Classification of Lung Diseases Using an Attention-Based Modified DenseNet Model

Lung diseases represent a significant global health threat, impacting both well-being and mortality rates. Diagnostic procedures such as Computed Tomography (CT) scans and X-ray imaging play a pivotal role in identifying these conditions. X-rays, due to their easy accessibility and affordability, serve as a convenient and cost-effective option for diagnosing lung diseases. Our proposed method utilized the Contrast-Limited Adaptive Histogram Equalization (CLAHE) enhancement technique on X-ray images to highlight the key feature maps related to lung diseases using DenseNet201. We have augmented the existing Densenet201 model with a hybrid pooling and channel attention mechanism. The experimental results demonstrate the superiority of our model over well-known pre-trained models, such as VGG16, VGG19, InceptionV3, Xception, ResNet50, ResNet152, ResNet50V2, ResNet152V2, MobileNetV2, DenseNet121, DenseNet169, and DenseNet201. Our model achieves impressive accuracy, precision, recall, and F1-scores of 95.34%, 97%, 96%, and 96%, respectively. We also provide visual insights into our model's decision-making process using Gradient-weighted Class Activation Mapping (Grad-CAM) to identify normal, pneumothorax, and atelectasis cases. The experimental results of our model in terms of heatmap may help radiologists improve their diagnostic abilities and labelling processes.

Prospecting the Potential of Plant Growth-Promoting Microorganisms for Mitigating Drought Stress in Crop Plants

Drought is a global phenomenon affecting plant growth and productivity, the severity of which has impacts around the whole world. A number of approaches, such as agronomic, conventional breeding, and genetic engineering, are followed to increase drought resilience; however, they are often time consuming and non-sustainable. Plant growth-promoting microorganisms are used worldwide to mitigate drought stress in crop plants. These microorganisms exhibit multifarious traits, which not only help in improving plant and soil health, but also demonstrate capabilities in ameliorating drought stress. The present review highlights various adaptive strategies shown by these microbes in improving drought resilience, such as modulation of various growth hormones and osmoprotectant levels, modification of root morphology, exopolysaccharide production, and prevention of oxidative damage. Gene expression patterns providing an adaptive edge for further amelioration of drought stress have also been studied in detail. Furthermore, the practical applications of these microorganisms in soil are highlighted, emphasizing their potential to increase crop productivity without compromising long-term soil health. This review provides a comprehensive coverage of plant growth-promoting microorganisms-mediated drought mitigation strategies, insights into gene expression patterns, and practical applications, while also guiding future research directions.

Gas Sensing Properties of PLD Grown 2D SnS Film: Effect of Film Thickness, Metal Nanoparticle Decoration, and In Situ KPFM Investigation

This study employs novel growth methodologies and surface sensitization with metal nanoparticles to enhance and manipulate gas sensing behavior of two-dimensional (2D)SnS film. Growth of SnS films is optimized by varying substrate temperature and laser pulses during pulsed laser deposition (PLD). Thereafter, palladium (Pd), gold (Au), and silver (Ag) nanoparticles are decorated on as-grown film using gas-phase synthesis techniques. X-ray diffraction (XRD), Raman spectroscopy, and Field-emission scanning electron microscopy (FESEM) elucidate the growth evolution of SnS and the effect of nanoparticle decoration. X-ray photoelectron spectroscopy (XPS) analyses the chemical state and composition. Pristine SnS, Ag, and Au decorated SnS films are sensitive and selective toward NO2 at room temperature (RT). Ag nanoparticle increases the response of pristine SnS from 48 to 138% toward 2 ppm NO2, which indicates electronic and chemical sensitization effect of Ag. Pd decoration on SnS tunes its selectivity toward H2 gas with a response of 55% toward 70 ppm H2 and limit of detection (LOD) < 1 ppm. In situ Kelvin probe force microscopy (KPFM) maps the work function changes, revealing catalytic effect of Ag toward NO2 in Ag-decorated SnS and direct charge transfer between Pd and SnS during H2 exposure in Pd-decorated SnS.

A magnetic field augmented ultra-thin layer chromatography coupled surface enhanced Raman spectroscopy separation of hemozoin from bacterial mixture

Malaria is considered as one the most widespread disease with highest possibility of co-infection at all levels of the disease prognosis. Rapid detection and discrimination of malaria from other co-infections remains a challenge. Hemozoin is a metabolic biproduct of malaraia possessing paramagnetic property due to presence of iron at its centre. Here, we report a label free, rapid and highly sensitive magnetic field based ultra-thin layer chromatography (UTLC) coupled with surface enhanced Raman spectroscopy (SERS) technique for detection and separation of hemozoin from a bacterial mixture. Highly optimized silver nanorods chip fabricated using glancing angle deposition (GLAD) is explored for the UTLC-SERS separation. These chips possessing channel like characteristic and high surface to the volume ratio serve as excellent UTLC plates. The magnetic nature of hemozoin has been exploited for its separation from the mixture of P. aeruginosa (Gram-negative) and S. aureus (Gram-positive) by allocating a 0.6 T magnet over the UTLC flow setup. The solvent front migrated approximately to a distance of 13 mm from the sample point due to the magnetic environment. Spatially resolved SERS data was collected along the mobile phase and separation of mixture was confirmed. Further, staining of hemozoin, P. aeruginosa and S. aureus was done using methylene blue, acridine orange and rhodamine 6 G respectively. The separation was confirmed for the stained analytes. The present developed method provides plate height as low as 18 µm and hemozoin detection limit as <10 parasites/mL. Therefore, we establish a highly specific and sensitive technique capable of separating small amounts of bioanalytes, aiding in the removal of co-infections from the disease at a very early stage of infection.

