surgery.

METHODS

A total of 387 consecutive cataract operations were followed, comprising 122 local anaesthetic day-cases, 149 local anaesthetic non-day-cases, 63 general anaesthetic non-day-cases, and 53 general anaesthetic day-cases.

RESULTS

Although not randomised the groups were comparable with respect to age, operator grade, sex, presence of diabetes, anaesthetic type, pre and postoperative visual acuities, and time to first planned outpatient visit. There were 10 early postoperative complications in the day-case group (5.71% of total) and 14 in the non-day-case group (6.6% of total), the commonest complications in both groups were raised intraocular pressure, corneal oedema, and wound leaks. One patient in each group had an early complication that necessitated attending the casualty department. The visual outcomes in both groups were comparable.

CONCLUSIONS

These findings suggest that there were no preventable complications within the constraints of the number of operations studied and that no additional risk is attached to 'true' day-case surgery relative to non-day-case surgery.