Spectroscopic and thermodynamic characterization of the interaction between sugar-stabilised silver nanoparticles and wheat germ agglutinin (WGA), a chitin binding lectin.

Nanomaterials have lately been investigated in agriculture as eco-friendly and effective antifungal agents. Many nanomaterials, notably metal nanoparticles, have strong antifungal properties. Among metal nanoparticles, Ag nanoparticles have received the most attention as antifungal agents. Many plant lectins have been identified as antifungal agents. Conjugating AgNPs with antifungal lectins is thus expected to improve Ag nanoparticle antifungal efficacy. Understanding the molecular interactions and physical features of lectin-sugar-stabilised nanoparticle conjugates is critical for future applications. WGA has traditionally been used as an anti-tumor and antifungal agent. To investigate the prospect of developing an effective biocompatible antifungal system with applications in medicine and agriculture, fluorescence spectroscopy was used to investigate the interaction between sugar-stabilised silver nanoparticles and WGA. During the association, protein intrinsic fluorescence emission is suppressed by about ∼15 % at saturation, with no significant shift in fluorescence emission maxima. Binding tests reveal a strong bond. Stern-Volmer analysis of the quenching data indicates that the interaction happens via a static quenching process that induces complex formation. The study of hemagglutination activity and interaction experiments in the presence of particular sugar shows that the lectin's sugar-binding site is separate from the nanoparticle-binding site, and cell recognition is conserved in the lectin-nanoparticle complex. The Van't Hoff plot thermodynamic parameters suggest that the contact is hydrophobic. The fact that ΔGo is negative shows that the binding is a spontaneous process. CD spectroscopy experiments reveal that the lectin's secondary structure is not affected while binding to the nanoparticle. Our findings suggest that a stable WGA-silver nanoparticle combination may emerge for a variety of applications.

Enzymatic and biochemical properties of lens in age-related cataract versus diabetic cataract: A narrative review.

Cataract is the leading cause of blindness worldwide. There is an increased incidence of cataract formation in the diabetic population due to several factors. Diabetes mellitus accelerates the development of cataract. Oxidative stress results in most of the diabetic complications including diabetic cataract. Oxidative stress leading to the expression of various enzymes has also been proven as crucial for cataractous changes in the lens in old age. A narrative review was undertaken to investigate the expression of different biochemical parameters as well as enzymes in diabetic and senile cataracts. Identification of these parameters is crucial for the prevention and treatment of blindness. Combinations of MeSH terms and key words were used to do literature search in PubMed. The search resulted 35 articles and among them, 13 were relevant to the topic and were included in synthesis of results. Seventeen different types of enzymes were identified in the senile and diabetic cataracts. Seven biochemical parameters were also identified. Alteration in biochemical parameters and expression of enzymes were comparable. Majority of the parameters were raised or altered in diabetic cataract compared to senile cataract.

Cataract surgical training among residents in India: Results from a survey.

Purpose: To assess the quantum of cataract surgical training opportunities for trainees enrolled in ophthalmology residency programs in India. Methods: An anonymous online survey was sent across to resident ophthalmologists across India through various social media platforms. The results were tabulated and analyzed. Results: A total of 740 resident ophthalmologists participated in the survey. In all, 40.1% (297/740) were independently performing cataract surgeries. Of those who were not performing independent cataract surgeries, 62.5% (277/443) were in the third year of residency. A significantly higher proportion of trainees who were not operating independent cataract surgeries were enrolled in MD/MS programs as compared with DNB courses (65.6% vs. 43.7%; P < 0.0001). Of those who were operating independent cases; 97.1% had exposure to manual small incision cataract surgery (MSICS), whereas only 14.1% performed phacoemulsification. It was noted that 31.3% of residents reported that on an average a trainee in their training program performed less than 100 independent cataract surgeries throughout the residency. Apart from cataract surgery, the most performed surgeries by residents were pterygium excision (85.3%), followed by enucleation/evisceration (68.1%). When it came to training aids, 47.2% (349/740) of the respondents reported no access to wet lab, animal/cadaver eyes, or surgical simulators for training. Conclusion: The amount of surgical exposure in terms of cataract surgery across residency programs in India is low with most of the ophthalmology residents who participated in this survey not operating cataracts independently; even in their final year of residency. Exposure to phacoemulsification in residency programs is very limited across the country. Although some programs do provide well-rounded surgical exposure to trainees, such centers are scarce; the stark variations in infrastructure, training opportunities, and surgical numbers warrant an overhaul in the structure and curriculum of residency programs in India.

Interaction of sugar stabilised silver nanoparticles with Momordica charantia seed lectin, a type II ribosome inactivating protein.