Ag2Se Nanorod Arrays with Ultrahigh Room Temperature Thermoelectric Performance and Superior Mechanical Properties

Ag₂Se is an intriguing material for room-temperature energy harvesting. Herein, we report the fabrication of Ag₂Se nanorod arrays by glancing angle deposition technique (GLAD) followed by simple selenization in a two-zone furnace. Ag₂Se planar films of different thickness were also prepared. The unique tilted Ag₂Se nanorod arrays show excellent zT = 1.14 ± 0.09 and a power factor of 3229.21 ± 149.01 μW/m-K², respectively, at 300 K. The superior thermoelectric performance of Ag₂Se nanorod arrays compared to planar Ag₂Se films could be ascribed to the unique nanocolumnar architecture that not only facilitates efficient electron transport but also significantly scatters phonons at the interfaces. Furthermore, the nanoindentation measurements were performed to explore mechanical properties of the as-prepared films. The Ag₂Se nanorod arrays showed hardness values of 116.51 ± 4.25 MPa and elastic modulus of 10,966.01 ± 529.61 MPa, which are lowered by 51.8 and 45.6%, compared to Ag₂Se films, respectively. The synergetic dependence between the tilt structure and thermoelectric properties accompanied with the simultaneous improvement in mechanical properties opens a new avenue for the practical applications of Ag₂Se in next-generation flexible thermoelectric devices.

Mycorrhizae set the stage for plants to produce a higher production of biomolecules and stress-related metabolites: a sustainable alternative of agrochemicals to enhance the quality and yield of beetroot (Beta vulgaris L.)

Population explosions, environmental deprivation, and industrial expansion led to an imbalanced agricultural system. Non-judicial uses of agrochemicals have decreased agrodiversity, degraded agroecosystems, and increased the cost of farming. In this scenario, a sustainable agriculture system could play a crucial role; however, it needs rigorous study to understand the biological interfaces within agroecosystems. Among the various biological components with respect to agriculture, mycorrhizae could be a potential candidate. Most agricultural crops are symbiotic with arbuscular mycorrhizal fungi (AMF). In this study, beetroot has been chose to study the effect of different AMFs on various parameters such as morphological traits, biochemical attributes, and gene expression analysis (ALDH7B4 and ALDH3I1). The AMF Gm-Funneliformis mosseae (Glomus mosseae), Acaulospora laevis, and GG-Gigaspora gigantean were taken as treatments to study the effect on the above-mentioned parameters in beetroot. We observed that among all the possible combinations of mycorrhizae, Gm+Al+GG performed best, and the Al-alone treatment was found to be a poor performer with respect to all the studied parameters. This study concluded that the more the combinations of mycorrhizae, the better the results will be. However, the phenomenon depends on the receptivity, infectivity, and past nutrient profile of the soil.

A Comprehensive Survey of Deep Learning Techniques in Protein Function Prediction

Protein function prediction is a major challenge in the field of bioinformatics which aims at predicting the functions performed by a known protein. Many protein data forms like protein sequences, protein structures, protein-protein interaction networks, and micro-array data representations are being used to predict functions. During the past few decades, abundant protein sequence data has been generated using high throughput techniques making them a suitable candidate for predicting protein functions using deep learning techniques. Many such advanced techniques have been proposed so far. It becomes necessary to comprehend all these works in a survey to provide a systematic view of all the techniques along with the chronology in which the techniques have advanced. This survey provides comprehensive details of the latest methodologies, their pros and cons as well as predictive accuracy, and a new direction in terms of interpretability of the predictive models needed to be ventured by protein function prediction systems.

A SERS based clinical study on HIV-1 viral load quantification and determination of disease prognosis

In resource limited settings, a cost-effective point-of-care diagnostic testing possessing the characteristics of detecting the minimum viral load of a malady like human immunodeficiency virus (HIV) acquired immune deficiency syndrome (AIDS) is a pressing priority. The present work describes a novel, rapid and field-deployable method using surface enhanced Raman spectroscopy (SERS) for detection and prognosis of HIV positive clinical samples, in seven different viral load ranges varying between 200 and 1 million copies/ml. A relationship between the increasing and decreasing intensity peaks of HIV-1 was also established for quantitation efficacy of the handheld tool. Three different types of SERS substrates: single arm Ag nanorods, double arm Ag nanorods and Au sputtered single arm Ag nanorods were used and the obtained data was compared for the three substrates. It was demonstrated that maximum enhancement was obtained for Au sputtered Ag nanorods. Rigorous coupled wave analysis (RCWA) simulations were performed to study the 'hotspots' in three different SERS substrates. Further, to explore the utility of our platform and to differentiate between the clade specific X4 and R5 tropism, their corresponding SERS spectra were studied using HIV-1 strains belonging to four different HIV-1 subtypes (A, B, C and D) which showed a clear distinction, implying the usefulness of the platform in understanding the disease prognosis. Statistical analysis of the obtained SERS spectra using principal component analysis (PCA) showed good agreement with the experimental results, confirming the ability of SERS platform to quantitate HIV-1 viral load and distinguish HIV-1 strains on the basis of their SERS spectra.

Fuzzy-logic-based IoMT framework for COVID19 patient monitoring

Smart healthcare is an integral part of a smart city, which provides real time and intelligent remote monitoring and tracking services to patients and elderly persons. In the era of an extraordinary public health crisis due to the spread of the novel coronavirus (2019-nCoV), which caused the deaths of millions and affected a multitude of people worldwide in different ways, the role of smart healthcare has become indispensable. Any modern method that allows for speedy and efficient monitoring of COVID19-affected patients could be highly beneficial to medical staff. Several smart-healthcare systems based on the Internet of Medical Things (IoMT) have attracted worldwide interest in their growing technical assistance in health services, notably in predicting, identifying and preventing, and their remote surveillance of most infectious diseases. In this paper, a real time health monitoring system for COVID19 patients based on edge computing and fuzzy logic technique is proposed. The proposed model makes use of the IoMT architecture to collect real time biological data (or health information) from the patients to monitor and analyze the health conditions of the infected patients and generates alert messages that are transmitted to the concerned parties such as relatives, medical staff and doctors to provide appropriate treatment in a timely fashion. The health data are collected through sensors attached to the patients and transmitted to the edge devices and cloud storage for further processing. The collected data are analyzed through fuzzy logic in edge devices to efficiently identify the risk status (such as low risk, moderate risk and high risk) of the COVID19 patients in real time. The proposed system is also associated with a mobile app that enables the continuous monitoring of the health status of the patients. Moreover, once alerted by the system about the high risk status of a patient, a doctor can fetch all the health records of the patient for a specified period, which can be utilized for a detailed clinical diagnosis.

