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This research emphasizes mainly on the need for software security. Softwares are developing at a faster pace so it is required to impose security on them in order to secure them from cybercrimes. Softwares have been facing problems by the attackers who are constantly kept on breaching the Data. Therefore this survey comprises the phases that are an integral part of the SDLC from the security point of views such as Design and testing phase. Moreover, it quests upon the data related to threats and attacks. Not only this, but it also involves the prerequisites that have to be determined before developing the software like, what are the approaches that should be followed and what are the best suitable designs to secure the software?

Background The role of radiation therapy (RT) following breast-conserving surgery (BCS) in ductal carcinoma in situ (DCIS) remains controversial. Trials have not identified a low-risk cohort, based on clinicopathologic features, who do not benefit from RT. A biosignature (DCISionRT®) that evaluates recurrence risk has been developed and validated. We evaluated the impact of DCISionRT on clinicians’ recommendations for adjuvant RT. Methods The PREDICT study is a prospective, multi-institutional, observational registry in which patients underwent DCISionRT testing. The primary endpoint was to identify the percentage of patients where testing led to a change in RT recommendations. Results Overall, 539 women were included in this study. Pre DCISionRT testing, RT was recommended to 69% of patients; however, post-testing, a change in the RT recommendation was made for 42% of patients compared with the pre-testing recommendation; the percentage of women who were recommended RT decreased by 20%. For women initially recommended not to receive an RT pre-test, 35% had their recommendation changed to add RT following testing, while post-test, 46% of patients had their recommendation changed to omit RT after an initial recommendation for RT. When considered in conjunction with other clinicopathologic factors, the elevated DCISionRT score risk group (DS > 3) had the strongest association with an RT recommendation (odds ratio 43.4) compared with age, grade, size, margin status, and other factors. Conclusions DCISionRT provided information that significantly changed the recommendations to add or omit RT. Compared with traditional clinicopathologic features used to determine recommendations for or against RT, the factor most strongly associated with RT recommendations was the DCISionRT result, with other factors of importance being patient preference, tumor size, and grade.

Adipose tissue (AT) plays a crucial role in maintaining me tabolic homeostasis by storing lipids and glucose from circulation as intracellular fat. As peripheral tissues like AT become insulin resistant, decompensation of blood glucose levels occurs causing type 2 diabetes (T2D). Currently, glycocalyx modulating as a pharmacological treatment strategy to improve glucose homeostasis in T2D patients is underexplored. Here, we show a novel role for cell surface heparan sulfate (HS) in establishing glucose uptake capacity and metabolic utilization in differentiated adipocytes. Using a combination of chemical and genetic interventions, we identified that HS modulates this metabolic phenotype by attenuating levels of Wnt signaling during adipogenesis. By engineering the glycocalyx of preadipocytes with exogenous synthetic HS mimetics, we were able to enhance glucose clearance capacity after differentiation through modulation of Wnt ligand availability. These findings establish the cellular glycocalyx as a possible new target for therapeutic intervention in T2D patients by enhancing glucose clearance capacity independent of insulin secretion.SIGNIFICANCEMetabolic disorders associated with the Western-style diet, such as type 2 diabetes, are among the main drivers of mortality in the US and globally, with more than 380 million people currently affected by this disease worldwide. However, treatment options for type 2 diabetes are currently limited to management of caloric uptake and expenditure, with none able to reverse the condition long-term. The ability to reprogram adipose tissues to improve their overall capacity to clear glucose may provide one such opportunity. Here we provide evidence that glycocalyx remodeling in pre-adipocytes with heparan sulfate mimetics will alter their differentiation program by modulating Wnt signaling to produce adipocytes with increased glucose uptake and utilization.

PurposeTo evaluate the effect of signal strength (SS) on optical coherence tomography (OCT) parameters, and devise an algorithm to adjust the effect, when acceptable SS cannot be obtained.Methods5085 individuals (9582 eyes), aged ≥40 years from the Singapore Epidemiology of Eye Diseases population-based study were included. Everyone underwent a standardised ocular examination and imaging with Cirrus HD-OCT. Effect of SS was evaluated using multiple structural breaks linear mixed-effect models. Expected change for increment in SS between 4 and 10 for individual parameter was calculated. Subsequently we devised and evaluated an algorithm to adjust OCT parameters to higher SS.ResultsAverage retinal nerve fibre layer (RNFL) thickness showed shift of 4.11 µm from SS of 5 to 6. Above 6, it increased by 1.72 and 3.35 µm to 7 and 8; and by 1.09 µm (per unit increase) above 8 SS. Average ganglion cell-inner plexiform layer (GCIPL) thickness shifted 5.15 µm from SS of 5 to 6. Above 6, increased by 0.94 µm from 7 to 8; and by 0.16 µm (per unit increase) above 8 SS. When compared with reference in an independent test set, the algorithm produced less systemic bias. Algorithm-adjusted average RNFL was 0.549 µm thinner than the reference, while the unadjusted one was 2.841 µm thinner (pConclusionsOCT parameters can be adjusted for poor SS using an algorithm. This can potentially assist in diagnosis and monitoring of glaucoma when scans with acceptable SS cannot be acquired from patients in clinics.