Sugar-stabilised nanomaterials have received a lot of attention in cancer therapy in recent years due to their pronounced application as specific targeting agents and maximizing their therapeutic potential while bypassing off-target effects. Lectins, the carbohydrate-binding proteins, are capable of binding to receptors present on the target cell/tissue and interact with transformed glycans better than normal cells. Besides some of the lectins exhibit anticancer activity. Conjugating sugar-stabilised NPs with lectins there for is expected to multiply the potential for the early diagnosis of cancer cells and the specific release of drugs into the tumor site. Because of the prospective applications of lectin-sugar-stabilised nanoparticle conjugates, it is important to understand their molecular interaction and physicochemical properties. Momordica charantia Seed Lectin (MCL) is a type II RIP and has been known as an anti-tumor agent. Investigation of the interaction between sugar-stabilised silver nanoparticles and MCL has been performed by fluorescence spectroscopy to explore the possibility of creating an effective biocompatible drug delivery system against cancer cells. In this regard interaction between lectin and NPs should be well-preserved, while recognizing the specific cell surface sugar. Therefore experiments were carried out in the presence and absence of specific sugar galactose. Protein intrinsic fluorescence emission is quenched at ~ 20% at saturation during the interaction without any significant shift in fluorescence emission maximum. Binding experiments reveal a good affinity. Tetrameric MCL binds to a single nanoparticle. Stern-Volmer analysis of the quenching data suggests that the interaction is via static quenching leading to complex formation. Hemagglutination experiments together with interaction studies in the presence of specific sugar show that the sugar-binding site of the lectin is distinct from the nanoparticle-binding site and cell recognition is very much intact even after binding to AgNPs. Our results propose the possibility of developing MCL-silver nanoparticle conjugate with high stability and multiple properties in the diagnosis and treatment of cancer.

Artificial intelligence based health indicator extraction and disease symptoms identification using medical hypothesis models.

Patient health record analysis models assist the medical field to understand the current stands and medical needs. Similarly, collecting and analyzing the disease features are the best practice for encouraging medical researchers to understand the research problems. Various research works evolve the way of medical data analysis schemes to know the actual challenges against the diseases. The computer-based diagnosis models and medical data analysis models are widely applied to have a better understanding of different diseases. Particularly, the field of medical electronics needs appropriate health indicator extraction models in near future. The existing medical schemes support baseline solutions but lack optimal hypothesis-based solutions. This work describes the optimal hypothesis model and Akin procedures for health record users, to aid health sectors in clinical decision-making on health indications. This work proposes Medical Hypothesis and Health Indicators Extraction from Electronic Medical Records (EMR) and International Classification of Diseases (ICD-10) patient examination database using the Akin Method and Friendship method. In this Health Indicators and Disease Symptoms Extraction (HIDSE), the evidence checking procedures find and collect all possible medical evidence from the existing patient examination report. Akin Method is making the hypothesis decision from count-based evidence principles. The health indicators extraction scheme extracts all relevant information based on the health indicators query and partial input. Similarly, the friendship method is used for making information associations between medical data attributes. This Akin-Friendship model helps to build hypothesis structures and trait-based feature extraction principles. This is called as Composite Akin Friendship Model (CAFM). This proposed model consists of various test cases for developing the medical hypothesis systems. On the other hand, it provides limited accuracy in disease classification. In this regard, the proposed HIDSE implements Deep Learning (DL) based Akin Friendship Method (DLAFM) for improving the accuracy of this medical hypothesis model. The proposed DLAFM, Convolutional Neural Networks (CNN) associated Legacy Prediction Model for Health Indicator (LPHI) is developed to tune the CAFM principles. The results show the proposed health indicator extraction scheme has 8-10% of better system performance than other existing techniques.

Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme.

Purpose: The need for computerized medical assistance for accurate detection of brain hemorrhage from Computer Tomography (CT) images is more mandatory than conventional clinical tests. Recent technologies and advanced computerized algorithms follow Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques to improve medical diagnosis platforms. This technology is making the diagnosis practice of brain issues easier for medical practitioners to analyze and identify diseases with an assured degree of precision and performance. Methods: As the existing CT image analysis models use standard procedures to detect hemorrhages, the need for DL-based data analysis is essential to provide more accurate results. Generally, the existing techniques are limited with image training efficiency, image filtering procedures, and runtime system tuning modules. On the scope, this work develops a DL-based automated analysis of CT scan slices to find various levels of brain hemorrhages. Notably, this proposed system integrates Convolutional Neural Network (CNN) and Generative Adversarial Network (GAN) architectures as Integrated Generative Adversarial-Convolutional Imaging Model (IGACM) for extracting the CT image features for detecting brain hemorrhages. Results: This system produces good results and takes lesser training time than existing techniques. This proposed system effectively works over CT images and classifies the abnormalities with more accuracy than current techniques. The experiments and results deliver the optimal detection of hemorrhages with better accuracy. It shows that the proposed system works with 5% to 10% of the better performance compared to other diagnostic techniques. Conclusion: The complex nature of CT images leads to noncorrelated feature complexities in diagnosis models. Considering the issue, the proposed system used GAN-based effective sampling techniques for enriching complex image samples into CNN training phases. This concludes the effective contribution of the proposed IGACM technique for detecting brain hemorrhages than the existing diagnosis models.