Secure data authentication and access control protocol for industrial healthcare system

Because of recent COVID-19 epidemic, the Internet-of-Medical-Things (IoMT) has acquired a significant impetus to diagnose patients remotely, regulate medical equipment, and track quarantined patients via smart electronic devices installed at the patient's end. Nevertheless, the IoMT confronts various security and privacy issues, such as entity authentication, confidentiality, and integrity of health-related data, among others, rendering this technology vulnerable to different attacks. To address these concerns, a number of security procedures based on traditional cryptographic approaches, such as discrete logarithm and integer factorization problems, have been developed. All of these protocols, however, are vulnerable to quantum attacks. This paper, in this context, presents a data authentication and access control protocol for IoMT systems that can withstand quantum attacks. A comprehensive formal security assessment demonstrates that the proposed algorithm can endure both current and future threats. In terms of data computing, transmission, and key storage overheads, it also surpasses other related techniques.

Artificial Intelligence in Accelerating Drug Discovery and Development

Drug discovery and development are critical processes that enable the treatment of wide variety of health-related problems. These are time-consuming, tedious, complicated, and costly processes. Numerous difficulties arise throughout the entire process of drug discovery, from design to testing. Corona Virus Disease 2019 (COVID-19) has recently posed a significant threat to global public health. SARS-Cov-2 and its variants are rapidly spreading in humans due to their high transmission rate. To effectively treat COVID-19, potential drugs and vaccines must be developed quickly. The advancement of artificial intelligence has shifted the focus of drug development away from traditional methods and toward bioinformatics tools. Computer-aided drug design techniques have demonstrated tremendous utility in dealing with massive amounts of biological data and developing efficient algorithms. Artificial intelligence enables more effective approaches to complex problems associated with drug discovery and development through the use of machine learning. Artificial intelligence-based technologies improve the pharmaceutical industry's ability to discover effective drugs. This review summarizes significant challenges encountered during the drug discovery and development processes, as well as the applications of artificial intelligence-based methods to overcome those obstacles in order to provide effective solutions to health problems. This may provide additional insight into the mechanism of action, resulting in the development of vaccines and potent substitutes for repurposed drugs that can be used to treat not only COVID-19 but also other ailments.

Is this question going to be closed? Answering question closibility on Stack Exchange

Community question answering sites (CQAs) are often flooded with questions that are never answered. To cope with the problem, experienced users of Stack Exchange are now allowed to mark newly posted questions as closed if they are of poor quality. Once closed, a question is no longer eligible to receive answers. However, identifying and closing subpar questions takes time. Therefore, the purpose of this article is to develop a supervised machine learning system that predicts question closibility, the possibility of a newly posted question to be eventually closed. Building on extant research on CQA question quality, the supervised machine learning system uses 17 features that were grouped into four categories, namely, asker features, community features, question content features and textual features. The performance of the developed system was tested on questions posted on Stack Exchange from 11 randomly chosen topics. The classification performance was generally promising and outperformed the baseline. Most of the measures of precision, recall, F1-score and area under the receiver operating characteristic curve (AUC) were above 0.90 irrespective of the topic of questions. By conceptualising question closibility, the article extends previous CQA research on question quality. Unlike previous studies, which were mostly limited to programming-related questions from Stack Overflow, this one empirically tests question closibility on questions from 11 randomly selected topics. The set of features used for classification offers a framework of question closibility that is not only more comprehensive but also more parsimonious compared with prior works.

Dronedarone versus sotalol in patients with atrial fibrillation: a systematic literature review and network meta-analysis

Background

There are limited comparative data on safety and efficacy within Vaughn Williams class III anti-arrhythmic drugs (AADs) for maintenance of sinus rhythm in adults with atrial fibrillation (AF).

Purpose

We sought to compare the safety and efficacy of dronedarone and sotalol, two commonly prescribed Vaughn Williams class III AADs with class II rate-controlling properties in patients with non-permanent AF.

Methods

A systematic literature review was conducted by searching MEDLINE®, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) up to June 15, 2021. Clinical trials and observational studies that evaluated safety and efficacy of dronedarone or sotalol in adults with AF were included. Where feasible, Bayesian random-effects network meta-analysis (NMA) was conducted to estimate comparative safety and efficacy. Where possible, sensitivity analyses were conducted by including only randomized controlled trials (RCTs).

Results

Of 3,581 records identified through database searches, 37 unique studies (23 RCTs, 13 observational studies, and 1 non-randomized trial) were included in the NMA. Dronedarone was associated with a statistically significantly lower risk of all-cause death versus sotalol in the all-studies NMA (hazard ratio [HR]: 0.38; 95% credible interval [CrI]: 0.19, 0.74; 22 studies); sensitivity analysis followed the same trend numerically (HR: 0.46; 95% CrI: 0.21, 1.02; 16 RCTs). Risk ratios of AF recurrence were not significantly different between dronedarone and sotalol in both all-studies and sensitivity analyses.