The Onduo Virtual Diabetes Clinic (VDC) for people with type 2 diabetes (T2D) combines a mobile app, remote lifestyle coaching, connected devices, and live video consultations with board-certified endocrinologists. Adults with T2D (n = 594) who were evaluated by a VDC endocrinologist, remotely prescribed and mailed a real-time continuous glucose monitoring (rtCGM) device and used ≥1 sensor completed a CGM satisfaction questionnaire. The CGM satisfaction score was 4.5 ± 0.8 out of 5. Most respondents (94.7%) agreed/strongly agreed that they were comfortable inserting the sensor remotely and that rtCGM use improved understanding of the impact of eating (97.0%), increased diabetes knowledge (95.7%), and helped improve diabetes control when not wearing the sensor (79.4%). HbA1c (n = 372) decreased from 7.7% ± 1.6% to 7.1% ± 1.2% (P

AimsTo use machine learning (ML) to determine the relative contributions of modifiable and non-modifiable clinical, metabolic, genetic, lifestyle and socioeconomic factors on the risk of major eye diseases.MethodsWe conducted analyses in a cross-sectional multi-ethnic population-based study (n=10 033 participants) and determined a range of modifiable and non-modifiable risk factors of common eye diseases, including diabetic retinopathy (DR), non-diabetic-related retinopathy (NDR); early and late age-related macular degeneration (AMD); nuclear, cortical and posterior subcapsular (PSC) cataract; and primary open-angle (POAG) and primary angle-closure glaucoma (PACG). Risk factors included individual characteristics, metabolic profiles, genetic background, lifestyle patterns and socioeconomic status (n~100 risk factors). We used gradient boosting machine to estimate the relative influence (RI) of each risk factor.ResultsAmong the range of risk factors studied, the highest contributions were duration of diabetes for DR (RI=22.1%), and alcohol consumption for NDR (RI=6.4%). For early and late AMD, genetic background (RI~20%) and age (RI~15%) contributed the most. Axial length was the main risk factor of PSC (RI=30.8%). For PACG, socioeconomic factor (mainly educational level) had the highest influence (20%). POAG was the disease with the highest contribution of modifiable risk factors (cumulative RI~35%), followed by PACG (cumulative RI ~30%), retinopathy (cumulative RI between 20% and 30%) and late AMD (cumulative RI ~20%).ConclusionThis study illustrates the utility of ML in identifying factors with the highest contributions. Risk factors possibly amenable to interventions were intraocular pressure (IOP) and Body Mass Index (BMI) for glaucoma, alcohol consumption for NDR and levels of HbA1c for DR.

Big data is the fuel of mankind's fourth industrial revolution. Coupled with new technology such as artificial intelligence and deep learning, the potential of big data is poised to be harnessed to its maximal in years to come. In ophthalmology, given the data-intensive nature of this specialty, big data will similarly play an important role. Electronic medical records, administrative and health insurance databases, mega national biobanks, crowd source data from mobile applications and social media, and international epidemiology consortia are emerging forms of "big data" in ophthalmology. In this review, we discuss the characteristics of big data, its potential applications in ophthalmology, and the challenges in leveraging and using these data. Importantly, in the next phase of work, it will be pertinent to further translate "big data" findings into real-world applications, to improve quality of eye care, and cost-effectiveness and efficiency of health services in ophthalmology.

The UK Biobank is an unprecedented resource for human disease research. In March 2019, 49,997 exomes were made publicly available to investigators. Here we note that thousands of variant calls are unexpectedly absent from this dataset, with 641 genes showing zero variation. We show that the reason for this was an erroneous read alignment to the GRCh38 reference. The missing variants can be recovered by modifying read alignment parameters to correctly handle the expanded set of contigs available in the human genome reference. Given the size and complexity of such population scale datasets, we propose a simple heuristic that can uncover systematic errors using summary data accessible to most investigators.