Knowledge of features of inflammatory back pain in primary care in the West Midlands: a cross-sectional survey in the United Kingdom.

KEY MESSAGES: There is a relative lack of confidence among GPs in the assessment and management of IBP vs. mechanical back pain. A simple screening tool for SpA, applicable in primary care urgently needs to be developed. It is reasonable for patients with symptoms suggestive of inflammatory back pain to be referred to secondary care without further investigations. The objective of this study was to assess current practice of our local general practitioners (GPs) in using clinical features, as well as radiological and laboratory investigations to assess patients with IBP. An online, observational questionnaire-based survey was done in 10 West Midlands CCGs including disparate geographical and socioeconomic areas. The survey consisted of 23 questions based on Calin, Berlin and ESSG Criteria for spondyloarthropathies. GPs were asked to rate the importance of a range of symptoms as indications of IBP IBP (10 point scale, range 1-10), and what their views were on which were the most important treatments for patients with suspected inflammatory back pain(4 point scale, range 1-4). The 4 most important symptoms for predicting inflammatory back pain according to our local cohort of GPs were 'morning stiffness' 'sleep disturbances caused by back pain' 'insidious onset' and 'age of onset' < 45. Among the treatment options, NSAIDs were ranked as the most important treatment option for IBP. DMARDS were rated as the next most important treatment option, ahead of physiotherapy and anti-TNF therapy. This study has highlighted relative lack of confidence among GPs in the assessment of IBP. Whether this reflects a need for education or poor performance of these questions in primary care populations requires further study.

Pulmonary arterial hypertension in SLE: what do we know?

Pulmonary hypertension (PH) can occur at any time during the course of systemic lupus erythematosus (SLE), and can be independent of lupus disease activity in other systems. The pathogenesis of PH in SLE can be multifactorial, but pulmonary arterial hypertension (PAH) is the commonest cause of PH in SLE. The international PH registries have published that approximately 15% of connective tissue disease-associated PH is lupus related in their cohorts. As the symptoms of PH in SLE can be mild and non-specific in early stages, an increasing awareness of this devastating complication is essential for early diagnosis. Echocardiographic evaluation of several right heart variables in addition to systolic pulmonary artery pressure estimation reduces false positive rates for PH detection. Antiphospholipid antibodies may predict SLE-PAH. Prompt treatment of PAH with newer PAH therapy as well as immunosuppression can reduce morbidity and prolong survival. The survival in SLE-associated PAH is better compared with systemic sclerosis-associated PH but worse than idiopathic PAH. Pregnancy in SLE-PAH can result in a fatal outcome, especially in severe and poorly controlled PH at onset.

First report of an alphasatellite associated with Okra enation leaf curl virus.

An alphasatellite DNA associated with Okra enation leaf curl virus (OELCuV) which causes enation and leaf curling in okra (Abelmoschus esculentus) plants was characterized. The full-length DNA comprises 1,350 nucleotides and shows typical genome organization of an alphasatellite. It shows the highest nucleotide sequence identity (79.7 %) to Hollyhock yellow vein virus-associated symptomless alphasatellite (HoYVSLA). This is the first report of the association of an alphasatellite with OELCuV from India.

A systematic approach to data-driven modeling and soft sensing in a full-scale plant.

The well-known mathematical modeling and neural networks (NNs) methods have limitations to incorporate the key process characteristics at the wastewater treatment plants (WWTPs) which are complex, non-stationary, temporal correlation, and nonlinear systems. In this study, a systematic methodology of NNs modeling which can be efficiently included in the key modeling information of the WWTPs is performed by selecting the temporal effect of the hydraulics based on multi-way principal components analysis (MPCA). The proposed method is applied for modeling wastewater quality of a full-scale plant, which is a Daewoo nutrient removal (DNR) process. Through the experimental results in a full-scale plant, the efficiency of the proposed method is evaluated and the prediction capability is highly improved by the inclusion of the hydraulics term due to the optimized structure of neural networks.

Effects of rituximab on resistant SLE disease including lung involvement.