Conclusion

Dronedarone, compared with sotalol, was associated with significantly lowered risk of all-cause death in the analysis combining RCTs and observational studies, with no differences in AF recurrence observed between the two therapies. This meta-analysis provides a comprehensive assessment of safety and efficacy evidence useful in evaluating treatment options in AF.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): Sanofi

Unraveling Microbial Volatile Elicitors Using a Transparent Methodology for Induction of Systemic Resistance and Regulation of Antioxidant Genes at Expression Levels in Chili against Bacterial Wilt Disease

Microbial volatiles benefit the agricultural ecological system by promoting plant growth and systemic resistance against diseases without harming the environment. To explore the plant growth-promoting efficiency of VOCs produced by Pseudomonas fluorescens PDS1 and Bacillus subtilis KA9 in terms of chili plant growth and its biocontrol efficiency against Ralstonia solanacearum, experiments were conducted both in vitro and in vivo. A closure assembly was designed using a half-inverted plastic bottle to demonstrate plant–microbial interactions via volatile compounds. The most common volatile organic compounds were identified and reported; they promoted plant development and induced systemic resistance (ISR) against wilt pathogen R. solanacearum. The PDS1 and KA9 VOCs significantly increased defensive enzyme activity and overexpressed the antioxidant genes PAL, POD, SOD, WRKYa, PAL1, DEF-1, CAT-2, WRKY40, HSFC1, LOX2, and NPR1 related to plant defense. The overall gene expression was greater in root tissue as compared to leaf tissue in chili plant. Our findings shed light on the relationship among rhizobacteria, pathogen, and host plants, resulting in plant growth promotion, disease suppression, systemic resistance-inducing potential, and antioxidant response with related gene expression in the leaf and root tissue of chili.

Portable fiber-optic SPR platform for the detection of NS1-antigen for dengue diagnosis

Here, we present a portable, selective and cost-effective fiber-optic surface plasmon resonance (SPR) based platform for early detection of Dengue virus. NS1 protein was targeted as the biomarker of dengue. Antibody-antigen specific binding was exploited for NS1 antigen detection. The binding of antibody was assisted by a self-assembled monolayer of alkanethiols on the surface of silver-coated unclad fiber. A wavelength interrogation mode of SPR was utilized to detect NS1 antigen in the dynamic range of 0.2-2.0 μg/ml. The 40 nm thick silver coated optical fiber exhibited resonance wavelength around 500 nm and change in resonance wavelength was monitored for each attachment step on the fiber. The sensitivity at the lowest concentration of NS1 antigen was found to be 54.7 nm/(μg/ml). The limit of detection of the sensor was found to be 0.06 μg/ml, which lies in the physiological range of NS1 protein present in the infected blood, hence the present technique may provide a very early detection advantage. Real blood serum samples were also successfully tested on the set-up, confirming compatibility with the conventional methods. The presented field-deployable platform has wide applications in mass monitoring of dengue, such as during outbreaks and epidemics.

COVID-19 and cyberbullying: deep ensemble model to identify cyberbullying from code-switched languages during the pandemic

It has been declared by the World Health Organization (WHO) the novel coronavirus a global pandemic due to an exponential spread in COVID-19 in the past months reaching over 100 million cases and resulting in approximately 3 million deaths worldwide. Amid this pandemic, identification of cyberbullying has become a more evolving area of research over posts or comments in social media platforms. In multilingual societies like India, code-switched texts comprise the majority of the Internet. Identifying the online bullying of the code-switched user is bit challenging than monolingual cases. As a first step towards enabling the development of approaches for cyberbullying detection, we developed a new code-switched dataset, collected from Twitter utterances annotated with binary labels. To demonstrate the utility of the proposed dataset, we build different machine learning (Support Vector Machine & Logistic Regression) and deep learning (Multilayer Perceptron, Convolution Neural Network, BiLSTM, BERT) algorithms to detect cyberbullying of English-Hindi (En-Hi) code-switched text. Our proposed model integrates different hand-crafted features and is enriched by sequential and semantic patterns generated by different state-of-the-art deep neural network models. Initial experimental results of the proposed deep ensemble model on our code-switched data reveal that our approach yields state-of-the-art results, i.e., 0.93 in terms of macro-averaged F1 score. The dataset and codes of the present study will be made publicly available on the paper's companion repository [https://github.com/95sayanta/COVID-19-and-Cyberbullying].

Social media analytics for end-users' expectation management in information systems development projects

Purpose

This study, an exploratory research, aims to investigate social media users' expectations of information systems (IS) products that are conceived but not yet launched. It specifically analyses social media data from Twitter about forthcoming smartphones and smartwatches from Apple and Samsung, two firms known for their innovative gadgets.

Design/methodology/approach

Tweets related to the following four forthcoming IS products were retrieved from 1st January 2020 to 30th September 2020: (1) Apple iPhone 12 (6,125 tweets), (2) Apple Watch 6 (553 tweets), (3) Samsung Galaxy Z Flip 2 (923 tweets) and (4) Samsung Galaxy Watch Active 3 (207 tweets). These 7,808 tweets were analysed using a combination of the Natural Language Processing Toolkit (NLTK) and sentiment analysis (SentiWordNet).

Findings

The online community was quite vocal about topics such as design, camera and hardware specifications. For all the forthcoming gadgets, the proportion of positive tweets exceeded that of negative tweets. The most prevalent sentiment expressed in Apple-related tweets was neutral, but in Samsung-related tweets was positive. Additionally, it was found that the proportion of tweets echoing negative sentiment was lower for Apple compared with Samsung.

Originality/value

This paper is the earliest empirical work to examine the degree to which social media chatter can be used by project managers for IS development projects, specifically for the purpose of end-users' expectation management.

Local structure investigation of Co-Fe-Si-B ribbons by extended X-ray absorption fine-structure spectroscopy

In the present work, extended X-ray absorption fine-structure (EXAFS) investigations of Co₆₉Fe_xSi_21-xB₁₀ (x = 3, 5, 7) glassy ribbons were performed at the Co K-edge. The magnitude of the first peak of the Fourier transforms of the EXAFS signals is found to increase monotonically with increasing Si concentrations indicating the formation of the localized ordered structure at the atomic scale. The Co-Si coordination number (CN) increases at the expense of the CN of Co/Fe. Smaller interatomic distances are observed in the glassy phase compared with that in the crystalline phase which promotes the stability of the glassy phase. Calculations of the thermodynamic parameter (P_HSS), cohesive energy (E_C) and the atomic radius difference (δ) parameter show that the alloy composition Co₆₉Fe₃Si₁₈B₁₀ has a good glass-forming ability (GFA) with the highest CN of Si compared with other compositions. A linear correlation of CN with that of the GFA parameter (P_HSS) exists and the CN also plays a crucial role in the GFA of the glassy alloys. This parameter should be considered in developing different GFA criteria.