We present a retrospective review of 11 patients with refractory systemic lupus erythematosus (SLE) treated with rituximab after failing corticosteroids and at least one other immunosuppressive drug. We measured clinical response using the Classic British Isles Lupus Assessment Group (BILAG) index, serum complement and reduction in maintenance prednisolone dose. B cells were measured using flow cytometry, and lung function testing was used to assess severe pulmonary disease (three patients). The median patient age was 42 years (range, 25-64) with median disease duration 6 years (range, 2-12). In all, 10 of 11 patients responded initially, with median global BILAG reduction of 7.5 at 6 months (P = 0.007), with loss of all A and B scores by 7 months. Rituximab treatment was associated with normalisation of complement (C3 P = 0.008, C4 P = 0.018) and reduction in steroid requirement, median reduction 15 mg/day (P = 0.036). In 9 of 10 patients who responded, all other immunosuppressants were stopped. There was no significant difference in anti-dsDNA antibody titres in these responders, but they were negative or had low titres at baseline. B-cell depletion continued for median 4 months (range, 2-9), and disease flare occurred at a median 6.6 months (range, 1.5-23) and was preceded by B-cell recovery in all but two patients. Rituximab was beneficial in refractory SLE including severe neurological and cardiorespiratory disease by inducing disease remission, allowing withdrawal of other agents and reduction in steroid requirement. Rituximab appeared to stabilise and possibly improve progressive lung disease.

BILAG-2004 index captures systemic lupus erythematosus disease activity better than SLEDAI-2000.

OBJECTIVE: To assess the reliability of Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)-2000 index in routine practice and its ability to capture disease activity as compared with the British Isles Lupus Assessment Group (BILAG)-2004 index. METHODS: Patients with systemic lupus erythematosus from 11 centres were assessed separately by two raters in routine practice. Disease activity was assessed using the BILAG-2004 and SLEDAI-2000 indices. The level of agreement for items was used to assess the reliability of SLEDAI-2000. The ability to detect disease activity was assessed by determining the number of patients with a high activity on BILAG-2004 (overall score A or B) but low SLEDAI-2000 score (<6) and number of patients with low activity on BILAG-2004 (overall score C, D or E) but high SLEDAI-2000 score (>or=6). Treatment of these patients was analysed, and the increase in treatment was used as the gold standard for active disease. RESULTS: 93 patients (90.3% women, 69.9% Caucasian) were studied: mean age was 43.8 years, mean disease duration 10 years. There were 43 patients (46.2%) with a difference in SLEDAI-2000 score between the two raters and this difference was >or=4 in 19 patients (20.4%). Agreement for each of the items in SLEDAI-2000 was between 81.7 and 100%. 35 patients (37.6%) had high activity on BILAG-2004 but a low SLEDAI-2000 score, of which 48.6% had treatment increased. There were only five patients (5.4%) with low activity on BILAG-2004 but a high SLEDAI-2000 score. CONCLUSIONS: SLEDAI-2000 is a reliable index to assess systemic lupus erythematosus disease activity but it is less able than the BILAG-2004 index to detect active disease requiring increased treatment.

Direct healthcare costs and predictors of costs in patients with primary Sjogren's syndrome.

OBJECTIVES: To analyse the healthcare usage, direct healthcare costs and predictors of cost in primary Sjögren's syndrome (PSS) in the UK and to compare the findings with the data from healthy control groups and rheumatoid arthritis (RA) patients. METHODS: A total of 129 patients with PSS (American-European criteria), 91 with RA and 92 controls, were included in the study. All groups were age-matched females and all completed questionnaires on health status (SF-36) and healthcare utilization (economic component of the Stanford Health Assessment Questionnaire). Annual direct healthcare costs were calculated (and expressed in 2004 UK pound sterling) and predictors of costs for each patient group were determined by regression analyses. Age, health status, disease duration and anti-Ro/La antibody positivity were used as potential predictor variables. RESULTS: Mean age was similar in the PSS (59.2 yrs, S.D. 11.6), RA (60.3 yrs, S.D. 10.5) and control groups (57.7 yrs, S.D. 12.5). The mean disease duration was 5.4 yrs (S.D. 4.8) in the PSS group and 13.4 yrs (S.D. 11.4) in the RA group. The mean annual total direct cost per patient [95% confidence interval (CI)] was 2188 pounds sterling (1831 and 2546 pounds sterling) in the PSS group, 2693 pounds sterling(2069 and 3428 pounds sterling) in the RA group and 949 pounds sterling (741 and 1156 pounds sterling) in the control group. The costs in the PSS group were greater than for the RA and control groups for visits to all healthcare professionals (total) as well as visits to the dentist, dental hospital and ophthalmologist. The costs in the PSS and RA groups were higher than in controls for diagnostic tests and visits to hospital and the accident and emergency (A&E) department. The PSS group also incurred higher costs than controls, but lower costs than the RA group, for visits to a rheumatologist, urine and blood tests, assistive devices and drug therapy. Regression analysis identified the SF-36 physical function subscale as the best predictor of costs in PSS patients as well as controls and the mental health subscale in RA patients. CONCLUSION: This is the first study to evaluate direct healthcare costs in patients with PSS. PSS has a significant impact on the healthcare system, similar to that of RA, by more than doubling costs compared with control patients.