Portable and sensitive Ag nanorods based SERS platform for rapid HIV-1 detection and tropism determination

In this study, surface-enhanced Raman scattering (SERS) based field-deployable platform has been explored for early detection and distinction of the human immunodeficiency virus (HIV-1). A highly optimized silver nanorods array, fabricated using glancing angle deposition technique was used as SERS substrate. Distinct signature peaks for varying concentrations (10² to 10⁶ copies/mL) were identified in five different HIV-1 subtypes (A, B, C, D, and CRF02_AG). Binding of viruses directly with Ag nanorods without using antibodies or intermediate reagents is shown. The purified viruses were spiked in water and healthy plasma to capture pure HIV-1 peaks. Distinct peaks were also captured for the X4 and R5 tropic strains suggesting tropism based detection. The above data was further confirmed and analyzed statistically using a multivariate tool. Thus, the present study indicates the ability of the SERS platform to detect and differentiate the HIV-1 virus implying its further validation using clinical specimens and isolates.

SERS Platform for Dengue Diagnosis from Clinical Samples Employing a Hand Held Raman Spectrometer

Dengue is a serious global health concern especially in tropical and subtropical countries. About 2.5 billion of the world's population is at risk for dengue infection. Early diagnosis is the key to prevent the deterioration of health of the patient to severe illness. Laboratory diagnosis of dengue is essential for providing appropriate supportive treatment to dengue patients with febrile illness, which is difficult to diagnose clinically. Here, we demonstrate surface enhanced Raman scattering (SERS) based diagnosis of dengue virus in clinical blood samples collected from total of 102 subjects. All of the samples were well characterized by conventional NS1 antigen and IgM antibody ELISA kits. The silver nanorods array fabricated by glancing angle deposition technique were employed as SERS substrates. A small amount of patient blood serum (5 μL) was taken for analysis and the report was prepared within a minute. SERS spectra of pure NS1 protein as well as spiked in serum was also recorded separately. Principal component analysis (PCA) was employed as the statistical tool to differentiate dengue positive, dengue negative, and healthy subjects on the basis of their respective SERS spectra. This method provides a sensitive, rapid, and field deployable diagnosis of dengue at the early stage (within 5 days of the onset of symptoms).

P5684Left ventricular wall thickness measured with computed tomography stratifies the response to cardiac resynchronization therapy in patients with non-ischemic cardiomyopathy

Background

Cardiac resynchronization therapy (CRT) has provided benefit in selected heart failure (HF) patients. Unfortunately, up to 30% of device recipients do not benefit clinically from CRT. Left ventricular (LV) wall geometry analyzed using computed tomography (CT) has not been evaluated in the response to CRT. The objective of this study was to examine the association of LV wall thickness (WT) and the ability for reverse LV remodeling after CRT in non ischemic cardiomyopathy (NICM) patients.

Methods

In this prospective study, a total 54 patients (33 NICM) scheduled for CRT, underwent pre procedural CT. Reduced LV WT was defined as WT≤6mm and was quantified as a percentage of total LV area. End points were 6-month clinical and echocardiographic response to CRT (NYHA functional class, LV ejection fraction (LVEF), LV end-diastolic volume (LVEDV) and LV end-systolic volume (LVEDV)) and 2-year major adverse cardiac events (MACE). Of note, positive reduction was defined as in reduction LVESV and LVEDV by ≥15% and ≥10% respectively and ≥5% absolute increase in LVEF.

Results

The 33 NICM enrolled patients were divided in 3 groups according to the percentage of LV WT<6mm area: ≤20% (low LV WT area); 20–50% (moderate LV WT area) and ≥50% (high LV WT area). At 6 months, 78%, 67% and 25% of the patients experienced NYHA class improvement by ≥1 in the ≤20%, 20–50% and ≥50% group respectively. Furthermore, majority of patients in the ≤20% and 20–50% groups (92% and 75% respectively) had a significant improvement of their global assessment compared to only 38% in the ≥50% group. Additionally, low LV WT area group presented a significant LVEF, LVEDV and LVESV positive response rate (92%, 69% and 85% respectively). Patients included in the moderate and high groups exhibited gradually lower LVEF, LVEDV and LVESV positive response rate (42% and 50%; 67% and 50%; 75% and 50%, respectively). Notably, patients with the least LV WT (i.e ≥50% group) experienced significantly lower 2-years MACE survival free probability than other groups.

Left ventriculat segmentation

Conclusion

LV WT evaluated using CT could help to stratify the response to CRT in NICM patients.

P3804Left ventricular wall thickness measured with computed tomography predicts mitral regurgitation improvement in patients implanted with cardiac resynchronization therapy

Background

Secondary mitral regurgitation (MR) is common in heart failure (HF) patients and results in progressive left ventricular (LV) dilatation, papillary muscle (PM) displacement and mitral valve leaflet tethering. In selected HF patients, cardiac resynchronization therapy (CRT) has been proved to reduce MR by LV reverse remodeling, resynchronization of PM insertion site contraction and reduction in MV tenting area and inter PM distance. However, data regarding the impact of LV wall thickness (WT) on MR improvement are scarce.

Methods

In this prospective study, a total 54 patients scheduled for CRT, underwent pre procedural CT. Reduced LV WT was defined as WT<6mm and was quantified as a percentage of total LV area. LV was segmented in 17 segments to assess the number of LV segments with reduced WT. End point was 6-month echocardiographic MR improvement by ≥1 class. For this analysis, we focused on patient with mild (class 2) to severe (class 4) MR.

Results

Among the 54 patients, 38 (70.4%) had mild to severe MR at baseline and a total of 16 (42.1%) experienced MR improvement by ≥1 class at 6 months. there was no difference regarding the co-morbidities, electrocardiogram and echocardiographic parameters between patients with or without MR improvement. However, patients without MR improvement had significant higher NT-pro BNP level at baseline. Interestingly, patients without MR improvement had larger LVWT <6mm area (41.541.5±19.4 vs. 22.4±16.1%, p=0.003) associated with higher number of papillary muscle (PM) inserted in reduced LV WT area. In multivariate analysis, an area ≥25% of LVWT<6mm including at least 1 PM insertion was the only predictor of no MR improvement at 6 months (HR 18.4 (1.25–271.75), p=0.034). Lastly, patients with MR improvement had significant lower rate of basal segments with reduced WT, especially in the lateral location. Of note, patients with MR improvement exhibited fewer rate of postero-lateral WT <6mm segments.

Left ventriculat segmentation

Conclusion

LV WT evaluated using CT is a strong predictor of no MR improvement in HF patients with mild to severe MR and who scheduled for CRT implantation.

Photomechanical and Chemomechanical Actuation Behavior of Graphene-Poly(dimethylsiloxane)/Gold Bilayer Tube for Multimode Soft Grippers and Volatile Organic Compounds Detection Applications

Graphene polymers-based soft actuators driven by infrared (IR) light have attracted wide attention recently. However, the scientific fraternity is striving hard in unraveling the area of actuators that could be triggered by IR light along with chemicals. The fabricating methodology of multiresponsive soft actuators based on graphene nanoplatelets (GNPs)-poly(dimethylsiloxane) (PDMS) nanocomposite/gold bilayers, ensuring large, fast, and reversible response, has been illustrated. The actuators display a novel dual-mode operation as photomechanical and chemomechanical actuation. The actuators are realized by depositing a thin film (100 nm) of gold on GNP-PDMS nanocomposite films resulting tubular structure on account of thermal residual stress. The actuation response of this structure upon its exposure to IR light and chemicals was measured in terms of percentage opening and degree of unscroll, respectively. The three-dimensional tubular structure is transformed into a two-dimensional sheet within 8 s under IR light irradiation. The same structures were also tested in various organic solvents like methanol, ethanol, acetone, isopropyl alcohol, and aldehydes, but the actuation has been observed only in acetone and aldehydes. This tubular actuator unscrolls completely and then scrolls in opposite direction along with tube axis shift through 90° during its exposure to acetone (liquid/vapors) and aldehydes. Few applications of these actuators, such as multimode soft grippers for on-demand capture/release of objects (with weight 1.2 times the actuator's own weight) and volatile organic compounds detection module, have been demonstrated. The combination of surface micromachining techniques of microelectromechanical systems process with this smart material may find applications in drug-delivery systems with precise control, soft robotics, and noninvasive diagnosis of diabetes and breast/lung cancers.

Sunlight-driven eco-friendly smart curtain based on infrared responsive graphene oxide-polymer photoactuators

Photomechanical actuation is the conversion of light energy into mechanical energy through some smart materials. Infrared-responsive smart materials have become an emerging field of research due to easy availability and eco-friendly nature of their stimulus in the form of sunlight, which contains about 50% of near-infrared(nIR) making these materials useful at macro-scale photoactuator applications. Here, we demonstrate fabrication of highly versatile nIR triggered photoactuators based on graphene oxide/polycarbonate bilayers that offers fast, low-cost fabrication, large deflection, reversible actuation and wavelength-selective response. The photoactuators are realized by vacuum filtration of graphene oxide/water dispersion through polycarbonate membrane resulting graphene oxide/polymer bilayer structure. The photoactuation response was measured in the form of deflection from equilibrium position as a result of infrared-irradiation. The deflection is caused by the generated thermal stress at the interface of bilayers due to mismatch of thermal expansion coefficient as a results of nIR absorption by graphene oxide and subsequent temperature rise. A maximum deflection of 12 mm (circular-shaped structure with diameter 28 mm) with corresponding bending curvature of 0.33 cm-1 was shown by this photoactuator for illumination intensity of 106 mW/cm2. Few applications of these photoactuators such as sunlight-driven smart curtain, infrared actuated curtain and self-folding box are also demonstrated.

An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India

Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with respect to the image data resolution (spatial and spectral) as well as the sensor platform position in space. Using Resourcesat-2 satellite data and Normalized Difference Vegetation Index (NDVI), this pilot scale study compared traditional linear and nonlinear models with an artificial intelligence-based non-parametric technique, i.e. artificial neural network (ANN) for formulation of the best-fit model to determine AGB of forest of the Bundelkhand region of India. The results confirmed the superiority of ANN over other models in terms of several statistical significance and reliability assessment measures. Accordingly, this study proposed the use of ANN instead of traditional models for determination of AGB and other bio-physical parameters of any dry deciduous forest of tropical sub-humid or semi-arid area. In addition, large numbers of sampling sites with different quadrant sizes for trees, shrubs, and herbs as well as application of LiDAR data as predictor variable were recommended for very high precision modelling in ANN for a large scale study.

ZnO-Nanowires-Coated Smart Surface Mesh with Reversible Wettability for Efficient On-Demand Oil/Water Separation

The rapid industrial growth has led to the large production of oily wastewater. Treatment of oily wastewater is an inevitable challenge to manage the greater demand of clean water for the rapidly growing population and economy. In the present work, we have developed a smart surface mesh with reversible wetting properties via a simple, ecofriendly, and scalable approach for on-demand oil-water separation. ZnO nanowires (NWs) obtained from the chemical vapor deposition method were coated on a stainless steel (SS) mesh. The as-synthesized ZnO-NWs-coated mesh shows superhydrophilic/underwater superoleophobic behavior. This mesh works in "water-removing" mode, where the superhydrophilic as well as underwater superoleophobic nature allows the water to permeate easily through the mesh while preventing oil. The wetting property of ZnO-NWs-coated mesh can be switched easily from superhydrophilic to superhydrophobic state and vice versa by simply annealing it at 300 °C alternatively under hydrogen and oxygen environment. The separation is solely driven by gravity. Thus, the reversible wettability of ZnO NWs provides a smart surface mesh which can be switched between "oil-removing" and "water-removing" modes. It was found that for more than 10 cycles of mesh reutilization in both modes alternatively, the separation efficiency of 99.9% stayed relatively invariant, indicating a prolonged antifouling property and excellent recyclability. This work provides a simple, fast, cost-effective, and on-demand solution for oily wastewater treatment and opens up new perspectives in the field of controllable oil-water separation.

Antimicrobial Properties of Teas and Their Extracts in vitro

Tea has recently received the attention of pharmaceutical and scientific communities due to the plethora of natural therapeutic compounds. As a result, numerous researches have been published in a bid to validate their biological activity. Moreover, major attention has been drawn to antimicrobial activities of tea. Being rich in phenolic compounds, tea has the preventive potential for colon, esophageal, and lung cancers, as well as urinary infections and dental caries, among others. The venture of this review was to illustrate the emerging findings on the antimicrobial properties of different teas and tea extracts, which have been obtained from several in vitro studies investigating the effects of these extracts against different microorganisms. Resistance to antimicrobial agents has become an increasingly important and urgent global problem. The extracts of tea origin as antimicrobial agents with new mechanisms of resistance would serve an alternative way of antimicrobial chemotherapy targeting the inhibition of microbial growth and the spread of antibiotic resistance with potential use in pharmaceutical, cosmetic, and food industries.

Utilization of services for institutional deliveries in Gorkha District

BACKGROUND

Adequate health services for improving maternal and neonatal health is an important global health issues. Institutional delivery is most important component to address maternal and neonatal issue. Institutional delivery service utilization assures safe birth and minimizes the maternal morbidity and mortality. This study was aimed to assess the utilization of institutional delivery service among the mothers of Gorkha district.

METHODS

A cross sectional study of 180 mothers having child below 2 years residing in Palungtar municipality was done between March to July 2015. Information was collected by using an interviewer administered semi-structured questionnaire. Chi-square test was used to for data analysis.

RESULTS

Of total, 93.3% of the mother gave birth to their current child at health institution. The study variables like age at marriage, knowledge on delivery incentive, long waiting hours at health facility, Information on maternal health before current pregnancy, age at first pregnancy, gestational age at first ANC visit and women knowing differences between home and institutional delivery were independent factors influencing utilization of institutional delivery service.

CONCLUSIONS

Promotion of information, education and communication on maternal health services and delivery incentives could result in utilization of institutional delivery services.

Comparative study of immediate functional loading and immediate non-functional loading of monocortical implants

BACKGROUND

Attempts to shorten the overall length of treatment have focused on immediate loading, subsequent to implant placement. Prosthetic rehabilitation immediately after implant placement can be either functional or non-functional in nature. There is paucity of literature on the comparative evaluation of immediate functional and immediate non-functional loading of implants. This in-vivo study was undertaken to comparatively evaluate Immediate Functional Loading and Immediate Non-Functional Loading of monocortical implants with a follow-up period of 18 months.

METHODS

50 partially edentulous cases were selected for the study. The cases were divided into two groups. In first group (Group-1), 25 implants were subjected to immediate functional loading. In second group (Group-2), 25 implants were subjected to immediate non-functional loading. The crestal bone loss, clinical stability and degree of osseointegration of these two groups were comparatively evaluated.

RESULTS

The crestal bone loss in both groups was within acceptable limits. The implant stability, which is a reflection of the status of bone-to-implant interface, was comparable in both the groups at different time intervals. Although, the ISQ values in Group-2 were slightly higher than those in Group-1, the results were not statistically significant. Radiodensity indicating degree of osseointegration at different time intervals in both groups was also comparable.

CONCLUSION

Both the IFL and INFL protocols can be undertaken satisfactorily in rehabilitation using endosseous implants; however, the main factors for success in IFL and INFL are case selection, meticulous treatment planning and the precision of technique.

Greenhouse gases emission from soils under major crops in Northwest India

Quantification of greenhouse gases (GHGs) emissions from agriculture is necessary to prepare the national inventories and to develop the mitigation strategies. Field experiments were conducted during 2008-2010 at the experimental farm of the Indian Agricultural Research Institute, New Delhi, India to quantify nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) emissions from soils under cereals, pulses, millets, and oilseed crops. Total cumulative N2O emissions were significantly different (P>0.05) among the crop types. Emission of N2O as percentage of applied N was the highest in pulses (0.67%) followed by oilseeds (0.55%), millets (0.43%) and cereals (0.40%). The emission increased with increasing rate of N application (r(2)=0.74, P<0.05). The cumulative flux of CH4 from the rice crop was 28.64±4.40 kg ha(-1), while the mean seasonal integrated flux of CO2 from soils ranged from 3058±236 to 3616±157 kg CO2 ha(-1) under different crops. The global warming potential (GWP) of crops varied between 3053 kg CO2 eq. ha(-1) (pigeon pea) and 3968 kg CO2 eq. ha(-1) (wheat). The carbon equivalent emission (CEE) was least in pigeon pea (833 kg C ha(-1)) and largest in wheat (1042 kg C ha(-1)). The GWP per unit of economic yield was the highest in pulses and the lowest in cereal crops. The uncertainties in emission values varied from 4.6 to 22.0%. These emission values will be useful in updating the GHGs emission inventory of Indian agriculture.

Potential of native shrubs Haloxylon salicornicum and Calligonum Polygonoides for restoration of degraded lands in Arid Western Rajasthan, India

Shrub-induced soil property spatial heterogeneity is common in arid and semi-arid ecosystems and aids desertified land restoration. However, the effectiveness of this technique may rely on the plant species used and the habitat conditions present. To assess the degree to which planting two native species, Haloxylon salicornicum and Calligonum polygonoides, facilitates degraded land restoration, soil and herbaceous plant community properties were measured 7 years after planting. Soil samples were extracted at two depths (0-5 and 5-20 cm) from three sub-habitats, i.e., under the shrub canopy, from alleys between shrubs and from the open area. Shrub planting increased the quantity of silt + clay content (30-39 %); enhanced water holding capacities (24-30 %); increased the levels of organic carbon (48-69 %), available nitrogen (31-47 %), available phosphorus (32-41 %), and electrical conductivity (21-33 %); and decreased the pH (7-12 %) and bulk density levels (5-6 %) in the surface layer of soils beneath the canopy. Soil property changes were more significant at the surface (0-5 cm) than in the deeper layer (5-20 cm), and were more pronounced under H. salicornicum than under C. polygonoides. Furthermore, the density and biomass levels of herbaceous plants were 1.1 to 1.2 and 1.4 to 1.6 times greater, respectively, in the shrub alleys than in open area. H. salicornicum induced more robust soil amelioration and herbaceous plant facilitative properties than did C. polygonoides. Artificially planting these shrubs may thus be employed to restore degraded areas of arid regions.

Poland's syndrome with unusual hand and chest anomalies: a rare case report

Poland's syndrome is a rare congenital anomaly consisting of a unilateral absence of the pectoralis major, ipsilateral muscle, hand anomaly and occasionally associated other malformations of the chest wall and breast. Many structural and functional abnormalities have been described in association with this syndrome. We report an incidentally diagnosed case in a 27-year-old male patient who presented to us with symbrachydactyly. In addition to this, anterior depression of 2nd, 3rd and 4th ribs and bifid (forked) 5th rib was present on radiological investigations. The body of sternum was short and deformed on the right side with absence of xiphoid process. All middle phalanges were absent on righthand. It is a rare variant of Poland's syndrome.

Role of the faecolith in modern-day appendicitis

Introduction

The prevailing view on appendicitis is that the main aetiology is obstruction owing to faecoliths in adults and lymphoid hyperplasia in children. Faecoliths on imaging studies are believed to correlate well with appendicitis.

Methods

A retrospective chart review was conducted of 1,014 emergency appendicectomy patients between 2001 and 2011. Faecolith prevalence in adult and paediatric appendicectomy specimens with and without perforation was studied. The sensitivity and positive predictive value (PPV) of computed tomography (CT) for identifying faecoliths in the pathology specimen were examined.

Results

Overall, faecoliths were found in 18.1% (178/986) of appendicitis specimens and 28.6% (8/28) of negative appendicectomies. Faecolith prevalence for positive cases was 29.9% (79/264) in paediatric patients and 13.7% (99/722) in adults (p<0.05). Faecolith prevalence was 39.4% in perforated appendicitis but only 14.6% in non-perforated appendicitis (p<0.05). In adults, faecolith prevalence was 27.5% in perforated appendicitis and 12.0% in non-perforated appendicitis (p<0.05) while in paediatric patients, it was 56.1% in perforated appendicitis and 22.7% in non-perforated appendicitis (p=0.00). Sensitivity and PPV of preoperative CT in identifying faecoliths on pathology were 53.1% (86/162) and 44.8% (86/192) respectively.

Conclusions

Faecolith prevalence is too low to consider the faecolith the most common cause of non-perforated appendicitis. Faecoliths are more prevalent in paediatric appendicitis than in adult appendicitis. Preoperative CT is an unreliable predictor of faecoliths in pathology specimens.

Chemical and genetic diversity among some wild stands of Calligonum polygonoides (Polygonaceae) from the Thar Desert of Rajasthan

The arid Western Rajasthan, where the Thar Desert of India is immersed, is mostly covered by sand dunes, a common landscape. The region has confronted with fragilities of natural resources, low, erratic and ill-distributed rainfall, and is covered up with many perennial hardy shrubs. Calligonumpolygonoides, the most common perennial shrub, is widely present in some localities of this Thar Desert. In this study, we evaluated the diversity present among 54 wild Calligonum polygonoides plants, sampled from eight different locations within the Thar Desert. Our methods included chemical/nutritional characteristics and random amplified polymorphic DNA (RAPD). Both chemical and molecular methods produced wider range of diversity, however, RAPD detected comparatively more diversity. A total of 163 band positions were produced by ten RAPD primers, of which 147 were found polymorphic with 90.18% polymorphism. RAPD-based Jaccard's similarity coefficients ranged from 0.43-0.89. The analysis of various chemical and mineral constituents revealed that phog is an excellent source of calcium, potassium and phosphorous while relatively poor in zinc. Among minerals, average potassium content was found maximum (2 430mg/100g) with 0.14 CV. Zinc was observed comparably less in quantity while highest variable with CV 0.73. The chemical-based Manhattan dissimilarity coefficient values ranged from 0.01-0.22 with an average of 0.12. The comparison of the clusters obtained based on the chemical and mineral parameters with those of the RAPD data showed that the groups formed in both cases showed different patterns of relationships among the samples. Broader range of diversity might be due to the out breeding behavior of C. polygonoides and indicates the good adaptability of the plants in the region studied. However, low diversity observed in the Bikaner province is alarming and suggests that anthropogenic activities leading to heavy population disturbances can affect the genetic composition of the species in a considerable way.

Flexible denture base material: A viable alternative to conventional acrylic denture base material

Although clinician's skills and experience play a major role in designing and fabrication of the optimum prosthodontic restorations, the selection of denture resins is equally important, especially when the patient has been using the prostheses since long. Eighteen cases who were not satisfied with their conventional acrylic dentures were selected. They were provided flexible dentures along with a questionnaire to precisely evaluate the advantages of new material. Prosthodontic planning & observations regarding this material are discussed on various parameters.